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In recent years, wireless communication has been widely adopted in the field of industrial systems. Compared with traditional wired control and monitoring systems, wireless control and monitoring systems are cost-effective and easy to deploy. On the other hand, IEEE 802.11-based wireless technology is widely applied in many areas due to its popularity, flexibility and ease of management, which makes it a good candidate for various industrial wireless control and monitoring applications with different requirements. However, real-time wireless control and monitoring applications usually have varying degrees of timeliness requirements, and the basic IEEE 802.11 MAC mechanism cannot support such requirements due to its inherent drawbacks. Therefore, in this paper we intend to produce a comprehensive survey and classification of the recent deterministic enhancement approaches in IEEE 802.11 networks, which can be applied in wireless control and monitoring systems with different real-time requirements. We explain each mechanism briefly, and give an extensive comparison of the features (especially the timeliness level) of all described MAC mechanisms. Finally, we conclude this paper by identifying some open research issues for future consideration.

Smart building equipment and automation systems often become a target of attacks and are used for attacking other targets located out of the Home Area Network. Attacks are often related to changes in traffic volume, disturbed packet flow or excessive energy consumption. Their symptoms can be recognized and interpreted locally, using software agent at Home Gateway. Although anomalies are detected locally at the Home Gateway, they can be exploited globally. Thus, it is significantly important to detect global attack attempts through anomalies correlation. Our proposal in this paper is the involvement of the Network Operator in Home Area Network security. Our paper describes a novel strategy for anomaly detection that consists of shared responsibilities between user and network provider. The proposed two-tier Intrusion Detection System uses a machine learning method for classifying the monitoring records and searching suspicious anomalies across the network at the service provider's data center. Result show that local anomaly detection combined with anomaly correlation at the service providers level can provide reliable information on the most frequent IoT devices misbehavior which may be caused by infection. National Centre for Research and Development (NCBiR) in Poland

Deployment of small cells along with macro base stations is considered as one of the most promising solutions for increasing the capacity and coverage of the wireless networks. Wireless networks comprising of various levels of base stations are called heterogeneous cellular networks (HCN). In this paper, the structure of HCNs is utilized for transmission of scalable video coding (SVC). In such networks, higher density of the stations increases the probability of handover for mobile users. Packet loss, delay, and failure in handover degrade the quality of media streaming services. In the proposed scheme, for two-layer spatially scalable coded video, due to the umbrella coverage of a macrocell, macro base station (MBS) is suitable for transmission of the base layer content to the users within its coverage area to minimize the costs of handover. Moreover, the enhancement layer is transmitted by an access point (AP) offering maximum biased received power. To evaluate the performance of the proposed scheme, first, the data rate distributions for a stationary user are modeled. Then, using the tools from stochastic geometry, theoretical expressions are derived for both horizontal and vertical handover probabilities experienced by a mobile user. In addition, two performance metrics are quantified to analyze the performance of the proposed scheme. These are the standard-definition (SD) outage probability and the high-definition probability. In this paper we show that using SVC over HCNs the SD outage probability is reduced by 50% to 55% compared to the conventional methods, where all layers receive from one AP.

Source Location Privacy (SLP) is becoming important for wireless sensor networks where the source of messages is kept hidden from an attacker. In this paper, we conjecture that similar traffic perturbation to altering the routing protocol can be achieved at the link layer through assignment of time slots to nodes. This paper presents a multi-objective optimisation problem where SLP, schedule latency and final attacker distance are criteria. We employ genetic algorithms to generate Pareto-optimal schedules using two fitness criteria, examining the Pareto efficiency of selecting either and confirming the efficiency by performing simulations which show a near optimal capture ratio.

Wireless sensor networks (WSNs) consist of a large number of sensor nodes which usually have very limited energy and are deployed in the wild environment. The batteries of the nodes cannot be recharged or replaced. Therefore, it is necessary to design energy-efficient routing protocols to maximize the network lifetime. This paper proposes an annulus sector grid aided routing protocol (ASGRP) which uses an annulus sector grid clustering method to improve WSNs’ energy efficiency and prolong the network lifetime. The annulus sector grid clustering method based on arithmetic progression is presented to divide the network area into clusters with various sizes. From the base station (BS) outwards, the network area is divided into different levels with incremental equal difference distance. This paper also presents an inter-level multi-hop routing algorithm to improve the energy efficiency of data transmission between the BS and cluster head (CH) nodes. The algorithm combines the communication management (CM) nodes with CH nodes to establish routes to transmit data. Simulation results show that compared with multi-hop EEBCDA, EEMRP and CAMP, ASGRP prolongs the network lifetime by 24.36–70.68% in the 200 m × 200 m network and 25.47–90.34% in the 400 m × 400 m network. The proposed protocol significantly reduces the energy consumption of each round and has better performance of energy balance and efficiency in the larger network area.

Wireless sensor nodes are the main components in wireless sensor networks. Such devices affect the performance and the accuracy of the network. Countless commercial and research nodes exist and their comparison is critical. Literature surveys do not provide a comprehensive overview about all the existing nodes’ technologies. The main goal of this paper is to provide a deep overview of the current state of the art with enough background, to allow to design evolutionary nodes and to analyze thoroughly the node design components and application trends. This survey is helpful not only for researchers but also for industry. Therefore, a work that gives an inclusive overview is required. With the exponential growth of technologies and electronics, it is essential to know the latest trends, the innovative future directions and to eliminate redundancies. This paper allows a global overview about existing nodes in industrial and research works to get decisions about the future of node fabrication.

A Wireless Sensor Network (WSN) is a group of tiny power-constrained nodes that cover a vast region of interest (ROI), sense and communicate it to the Base Station (BS). The main challenge encountered in WSNs is how to cover the ROI perfectly and transmit the monitored data to the BS for the longest possible time. Although many energy-efficient routing protocols for periodic monitoring applications were recently introduced, the dynamic nature and complex environments of WSN applications make building such protocols a considerable challenge. In this paper, the node degree of the Degree Constrained Tree (DCT) in homogeneous proactive WSN is studied analytically for the network with one BS that is outside the ROI. Since the node degree affects the network lifetime of these types of networks, the optimum node degree for minimum energy consumption in DCT is derived. Subsequently, the paper proposes a Collaborative Distributed Antenna (CDA) routing protocol that is based on distributed antenna theory to provide fair load distribution in terms of transmission energy. CDA is based on DCT with optimal node degree and is designed for periodic data monitoring in WSN applications. The experimental results prove our analysis to emphasize that using optimal node degree in DCT doubles its network lifetime compared to using other node degrees. Moreover, adding CDA to DCT with optimal node degree is proved to double the network stability period and reduce the ratio between instability period and the network lifetime to its half. It also shows 25% increase in network lifetime and minimum rate of node loss compared to its peers, such that the lifetime of half the nodes is preserved until few rounds before the end of network lifetime.

