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In this paper, a long-term workload management problem for multi-server edge computing with server collaboration is studied. In the considered model, mobile users computation-intensive tasks are generated dynamically over the time and offloaded to associated edge servers according to pre-determined subscription agreements. Upon receiving the subscribed workload, each edge server can then decide to whether participate in server collaboration for enabling workload re-allocation (i.e., workload exchange) with other heterogeneously configured edge servers. Unlike most of the existing work, this paper takes into account both competitions and collaborations among strategic edge servers in sharing their computing capacities. To achieve the equilibrium for each edge server in minimizing its expected cost (including energy consumption, delay, transmission, configuration and pricing costs), a joint optimization is formulated for determining i) its amount of workload to undertake, ii) compensation price charged from peers, and iii) computing speed to adopt. To efficiently solve this problem, we propose a novel cooperative queueing game approach, which integrates a convex optimization, a core cost sharing scheme and a mapping rule. Theoretical analyses and extensive simulations are conducted to evaluate the performance of the proposed solution, and demonstrate its superiority over counterparts.

This paper targets to transmit industrial data from one sensor node to another sensor node, wirelessly and securely. However as the nodes have Internet access and are typically positioned in an unsupervised context with minimal individual intervention; security and seclusion are the prime challenges in Industrial Wireless Sensor Networks (IWSN). To use IWSN, a user must be able to get real time information straight from the source nodes and this is accomplished by Radio Frequency Identification (RFID). It yields a cost-effective solution of identification problems, but it frequently suffers from diverse safety and privacy difficulties. This paper resolves the issues of RFID systems using Global System for Mobile Communications (GSM) module that generates a One-Time Password (OTP) for accessing the data, and thereby ensures user's privacy and security in Industrial Wireless Sensor Network. Furthermore, eight evaluation criteria have been met by the proposed system surpassing the existing systems.

Mobile Ad-hoc networks (MANET) is a collection of nodes of wireless connectivity. In Mobile Ad hoc Network (MANET) all the mobile nodes are requiring restricted battery capacity. Because of the changing nature of network the sudden communication link breakage happens. Hence the possibility of data loss is more. Efficient utilization of energy and lossless transmission are the important issues in MANET. This paper proposes a new Trust based Efficient Energy Balanced Less Loss Routing (TER) Protocol for MANETS. This protocol improves the network performance by properly choosing the intermediate forwarding nodes. The Source Node picks only single of its neighbors as its next hop node by using Efficient Parameter (EP). The EP is calculated from the residual energy, distance, Occupied Queue space, the velocity of that node. The node using maximum EP is nominated as the succeeding node. This protocol reduces the number of channeling messages and hence reduces the path-finding Overhead of the network. It lessens the chance of data loss and hence improves throughput and Packet Delivery Ratio. This protocol adds trust to the selected node. In this paper, we do the simulation in ns-2 simulator and the performance is measured by with performance parameters like Routing Overhead, Packet Delivery Ratio, Throughput, End to End Delay and Average energy consumption.

This paper proposes SilentDelivery, a secure, scalable and cost-efficient protocol for implementing timed information delivery service in a decentralized blockchain network. SilentDelivery employs a novel combination of threshold secret sharing and decentralized smart contracts. The protocol maintains shares of the decryption key of the private information of an information sender using a group of mailmen recruited in a blockchain network before the specified future time-frame and restores the information to the information recipient at the required time-frame. To tackle the key challenges that limit the security and scalability of the protocol, SilentDelivery incorporates two novel countermeasure strategies. The first strategy, namely silent recruitment, enables a mailman to get recruited by a sender silently without the knowledge of any third party. The second strategy, namely dual-mode execution, makes the protocol run in a lightweight mode by default, where the cost of running smart contracts is significantly reduced. We rigorously analyze the security of SilentDelivery and implement the protocol over the Ethereum official test network. The results demonstrate that SilentDelivery is more secure and scalable compared to the state of the art and reduces the cost of running smart contracts by 85%., This paper has been accepted by IEEE Transactions on Services Computing

Different applications of Wireless Sensor Networks (WSNs) have different expectations from the working of Medium Access Control (MAC) protocols. Some value reliability more than delay incurred while some demand a fair trade-off for the factors like: Throughput, Bit Error Rate (BER) etc. This paper evaluates the performance of Wireless Personal Area Networks (WPANs) from 802.15.4 group for WSNs with modified algorithm which helps in reducing the Medium Access Delay and Delay in reaching of the packet from one end to another end. In this paper certain modifications to existing algorithm have been proposed for reducing the Medium Access Delay and to reduce the number of packets dropped. The result comparisons on the performance parameters like: network output load, generated acknowledged traffic, media access delay, battery consumed and delay in packet transmission from one end to another end that the back-off number & exponent values used for transmission play vital role for improving the performance of WSNs as they directly affect the number of packets dropped, successfully acknowledged and Medium Access Delay.