Low-duty-cycle mode is widely adopted in energy-critical wireless sensor networks (WSNs). Such mode greatly reduces the energy waste caused by idle listening. However, it brings many new challenges for broadcasting. This paper mainly focuses on the minimum cost broadcast problem for low-duty-cycle WSNs. We propose a novel opportunistic broadcasting transmission model, which makes full use of the broadcast nature of wireless media to reduce the total energy consumption for broadcasting. The key idea is to allow nodes to defer their wake-up slots to opportunistically overhear the broadcasting messages sent by their neighbors, which could reduce the total energy consumption for broadcasting but increase the average end-to-end broadcasting delay. In this paper, we define a generalized broadcasting cost function, which can make a flexible tradeoff between average end-to-end broadcasting delay and total energy consumption for broadcasting, to adaptively meet various broadcasting performance requirements. Our target is to utilize the opportunistic broadcasting transmission model to design an efficient broadcasting schedule for low-duty-cycle WSNs, so that the broadcasting cost function is minimized. First, we define the Receiver-Constrained Minimum Cost Single-hop Broadcast Problem (RC-MCSB) and propose an optimal solution with a polynomial running time. Next, we extend the solution of RC-MCSB problem to our target problem and present a novel and efficient bottom-up solution. The simulation results have verified the significant performance advantage of our proposed bottom-up solution over the existing top-down solutions and the other solutions.

Information Centric Networking (ICN) is a paradigm in which the network layer provides users with access to content by names, instead of providing communication channels between hosts. The ICN paradigm promises to offer a set of advantages with respect to existing (IP) networks for the support of the large majority of current traffic. In this paper, we consider the deployment of ICN by exploiting the Software Defined Networking (SDN) architecture. SDN is characterized by a logically centralized control plane and a well-defined separation between data and control planes. An SDN-enabled network facilitates the introduction of ICN functionality, without requiring a complex transition strategy and the re-deployment of new ICN capable hardware. More in details, in this paper we provide: i) a solution to support ICN by exploiting SDN, extending a previous work of ours; ii) design and implement an open reference environment to deploy and test the ICN over SDN solutions over local and distributed testbeds; iii) design and implementation of a set of Caching policies that leverage on the ICN over SDN approach; iv) performance evaluation of key aspects of the ICN over SDN architecture and of the designed caching policies. All the source code and the monitoring suite are publicly available. To the best of our knowledge, there are no other similar solutions available in Open Source, nor similar emulation platforms, including also a comprehensive set of monitoring tools.

The paper focuses on the problem of effective and resilient network resources management under condition of increasing Internet traffic. Multilayer automatic optical networks are considered as a solution usually indicated as the most appropriate for the future Internet. In this paper, we propose a Survivable Automatic Hidden Bypasses approach to enhance resource utilization and reliability in multilayer optical networks. Our solution uses the Software-Defined Networking concept to automatically create or remove hidden bypasses which are not visible at the network layer. We propose a novel survivability metric which is applied during optical bypass creation in order to handle network failures in a proactive manner. Such an approach contrasts with the most common one where bypasses are considered as a mechanism to handle network failures. We combine the metric with different restoration schemas and investigate the proposed mechanism under three failure scenarios. The mechanism of hidden bypasses increases throughput and reduces transmission delays while novel proactive survivability mechanisms neutralize negative impact of network failures.

This paper focuses on the congestion control issues in Unmanned Aerial Vehicle (UAV) Swarm Networks (USNs). In a USN, many network factors can cause segment loss, including dynamic swarming, high mobility, and link fading loss. With traditional transport layer protocols such as Transmission Control Protocol (TCP), these losses are interpreted as congestion events and will cause the data sending rate being decreased dramatically, therefore impacting throughput. In this paper, a learning-based adaptive network coding scheme is proposed to handle segment loss. In this scheme, a certain amount of redundancy is attached to the original data. If the segment loss is caused by random factors (such as radio interference), the lost segments are retrieved by decoding. However, if the loss is caused by congestion, the sender will retransmit the lost segments and decrease the sending rate. The coding rate is a critical factor, which should guarantee that the random loss can be retrieved by decoding while the congestion loss triggers retransmission and sending rate deduction. To achieve this goal, a Deep Learning (DL) algorithm is proposed, which comprehensively considers the wireless network conditions and dynamically optimizes the coding rate. Our experimental results show that the DL-based network coding scheme provides improved throughput and end-to-end delay compared to the TCP and general network coding schemes.

Delay tolerant networks (DTNs) are characterized by the absence of the end-to-end path due to intermittent connectivity among the nodes. Such networks are potentially applicable in the challenging scenarios, e.g. interplanetary communication, post-disaster environment, where traditional communication infrastructure is partially or fully absent. Each application requires some quality of service (QoS) guarantees for the traffic flow. QoS support cannot be provided to a network without QoS provisioning. However, QoS provisioning in a DTN is more difficult task than traditional networks, because of its inherent characteristics. There exist various issues which affect QoS in DTNs. In this paper, we explore the issues that influence QoS in DTNs. Subsequently, we analyze the effects of the issues on the QoS in terms of delivery ratio, packet drop etc. We also review various QoS management solutions in DTNs. The schemes on the QoS issues are classified based on their underlying approaches and key features. The paper is concluded with a brief discussion on some of the open research issues regarding QoS in DTNs.

Smart Gateway Diversity (SGD) is a fundamental concept introduced to maintain high service availability in High Throughput Satellites (HTS) working at frequency bands above Ka-band. This paper proposes a novel approach for the SGD management logic that takes into account the “graceful degradation” of the link for triggering a handover of traffic among gateways (GWs.) Moreover, the paper proposes a Software Defined Network (SDN) implementation of the handover control procedure and an algorithm for building the flows matrices of the SDN switches that guarantees a fair balancing of traffic among the gateways, thus allowing a better exploitation of resources and maximization of the overall operational capacity of the HTS system. The SDN paradigm, by allowing efficient network programmability and real time re-configuration of the flow tables, enables the possibility to implement dynamic and granular resource allocation; this is a fundamental requirement for the proposed novel SGD network management approach, where re-configuration is triggered by smaller and more frequent signal-to-noise ratio (SNR) fluctuations. The performance of the proposed handover control procedures have been evaluated over real Q/V band link by using the experimental data collected through the TDP5 “Aldo Paraboni” payload embarked on the Alphasat satellite. Performance results show a gain of 40% in terms of aggregated capacity of the system with respect to the case of using an on–off SGD management logic.

Virtual Private LAN services (VPLS) is a Layer 2 Virtual Private Network (L2VPN) service that has gained immense popularity due to a number of its features, such as protocol independence, multipoint-to-multipoint mesh connectivity, robust security, low operational cost (in terms of optimal resource utilization), and high scalability. In addition to the traditional VPLS architectures, novel VPLS solutions have been designed leveraging new emerging paradigms, such as Software Defined Networking (SDN) and Network Function Virtualization (NFV), to keep up with the increasing demand. These emerging solutions help in enhancing scalability, strengthening security, and optimizing resource utilization. This paper aims to conduct an in-depth survey of various VPLS architectures and highlight different characteristics through insightful comparisons. Moreover, the article discusses numerous technical aspects such as security, scalability, compatibility, tunnel management, operational issues, and complexity, along with the lessons learned. Finally, the paper outlines future research directions related to VPLS. To the best of our knowledge, this paper is the first to furnish a detailed survey of VPLS.

Recently, Chuang et al. introduced a secure password authentication mechanism, called SPAM, for seamless handovers in Proxy Mobile IPv6 (PMIPv6). SPAM aimed at providing high security properties while optimizing handover latency and computation overhead, but as pointed out in this paper SPAM is vulnerable to replay and malicious insider attacks as well as the compromise of a single node. In this paper, a new Security Protocol for Fast PMIPv6, called SPFP, is proposed that provides a ticket-based secure handover for mobile nodes (MNs). In SPFP, a ticket containing authentication materials is used for fast handover authentication when an MN changes its attachment point. Moreover, the MN’s anonymity is supported for preserving location privacy. Detailed operations of initial authentication and handover authentication are presented with message flows. The formal security analysis of SPFP is provided with results of qualitative analysis and quantitative analysis.

The carrier sensing multiple access with collision avoidance (CSMA/CA) protocol is a widely-adopted MAC protocol in the current wireless networks, but the quality of service (QoS) cannot be guaranteed due to random access. Investigations reveal that the collision avoidance mechanism which relies on the binary exponential backoff scheme is the root cause of QoS issue. Therefore, this paper first proposes a CSMA with automatic synchronization (CSMA/AS) MAC protocol to mitigate the collision problem caused by random access. By CSMA/AS, all the stations can be synchronized and then served in a round-robin fashion without contention collisions. Even if a new station joins, the wireless network can also quickly converge and go back to the synchronized state. The simulation results show that the proposed CSMA/AS protocol can fully mitigate the issues caused by random access, such as the severe contention collisions and large delay variation. In addition, this paper demonstrates how to provide hard QoS guarantees, such as fairness, rate guarantee, and delay guarantee, which cannot be achieved by the existing CSMA-based protocols. Because CSMA/CA does not rely on any additional control message, the implementation complexity of CSMA/AS is similar to that of legacy CSMA/CA protocols.

In this paper, we devise an analytical framework for the performance evaluation of communication void-handling algorithms designed for underwater wireless sensor networks (UWSNs). Geographic and opportunistic routing (GOR) have been shown efficient for multi-hop data delivery in UWSNs. However, geo-routing suffers from a serious drawback known as communication void region. The communication void region problem occurs when a source node does not have a neighbor node in closer proximity to the destination that can continue forwarding the packet. Whenever a data packet reaches a node in a void region, the data packet should be re-routed from a void-handling procedure or discarded. In this paper, we model the three main methodologies that have been used for the design of void-handling algorithms for geographic and opportunistic routing protocols in UWSNs. Our proposed analytical framework considers the characteristics of underwater sensor networks, network density and traffic load, underwater environment and acoustic channel, as well as the characteristics of the power control, bypassing void region and mobility assisted void-handling paradigms. The devised analytical framework is aimed to fill the gap in the literature of analytical tools that allow the performance evaluation of the trade-offs of each paradigm along different scenarios of UWSNs. The proposed model provides insights for the further design of void-handling algorithms in different underwater application and sensor network configurations. Numerical results show that the widely used bypassing void region approach is not effectively for moderate- and high-density UWSN scenarios. Conversely, topology control-based approaches (power control and mobility-assisted) are preferable as they create additional links. However, the use of void-handling procedures increased the network energy consumption, which made each paradigm unsuitable for specific scenarios revealed by the proposed modeling.

International audience; This paper studies the routing protocol "Lightweight On-demand Ad hoc Distance-vector Routing Protocol Next Generation (LOADng)", designed to enable efficient, scalable and secure routing in low power and lossy networks. As a reactive protocol, it does not maintain a routing table for all destinations in the network, but initiates a route discovery to a destination only when there is data to be sent to that destination to reduce routing overhead and memory consumption. Designed with a modular approach, LOADng can be extended with additional components for adapting the protocol to different topologies, traffic, and data-link layer characteristics. This paper studies several such additional components for extending LOADng: support for smart route requests and expanding ring search, an extension permitting maintaining collection trees, a fast rerouting extension. All those extensions are examined from the aspects of specification, interoperability with other mechanisms, security vulnerabilities, performance and applicability. A general framework is also proposed to secure the routing protocol.

This paper addresses new challenges arising from the emergence of Bluetooth mesh and its rapid adoption in Internet of Things (IoT) and Industrial IoT. One of the main problems associated with Bluetooth mesh is the power consumption of the mesh nodes, since the network needs to be scanned constantly to receive and relay messages. In order to reduce the energy consumption in the nodes where possible, the friendship mechanism is provided as a solution by the Bluetooth mesh specification. The friendship mechanism enables Low Power Nodes (LPNs) to spend most of their lifetime in sleep mode without losing the messages addressed to them. For this purpose, a node that is constantly in scan mode, called friend node (FN), stores these messages, sending them on request. This mechanism works with a stop-and-wait protocol, resulting in inefficient channel utilisation. However, to the best of our knowledge, there are no proposals for the improvement of this mechanism, likely due to its novelty. This paper studies different approaches for the improvement of the friendship mechanism: improving the Bearer Layer, improving time synchronisation and improving advertising channel utilisation. The results of this study reveal that each of the proposals presents a limitation that makes its final implementation unfeasible, and thus the challenge arises of developing a proposal for its optimisation. Accordingly, this work presents a proposal to improve the friendship mechanism with Burst Transmissions and Listen Before Transmit (BTLBT), which has been evaluated and validated in real hardware platforms. The results obtained for 4 LPNs show a reduction in the time required to receive the FN messages, as well as a 66.65% reduction in the time required to scan for each message. Finally, a consumption study is presented, where the results show that our proposal achieves a 19.81% improvement in lifetime compared to the standard friendship mechanism.

This paper builds on the UE-based Virtual Base Station (UE-VBS) concept, which enables the Smartphones (i.e., UEs) of the general population to be enhanced with Base Station and Relay Node functionalities and be embedded as an integral part of the Mobile Network Infrastructure, offering relief in stressful or overloaded situations. This paper focuses on the selection process of eligible-UEs that will be activated on-the-fly into UE-VBSs to complement and support the Mobile Network infrastructure, either as virtual small cells (VSCs) or virtual relay nodes (VRNs). We adopt a Modified Affinity Propagation Clustering (MAPC) algorithm to select UE-VBSs to act as VSCs for capacity/data rate expansion in areas where the infrastructure is weak and a more effective and agile network operation is needed. Additionally, to provide for a more spectrum efficient backhauling of mobile data traffic from the VSCs towards the BS, the Multi-hop Load balanced Geographical Path selection (MLGP) algorithm is proposed. The MAPC and MLGP algorithms are implemented and evaluated in MATLAB and also validated using the NS3 network simulator, with mobile data traffic modeled as a non-uniform distribution with respect to the time and space domain. The results demonstrated that the proposed approaches improve the network performance in terms of throughput, delay and jitter.

The wide network applications of Internet of Things (IoT) urge to integrate the different wireless networking technologies. However, the future generation technologies like Software Defined Networking (SDN) can be useful to alleviate the associated challenges such as security, installation issues, coverage, etc. The growing number of IoT users produce massive volume of traffic causing heavy network load conditions, resulting in the state of network congestion. The network congestion may cause severe performance degradation issues such as frequent packet drops, longer delays, low throughput, etc. Thus, a promising solution is needed to reduce and/or prevent the network congestion. This paper presents an Optimized load balancing based Admission Control Mechanism (Opt-ACM) for effective network flow management resulting in the reduced network congestion. In addition to this, the paper highlights the challenges of the existing solutions, and discusses a Software Defined Hybrid Wireless based IoT (SDHW-IoT) network architecture consisting of Software Defined Wireless Sensor Network (SDWSN) and Software Defined Wireless Mesh Network (SDWMN). To validate the efficiency of Opt-ACM, a Mixed-Integer Linear Programming (MILP) based optimization problem is formulated and tested using a well-known mathematical optimization solver called Gurobi. Additionally, Opt-ACM is also emulated in Mininet-Wifi with varying network scenarios against some traditional (OLSR and OSPF) and state-of-the-art (FACOR and EASDN) approaches. Opt-ACM achieves an overall efficiency of 9.47% and 12.32% over other approaches for Packet Delivery Ratio (PDR) and Packet Loss Ratio (PLR) respectively. Similarly, an average improved efficiency of 26.77% and 33.10% is achieved with respect to the Average Delay (AD) and Average Jitter (AJ) metrics respectively.

Digitalization is a journey that has been started and put ICT industry in a crucial situation to provide required infrastructure for diverse range of data hungry, short tempered applications and services. One of the main technologies that will pave the way towards new digital ecosystem is fifth Generation of mobile technology. To meet 5G network service requirements, innovative architectures, technologies and standards focusing on cloudification are employed. Cloudification of network functions along with the use of virtualized network functions (VNFs) and containerized network functions (CNFs) allows agile and scalable service provisioning. The use of VNFs and CNFs has been started from core and networking middleboxes but then extended to RAN functions. Open radio access network (O-RAN) proposes an interoperable and standard architecture for cloudified RAN. The main idea behind this architecture is to make RAN more flexible. O-RAN allows different layers of RAN to be split and deployed as virtual function and openly communicate with each other for service provisioning. In this paper, we model an End-to-End mobile network operator (MNO) employing O-RAN. We consider a mobile network architecture, with three layer hierarchical data centers (Local, Regional, and Core) to add flexibility in resource allocation, and increase reliability, taking the advantages of O-RAN. MNO receives various service function requests (SFRs) requiring accommodation on the network. We assume RAN and core functions are deployed as CNFs on the data centers. Users of SFRs connects to remote radio heads (RRH) to receive the service. In this paper, we mathematically model the CNF placement and resource allocation of an O-RAN enabled LTE/5G network while trying to minimize the End-to-End delay of the data plane. We study the problem in two different cases First, we assume that the SFR traffic traverse through a single path across the RAN functions and model this problem. This is a mixed integer non-linear programming problem. With some change of variables, we make it a linear mixed integer programming problem but it is still non-trivial to solve. Then, we model the problem for the case where traffic of an SFR can be split and be served via multiple CNFs. We proposed a gradient based scheme to solve the minimum delay problem in this case. Experimental results indicate that by increasing the number of service requests in a network, the proposed GBMD(Gradient-Based Minimum Delay) algorithm serves up to 90% End-to-End Delay decrease. Another improvement on the performance of a network will occur by levering GBMD algorithm for around 72% End-to-End delay reduction in case of limited resources.

Information centric networking (ICN) aims to transform todays Internet from a host-centric model to a content-centric one by caching content internally within the network at storage-enabled nodes. Recently, multiple routing and cache management strategies have been proposed [1,2,3,4,5,6] to improve the user-level performance, primarily latency in ICN. In this paper, we define latency as the download time for a piece of content. In this paper, we propose a simple routing strategy that leverages the concept of characteristic time to improve latency. Characteristic time for a content in a cache indicates the amount of time in future a recently accessed content is likely to remain in that cache. Our proposed algorithm namely, Characteristic Time Routing (CTR) uses characteristic time information to forward requests to caches where the content is likely to be found. CTR augments native routing strategies (e.g., Dijkstras algorithm), works with existing cache management and cache replacement policies and thus can be implemented in ICN prototypes with minimal effort. We perform exhaustive simulation in the Icarus simulator [7] using realistic Internet topologies (e.g., GEANT, WIDE, TISCALI, ROCKETFUEL [8]) and demonstrate that the CTR algorithm provides approximately 1050% improvement in latency over state-of-the-art routing and caching management strategies for ICN for a wide range of simulation parameters.

TCP remains the dominant transport protocol for Internet traffic. It is usually considered to have its sending rate covered by a sliding window congestion control mechanism. However, in addition to this normal congestion control, a number of other mechanisms limit TCP throughput. This paper analyses the extent to which network, host and application settings define flow throughput over time and across autonomous systems. Our study draws on data from a longitudinal study spanning five years of passive traces collected from a single transit link. Mechanisms for this include limiting by application, interference with the TCP window control mechanism and artificial limitations on maximum window sizes by the operating system. This paper uses a large data set to assess the impact of each mechanism. We conclude that more than half of all heavy-hitter inbound traffic remains throttled by constraints beyond network capacity. For this data set, TCP congestion control is no longer the dominant mechanism that moderates throughput.

Recently, researchers introduced energy-efficient dynamic routing protocols for wireless sensor networks to avoid the premature end of network lifetime. This paper addresses the routing hole problem due to energy depletion and the trade-off between the network need for periodic setups to preserve connectivity and power constraints on sensor nodes. The paper solves the problem of the premature end of network lifetime in applications where the base station (BS) is far from the Region Of Interest (ROI). Therefore, we propose two distributed, energy-efficient, and connectivity-aware routing protocols for solving the routing hole problem. These protocols are On-Hole Children Reconnection (OHCR) with local nature and On-Hole Alert (OHA) with global nature. The proposed protocols preserve the connectivity of all single setup phase, single path networks with any topology in an energy efficient manner by avoiding topology reformation overhead. The simulation results proved that the proposed protocols outperform the recent ones in terms of network lifetime, node loss rate, and network overhead. Such that, the two protocols are examined on both Degree Constrained Tree (DCT) and Shortest Path Tree (SPT) to provide about 50% to 75% increase in network lifetime over the recent energy efficient routing protocols; like UCCGRA and NEECP. Additionally, applying OHCR and OHA to any network topology doesn't affect its stability period, since these protocols are triggered by routing hole occurrence.

Localization in wireless sensor networks (WSNs) is regarded as an emerging technology for numerous cyber-physical system applications, which equips wireless sensors with the capability to report data that is geographically meaningful for location based services and applications. However, due to the increasingly pervasive existence of smart sensors in WSN, a single localization technique that affects the overall performance is not sufficient for all applications. Thus, there have been many significant advances on localization techniques in WSNs in the past few years. The main goal in this paper is to present the state-of-the-art research results and approaches proposed for localization in WSNs. Specifically, we present the recent advances on localization techniques in WSNs by considering a wide variety of factors and categorizing them in terms of data processing (centralized vs. distributed), transmission range (range free vs. range based), mobility (static vs. mobile), operating environments (indoor vs. outdoor), node density (sparse vs. dense), routing, algorithms, etc. The recent localization techniques in WSNs are also summarized in the form of tables. With this paper, readers can have a more thorough understanding of localization in sensor networks, as well as research trends and future research directions in this area.

This paper proposes a modeling of expected link delay (i.e., data delivery delay) on a two-way road segment for carry-and-forward data delivery schemes in vehicular networks. Recently, a lot of vehicles can communicate with each other by dedicated short-range communications (DSRC) for vehicular networking. In the near future, more vehicles will be equipped with DSRC devices because of governmental policies for driving safety. In this paper, we derive a link delay model on a two-way road segment. This link delay model is essential to support multihop infrastructure-to-vehicle or vehicle-to-vehicle data delivery in vehicular networks as disruption tolerant networks. Through simulation, it is shown that our two-way link delay model is more accurate than the legacy two-way link delay model. Furthermore, by applying our model to data unicasting, we show that our model is precise enough to support the efficient data unicasting on vehicular networks.

In recent years, we have witnessed an increase in the popularity of mobile wireless devices and networks, with greater attention devoted to feasibility of opportunistic computing, sensing, and communication. In Mobile Social Networks (MSNs), communication is provided by spatial proximity and social links between peers, where personal devices carried by users communicate directly in a device-to-device mode. On one hand, human mobility provides encounters between peers and opportunities for communication without additional infrastructure; on the other hand, it introduces intermittent connections, network partitions, and long delay, requiring sophisticated message-forwarding mechanisms to improve network performance. Therefore, socially-inspired approaches which consider network structure and personal user features have been proposed to cope with these challenges. However, many studies disregard adaptive policies of message forwarding capable of dealing with variations of these features. In this paper, we investigated message dissemination in MSNs considering external factors such as temperature and seasonal calendar as environmental features capable of model users’preferences and encounters. We evaluated the time of day, the day of the week, and environmental variables such as weather and geographic position as important factors to the collective behavior and spatiotemporal characteristics of urban scenarios. This paper presents an analysis of real data from weather and human mobility, which depict distinct social interactions and spatial features characterized by changes in thermal conditions. Thus, we propose a socially-aware forwarding mechanism that is adaptable to the seasonality of personal preferences. Our experiments indicated that pervasive data can provide useful information towards the design of the next generation of human-centered Opportunistic Networks.

Wireless local area networks (WLANs) can adopt channel hopping technologies in order to avoid unintentional interferences such as radars or microwaves, which function as proactive jamming signals. Even though channel hopping technologies are effective against proactive types of jamming, it has been reported that reactive jammers could attack the targets through scanning busy channels. In this paper, we demonstrate that reactive jamming is only effective against channel hopping WLAN devices in non-dense networks and that it is not effective in dense networks. Then, we propose a new jamming attack called “persistent jamming”, which is a modified reactive jamming that is effective in dense networks. The proposed persistent jamming attack can track a device that switches channels using the following two features, and it can attack the specific target or a target group of devices. The first feature is that the proposed attack can use the partial association ID (PAID), which is included for power saving in the IEEE 802.11ac/af/ah frame headers, to track and jam the targets. The second feature is that it is possible to attack persistently based on device fingerprints in IEEE 802.11a/b/g/n legacy devices. Our evaluation results demonstrate that the proposed persistent jamming can improve the attack efficiency by approximately 80% in dense networks compared with the reactive jamming scheme, and it can also shut down the communication link of the target nodes using 20 dBm of jamming power and a 125 ms response time. In order to defend against the persistent jamming attack, this paper proposes three defense mechanisms for anti-tracking and anti-jamming; a digital fingerprints predistortion, dynamic ID allocation, and dual channel friendly jamming. The experimental results demonstrate that the proposed defense mechanisms are feasible and effective to significantly decrease the device tracking success ratio of the persistent jamming attack.

This paper studies the temporal behavior of communication flows in the Internet. Characterization of flows by temporal patterns supports traffic classification and filtering for network management and network security in situations where full packet data is not accessible (e.g., obfuscated or encrypted traffic) or cannot be analyzed due to privacy concerns or resource limitations. In this paper we define a time activity feature vector that describes the temporal behavior of flows. Later, we use cluster analysis to capture the most common time activity patterns in real internet traffic using traces from the MAWI dataset. We discovered a set of seven time-activity footprints and show that 95.3% of the analyzed flows can be characterized based on such footprints, which represent different behaviors for the three main protocols (4 in TCP, 1 in ICMP and 2 in UDP). In addition, we found that the majority of the observed flows consisted of short, one-time bursts. An in-depth inspection revealed, besides some DNS traffic, the preponderance of a large number of scanning, probing, DoS attacks and backscatter traffic in the network. Flows transmitting meaningful data became outliers among short, one-time bursts of unwanted traffic.

Vehicular Ad-hoc NETworks (VANETs) have lately gained the interest of researchers due to their unique properties of high mobility and constantly changing network topology. As mentioned in IEEE 802.11p which is the standard for VANETs, CSMA is used as the channel access mechanism. However, CSMA causes high contention and leads to lower network performance in terms of packet delivery ratio and average end-to-end delay. Many-to-Many (M2M) communication is a technique which makes use of simultaneous transmission of packets by using Code Division Multiple Access (CDMA). Although M2M communication helps to improve the performance of VANETs, further improvements can be done to fully reap the benefits of M2M communication. In this paper, we suggest piggybacking of information along with M2M communication in a vehicular network scenario. This leads to dissemination of more information from a vehicle at a time, thereby increasing the average packet delivery ratio and average end-to-end delay. Our simulation results confirm that piggybacking along with M2M communication helps to improve network performance in terms of packet delivery ratio and end-to-end delay. We mathematically analyse average packet delivery ratio and average end-to-end delay of such a system by modelling the buffers at vehicles and RSUs as M/M/1 and M/D/1 queues, respectively. Our analytical results are verified by extensive simulations. In M2M communication, vehicles are chosen randomly to enter in a communication session. In this paper, we formulate an optimization problem for selection of vehicles which can enter in a communication session and also propose an efficient vehicle selection algorithm for the same. Our proposed algorithm not only improves the average packet delivery ratio and average end-to-end delay of the network but also significantly reduces the number of packets dropped in the network.

The goal of this paper is to find the requirement and security issues of wireless sensor networks (WSNs) especially in coal mines for safety monitoring and to develop an authentication protocol to provide the security in WSNs. The WSNs help in reducing the hazard and increase the productivity by proper monitoring the equipments and underground conditions. In mines, a sensor in a WSN senses the environment and transmits the data to colliery professionals for further detailed assessment as a minor factual error may cause severe human casualties and large resource destruction that may lead to huge monetary losses. The sensors have limited battery that should be used efficiently in computing the acquired information. In this paper, we present an authentication protocol to overcome the security issues in WSNs by authenticating the users (professionals) and the mechanical sensors. Our protocol requires only light weight functions and low cost in transmission of the messages to save the battery in sensors. We use the BAN (Burrows-Abadi-Needham) logic to ensure the mutual authentication and session key agreement properties. The formal security analysis proves its resilience against various security attacks. For its formal security verification, a widely accepted AVIPSA (Automated Validation of Internet Security Protocols and Applications) tool is used.

Intrusions and intrusive behaviour can be aimed at different parts of the system, ranging from lower-level network attacks intended to disrupt the flow of data in general, to higher-level attacks targeted against specific applications or services. Due to the constant growth of network traffic and the need to inspect the traffic thoroughly, intrusion detection and prevention are becoming increasingly complex and require significant computational resources. This paper presents a distributed, scalable solution for the detection of lower-level Denial-of-Service (DoS) attacks which are executed by transmitting overwhelming amounts of data with the intention of disrupting regular network service. Scalability is achieved by active traffic balancing among multiple traffic processors, exploiting the flexibility and network programmability that Software Defined Networking paradigm brings and packet processing based on device polling. Traffic processors can be elastically added into the pool depending on the traffic volume. The whole system is completely transparent to the external observers. The paper shows that the implemented balancing algorithm further improves the reliability of the intrusion detection.

With the development of the Internet of Things (IoT), the network is required to guarantee the differential Quality of Service (QoS) requirements of the various data flows of various IoT services. Software-defined network (SDN) is envisioned as a promising technique to guarantee the QoS requirements of different services, through separating the control logic from data planes of networks. In order to guarantee the QoS requirements of data flows in SDNs, in this paper we investigate the problem of intelligent routing in SDNs, by leveraging a novel data flow classification method. Combining a variety of machine learning algorithms, a data flow classification method called MACCA2-RF&RF is proposed, in order to identify the data flow category and obtain the QoS requirements. The link parameter is newly designed considering multiple QoS requirements. According to the link parameter, the QoS-guaranteed path selection algorithm is then proposed, which can select QoS guaranteed routing path for different data flows with different QoS requirements. Aiming at the situation that the link is congested, local routing change algorithm is then proposed which only adjusts the links before and after the congested link instead of the entire path. Based on the above, a QoS-guaranteed intelligent routing mechanism called QI-RM in SDN is finally proposed in this paper to achieve QoS guarantee for data flows. The simulation results show that the MACCA2-RF&RF can classify data flows efficiently with an identification accuracy of 99.73%, and the QI-RM can guarantee the QoS requirements of data flows before and after link congestion.

Broadcast is an important primitive in large-scale distributed systems. One application is to enable reliable and efficient communication in large-scale networks such as sensor networks and Internet-of-Things. There is a rich study on achieving reliable broadcast under various kind of failures. In this paper, we use the notion of “trust” to improve the performance of reliable broadcast. We focus on Certified Propagation Algorithm (CPA), one of the simple algorithms that does not rely on a cryptographic infrastructure and has a proven guarantee on resilience (number of node failures tolerated). Specifically, the paper has two main contributions: (i) A new algorithm Trust-CPA – which integrates CPA with trusted nodes – has been proposed and shown to increase the resilience from the original CPA, and (ii) Natural optimization problems related to Trust-CPA have been proposed and studied as well. First, we study the location to place trusted nodes to reduce power consumption while maintaining the same level of resilience. Second, we study two optimizations problems on finding out which set of nodes to “trustify” to increase resilience and reduce speed. For the speed-related optimization problem, we present a greedy heuristic algorithm, and its efficacy has been examined using simulation. We show that our algorithm performs relatively well in geometric random graphs, an appropriate model for large-scale wireless sensor networks.

Nowadays, there is no effective solution to take down P2P botnets. In this paper, we have proposed a probabilistic node-removal method for P2P botnets forming random network, which reduces the resilience of the C&C channel of P2P botnets more effectively compared to other previous methods. We have introduced a new approach for selecting the critical nodes. In our method, based on collecting the receiving times of commands in some bots, the command entry points are identified, and then the critical nodes are determined. Our approach can be used for cases in which the botmaster inject the commands into the botnet from more than one point. If the topology of botnets is unknown, our method can be applied to the reconstructed topology. In this paper, a new metric is defined for accurately measuring the power of the botnet after removing the critical nodes. This metric is compatible with several entry points of the commands. We have validated our method through simulations. The obtained results indicate that we can effectively isolate significantly more nodes from the origin compared to the other node-removal methods. In the best results, we have managed to isolate the first node of a botnet with 500 peers by removing only 8% of the bots. In the same botnet, 22% of the bots are isolated by only 75 removals, while the best other methods isolate 1% of the bots by 466 removals. Moreover, in two cases of P2P botnet with multiple command entry points, our method has isolated around 14 and 22 times more nodes compare to the best method among the others.

Integration of wireless sensor networks (WSNs) with Internet of Things (IoT) has given rise to applications such as Smart Home Networks, Vehicular Ad hoc Sensor Networks and Health and Wellness Wireless Sensor Networks among others. These applications tend to use multi-sensor nodes that have multiple sensors mounted on a single radio board and may require handling heterogeneous traffic. Modern WSNs are therefore no longer homogeneous in nature and have different quality of service (QoS) requirements. Modeling the performance of heterogeneous data is a challenging task owing to the complexity involved. In this paper we propose a MK/HyperK/1/M queuing model for multi-sensor nodes. Queues with Poisson arrivals and hyper-exponentially distributed service time and their applications have been widely discussed in literature however hardly any work can be found that uses them for modeling WSNs. In this paper we consider that the traffic from multi-sensor node is emanating from different sensor types within the node and is hence heterogeneous. The model captures the impact of varying arrival rates, mean packet lengths, buffer size and duty cycle on throughput. The model can be used with any duty cycle-based medium access control (MAC) protocols for WSNs. To test the model we apply it to IEEE 802.15.4 in beacon-enabled mode with star topology. Analytical results are corroborated by ns-2.35 simulations. Results indicate that the heterogeneity of traffic has a significant impact on the throughput and this may be useful in improving the QoS of applications.

The use of network applications to manage network operations by the controller in SDN architecture introduces a threat that makes the controller to be susceptible to several network attacks. This is possible because the network applications operate without any access control mechanism that authenticates or dictates what operations they can execute in the network. This consequently makes the network applications to take advantage of their ability to manipulate, change or modify network state to compromise network operations and resources. In order to address this problem this paper introduces a token-based authentication method that enables the controller to authenticate the various network applications. The application of this method builds an access permission zone where only legitimate network applications with the correct token credentials can have access to the network prior to implementing any network changes. This paper contributes in providing an authorisation method Boolean Access Matrix that enforces permission constraints on what the network applications can access or execute within the network. The authorisation method helps limits the unprecedented access the network applications have over the control layer resources, core services and the network operations. The paper introduces a novel method of evaluating the trust between the controller and the network application based on Subjective Logic Reasoning (SLR) which is a belief learning model. SLR is an advanced learning algorithm that is derived from Probability Calculus and Statistics. Experiments demonstrate the efficiency and scalability of the proposed algorithms in a large scale test environment.

Software defined networking (SDN), network function virtualization (NFV), and cloud computing are receiving significant attention in 5G networks. However, this attention creates a new challenge for security provisioning in these integrated technologies. Research in the field of SDN, NFV, cloud computing, and 5G has recently focused on the intrusion detection and prevention system (IDPS). Existing IDPS solutions are inadequate, which could cause large resource wastage and several security threats. To alleviate security issues, timely detection of an attacker is important. Thus, in this paper, we propose a novel approach that is referred to as multilayered intrusion detection and prevention (ML-IDP) in an SDN/NFV-enabled cloud of 5G networks. The proposed approach defends against security attacks using artificial intelligence (AI). In this paper, we employed five layers: data acquisition layer, switches layer, domain controllers (DC) layer, smart controller (SC) layer, and virtualization layer (NFV infrastructure). User authentication is held in the first layer using the Four-Q-Curve algorithm. To address the flow table overloading attack in the switches layer, the game theory approach, which is executed in the IDP agent, is proposed. The involvement of the IDP agent is to completely avoid a flow table overloading attack by a deep reinforcement learning algorithm, and thus, it updates the current state of all switches. In the DC layer, packets are processed and classified into two classes (normal and suspicious) by a Shannon Entropy function. Normal packets are forwarded to the cloud via the SC. Suspicious packets are sent to the VNF using a growing multiple self-organization map (GM-SOM). The proposed ML-IDP system is evaluated using NS3.26 for different security attacks, including IP Spoofing, flow table overloading, DDoS, Control Plane Saturation, and host location hijacking. From the experiment results, we proved that the ML-IDP with AI-based defense mechanisms effectively detects and prevents attacks.

Rapid rise in adoption of smart devices in distributed Internet-of-things (IoT) has resulted in an exponential increase in volume of generated data. However, due to resource-constrained sensor nodes and vulnerable communication channels, information protection has become a key concern and prominent factor for improvement in IoT environment. Batch processing systems have several shortcomings as compared to distributed systems. Distributed systems enable dynamic changes in the potential number of sensors, actuators, RFID’s, resources, users and subjects to tolerate unbounded interruptions in communication patterns. In this paper, we address the key challenges of communication security and scalability in IoT environment. We hypothesize distributed IoT approach between non-identical entities to communicate through secure authentication protocol for dynamically adding new user with partially involved trusted third party (TTP) as our module 1 and attribute based encryption scheme for non-identical smart entities to communicate securely as our module 2. We discuss module 1 in this paper. The existing approaches that focus on fully trusted central authority having full rights lead to serious weakness in violating security rules, while multi-authority based systems display revocation and compulsory user participation issues. As ideal functionalities we view TTP as honest-but-curious, honestly following the protocol while on the other hand curious to decrypt the cipher-text to breach the intention of encrypting parties. This motivates us to design an approach which jointly achieves effective authentication and partial trust management with scalability in distributed IoT environment. In accordance, we propose a novel authentication scheme with partially involved TTP nomenclatured Secure Dynamic User Addition Protocol (SDUAP) based on JWT (JSON Web Token) challenge and response game using symmetric key cryptography. The security of SDUAP is proved under real or random oracle model and its robustness against several attacks is verified using scyther security verification tool. We also compare performance of SDUAP with relatively similar modeled schemes in terms of communication, computation and storage overheads. The purpose of this paper is to mitigate the complications associated with scalability and curious/suspicious third party in distributed IoT approaches.

With the rapid development of the Internet of things and mobile Internet, more and more data flows into the Internet and will cause congestion of multiple routers in the network. However, most of the current congestion control methods are designed for a single router, which cannot adapt to the situation of multi-router congestion. Therefore, this paper proposes a congestion control algorithm to solve the network congestion problem of multiple routers. The model used in this paper captures the dynamics of Transmission Control Protocol (TCP) and covers the four possible behaviors of the TCP network when congestion occurs. The idea of TCP Active Queue Management (AQM) is to reduce congestion by actively discarding some packets in the queue. Taking the probability of packets marked as dropping as the control input, the congestion problem can be solved by using the backstepping method to make the queue length converge to the desired queue length. In this paper, the classical control strategy, backstepping, is extended to TCP network with multiple bottleneck routers to handle the AQM problem. Inspired by the existing network model with one bottleneck router, a revised model is introduced for TCP/AQM network with multiple bottleneck routers. And then, an AQM method Backstepping Congestion Control for Multi-router (BCCM) is proposed to deal with network congestion based on integral backstepping. Simulation results demonstrate that the convergence time of BCCM is about 10% of that of RED and The packet loss ratio of BCCM is 3 orders of magnitude lower than RED. In addition, BCCM has greater stability when traffic, link capacity, and router locations change.

Recently much research has been carried out towards the road condition monitoring system for improving the road safety and moving towards modern intelligent transportation system (ITS). 5G-based vehicle-to-everything (V2X) communication offers wider support and enhances the capabilities of road monitoring systems. The road monitoring systems utilizes the vehicles to report road conditions, traffic information or accidents to the roadside units (RSUs), which further relays such information to the cloud server for computing and processing. Then the cloud computing network redirects the necessary actions based on the these received reports. The major problem with this type of architecture is that it requires long computational time and causes high network latency. This also leads to poor utilization of bandwidth. As a result, in this paper a new network protocol has been proposed based on edge-based computing. In this paper, we present a new privacy preserving protocol to boost the security in vehicular network, by utilizing the concept of edge-based computing. The major concern in edge-based architecture is that all the data processing is performed at edge nodes which have various security holes. To secure the edge-based processing, we propose the idea of improved certificate-less aggregation sign-cryption scheme (iCLASC) with incorporating the information transmission protocol to formulate the road monitoring data. Confidentiality, integrity, joint authentication, privacy and anonymity are the key components of the security protocol. Lastly, we make the comparisons of the proposed work with the existing works in terms of computational cost, communication overhead and security feature analysis. Our scheme outperform all the previous methods and shows satisfactory security and communication performance requires for 5G-V2X Communication.

User cooperation is an effective technique to tackle the severe near-far user unfairness problem in wireless powered communication networks (WPCNs). In this paper, we consider a WPCN where two collaborating wireless devices (WDs) first harvest wireless energy from a hybrid access point (HAP) and then transmit their information to the HAP. The WD with the stronger WD-to-HAP channel helps relay the message of the other weaker user. In particular, we exploit the use of ambient backscatter communication during the wireless energy transfer phase, where the weaker user backscatters the received energy signal to transmit its information to the relay user in a passive manner. By doing so, the relay user can reuse the energy signal for simultaneous energy harvesting and information decoding (e.g., using an energy detector). Compared to active information transmission in conventional WPCNs, the proposed method effectively saves the energy and time consumed by the weaker user on information transmission during cooperation. With the proposed backscatter-assisted relaying scheme, we jointly optimize the time and power allocations on wireless energy and information transmissions to maximize the common throughput. Specifically, we derive the semi-closed-form expressions of the optimal solution and propose a low-complexity optimal algorithm to solve the joint optimization problem. By comparing with some representative benchmark methods, we simulate under extensive network setups and demonstrate that the proposed cooperation method effectively improves the throughput performance in WPCNs., This paper has been submitted for potential journal publication

The goal of the paper is to present the ideal form of an NDN forwarding engine on a commercial off-the-shelf (COTS) computer. In this paper, we design a reference forwarding engine by selecting well-established high-speed techniques and then analyze a state-of-the-art prototype implementation to identify its performance bottleneck. The microarchitectural analysis at the level of CPU pipelines and instructions reveals that dynamic random access memory (DRAM) access latency is one of bottlenecks for high-speed forwarding engines. Based on the analysis result, we design two prefetch-friendly packet processing techniques to hide DRAM access latency. The prototype employing the techniques achieves a forwarding rate exceeding 40 million packets per second on a COTS computer.

Traffic growth forecasts announce a dramatic future for core networks, struggling to keep the pace of traffic augmentation. Internet traffic growth primarily stems from the proliferation of cloud services and the massive amounts of data distributed by the content delivery networks (CDNs) hosting these services. In this paper, we investigate the evolution of core traffic in the presence of growing CDNs. Expanding the capacities of existing data centers (DCs) directly translates the forecasted compound-annual-growth-rate (CAGR) of user traffic to the CAGR of carried core link traffic. On the other hand, expanding CDNs by building new geographically dispersed DCs can significantly reduce the predicted core traffic growth rates by placing content closer to the users. However, reducing DC-to-user traffic by building new DCs comes at a trade-off with increasing inter-DC content synchronization traffic. Thus, the resulting overall core traffic growth will depend on the types of services supported and their associated synchronization requirements. In this paper, we present a long-term evolution study to assess the implications of different CDN expansion strategies on core network traffic growth considering a mix of services in proportions and growth rates corresponding to well-known traffic forecasts. Our simulations indicate that CDNs may have significant incentive to build more DCs, depending on the service types they offer, and that current alarming traffic predictions may be somewhat overestimated in core networks in the presence of expanding CDNs. (C) 2019 The Authors. Published by Elsevier B.V. The research leading to these results has received funding from the European Commission for the H2020-ICT-2016-2 METRO-HAUL project (G.A. 761727) and it has been partially funded by the Spanish national project ONOFRE-2(TEC2017-84423-C3-1-P, MINECO/AEI/FEDER, UE).

There are many common characteristics between Peer-to-Peer (P2P) overlay networks and Mobile Ad-hoc Networks (MANET). Self-organization, decentralization, dynamicity and changing topology are the most shared features. Furthermore, when used together, the two approaches complement each other. P2P overlays provide data storage/retrieval functionality, and their routing information can complement that of MANET. MANET provides wireless connectivity between clients without depending on any pre-existing infrastructure. The aim of this paper is to survey current P2P over MANET systems. Specifically, this paper focuses on and investigates structured P2P over MANET. Overall, more than thirty distinct approaches have been classified into groups and introduced in tables providing a structured overview of the area. The survey addresses the identified approaches in terms of P2P systems, MANET underlay systems and the performance of the reviewed systems.

Information Centric Networking (ICN) is a new network paradigm that emphasizes information and content, and considers the content name rather than the existing destination address as the routing criterion. Software-Defined Networking (SDN) can be a great help to the feasibility of ICN because it provides a network with flexibility and continuous management. In this paper, we present a method for significantly improving the efficiency of ICN content management using the SDN concept in a Wireless Mesh Network (WMN) environment. Each mesh node of a WMN can utilize its memory and storage as a cache, and the cache server, which has a sufficient amount of space, is used for high-capacity content. SDN enables a network to support various caching techniques, such as content identification, cache location decision, and cache distribution on the network layer. In particular, the SDN described in this paper significantly improves the cache distribution performance and content management efficiency through a cache location decision considering the features of wireless communication, a mesh topology, and constraints to the hardware capacity and cache space. The proposed system was evaluated through actual experiments. In the environment where the clients are locally converged, the proposed SDN-based content management schemes decrease the average response delay by 22.74% with only 4.59 kb control traffic load per second in comparison to other in-network cache schemes.

The existing electrical grid is now experiencing a revolutionary change to a new paradigm, i.e., smart grid, due to the development of information and communication technologies. Communications among smart grid components such as sensors, intelligent electronic devices (IED), and smart meters of automatic metering infrastructure (AMI) are some of the key components to successfully build smart grid. To reduce installation costs and spatial limits, wireless communications are considered as effective communication techniques in smart grid. However, severe wireless interference due to the electromagnetic wave generated by electronic devices, and strict requirements of smart grid applications such as delay-constraint, short delay, reliability, and scalability are making existing network protocols inappropriate for smart grid applications. In this paper, we propose AFAR to provide robust and delay-constrained communication services to smart grid applications while satisfying their requirements successfully. This paper includes a detailed description of the framework, mathematical modeling, OPNET simulation, and co-simulation between OpenDSS and OPNET to evaluate AFAR under the specific smart grid application scenario.

Wireless network performance is much restricted by the unreliability of the wireless channel and the competition among different flows for the shared network resources such as the bandwidth. Network coding is a technique that exploits the broadcast of the wireless channel and can effectively address these two restrictions to improve network performance. For example, with network coding, an intermediate node of multiple flows can encode packets from these flows into one mixed packet and serve these flows using only one transmission instead of multiple transmissions in the traditional way, thus mitigating the competition among flows. Inter-flow network coding (XNC), as a form of network coding, considers encoding packets from different flows, and it can benefit wireless mesh networks (WMNs) with either reliable or lossy links. In this paper, we present a survey on XNC in WMNs for unicast traffic, with various design factors related to XNC being covered. Specifically, our survey considers two types of WMNs, one with reliable links and the other with lossy links, and we study how XNC can be effectively utilized in both two types of WMNs. In addition to the benefits of XNC, we also present in this survey some drawbacks of applying XNC in WMNs. With this paper, we believe that readers will have a more thorough understanding of XNC on how it effectively mitigates the resource competition among flows and the channel unreliability problem in WMNs.

Smart grid has diverse stakeholders that often require varying levels of access to grid state and measurements. At the distribution level (i.e., MAN), smart grid provides two way communication between households and utilities. At the transmission level (i.e., WAN), multiple organizations need to share the transmission lines and cooperate with participants in their region. In this paper, we propose secure communication and computation services for smart grid to transform the current "closed cyber architecture" to an "open cyber architecture". In order to ensure the privacy and integrity of communicating parties at the distribution level, we propose to utilize the smart meters as a gateway between intra-network (i.e., HAN) and inter-network (i.e., WAN) communications, and manage incoming and outgoing traffic and mediate household devices based on the instructions from the electric utility or contracted service providers. To enhance data sharing between operators at the transmission level, we propose an open cyber architecture that utilizes blind processing service, in which sensitive data is transmitted through the secured channel and used in computations running in an isolated environment while the outcome is rendered only to a dedicated user or process. The "open" communication between the smart substructures and "blind" computation at operation centers will increase data sharing, minimize human intervention, and mitigate cascading events. In the paper, we provide and discuss underlying mechanisms to achieve an open cyber architecture.