The evolution of wireless body area network (WBAN) has changed the human life for its applications in the field of healthcare, fitness, entertainment and sports etc. However, two of the major challenges in the design of WBAN are energy efficiency and guaranteeing QoS. The load balance of different packet queues in a WBAN plays important role in design of energy efficient and reliable system. In this paper, we propose a Traffic Prioritized Load Balanced Scheduling (TPLBS) algorithm for load balancing in different priority queues in wireless body area networks based on IEEE 802.15.6 model. The main objective of this paper is to minimize packet drop in the queues so that throughput of WBAN can be improved. In this case we consider both priority and location from which the packet received, so that no packet should wait for a long time in the assigned queue to be transmitted to Access Point. The proposed method is simulated using Castalia to study and compare its performance with its counterparts. The simulation results reveal that the proposed protocol works better than the existing methods in terms of delay, throughput and energy efficiency.

To achieve higher throughputs in cellular networks, 3GPP proposes to use unlicensed frequency bands and develops technologies - the latest one is NR-U - allowing a cellular base station to transmit in unlicensed bands, which are already occupied by Wi-Fi networks. To enable fair channel sharing between two technologies, the base station uses a sort of CSMA/CA with binary exponential backoff similar to Wi-Fi. However, the base station can start data transmission only at strictly periodic time moments. Many papers propose sending a reservation signal between the end of the backoff procedure and such a moment to prevent nearby devices from accessing the channel. However, this approach significantly reduces Wi-Fi performance. The paper proposes a novel method CR-LBT of transmitting a reservation signal that greatly decreases channel resource waste caused by collisions and improves channel resource sharing fairness. With developed analytical models and simulations, it is shown that CR-LBT may simultaneously increase the throughput of both NR-U and Wi-Fi networks. The effect is more noticeable for the Wi-Fi network, the throughput of which may rise three times compared with the traditional method of sending the reservation signal. Finally, the influence of various factors on CR-LBT performance is studied.

High density base station (BS) will bring the problem of frequent handover to mobile Internet of things (IoT) devices. Frequent handover will lead to quality of service problems (QoS) such as increased handover delay and reduced data transmission rate. In order to overcome the limitation of mobile IoT devices’ QoS caused by frequent handover BSs, the Multiple-Input Multiple-Output (MIMO) systems can be used to improve the channel capacity and reduce the BS density. However, because the handover decision of mobile IoT devices will affect the data rate and network stability, how to implement the handover to reduce the impact of handover on mobile IoT devices is a problem worthy of study. Therefore, this paper proposes a handover strategy based on fuzzy logic in MIMO systems, which are used to reduce the handover frequency and improve the average data rate of mobile IoT devices. Firstly, the mobile IoT devices converts the devices’s speed, the distance from the devices to the MIMO systems and the transmission power of the MIMO systems to fuzzy values. Then, the fuzzy values obtained in the first step are taken as input, and the fuzzy logic based handover algorithm is implemented through the fuzzy logic controller. Finally, according to the results of the handover algorithm and the theoretical results about the average throughput of mobile IoT devices derived in this paper, the number of antennas used to provide transmission services for IoT devices with different data rate requirements and different mobile speeds can be allocated more flexibly. Simulation results show that the proposed scheme achieves a better performance.

Neighbor discovery (ND) is a key initial step of network configuration and prerequisite of vehicular ad hoc network (VANET). However, the convergence efficiency of ND is facing the requirements of multi-vehicle fast networking of VANET with frequent topology changes. This paper proposes gossip-based information dissemination and sensing information assisted ND with multi-packet reception (GSIM-ND) algorithm for VANET. GSIM-ND algorithm leverages efficient gossip-based information dissemination in the case of multi-packet reception (MPR). Besides, through multi-target detection function of multiple sensors installed in roadside unit (RSU), RSU can sense the distribution of vehicles and help vehicles to obtain the distribution of their neighbors. Thus, GSIM-ND algorithm leverages the dissemination of sensing information as well. The expected number of discovered neighbors within a given period is theoretically derived and used as the critical metric to evaluate the performance of GSIM-ND algorithm. The expected bounds of the number of time slots when a given number of neighbors needs to be discovered is derived as well. The simulation results verify the correctness of theoretical derivation. It is discovered that GSIM-ND algorithm proposed in this paper can always reach the short-term convergence quickly. Moreover, GSIM-ND algorithm is more efficient and stable compared with completely random algorithm (CRA), scan-based algorithm (SBA) and gossip-based algorithm. The convergence time of GSIM-ND algorithm is 40%-90% lower than that of these existing algorithms for both low density and high density networks. Thus, GSIM-ND can improve the efficiency of ND algorithm.

LoRa (Long-Range) has become the Deoxyribo Nucleic Acid (DNA) of the Internet of things (IoT) for equipping smart solutions. Home automation is responsible for providing a safe and stylish home. This paper proposes a capable architecture of home automation for both short-range and long-range utilizing multiple communication technologies, namely LoRaWAN, server-based LoRa gateway, and Bluetooth connectivity. This integrated system effectively controls distinct types of home appliances and keeps smart management among all the electronics components. A regular user can easily manage these unified systems by using an Android application. This paper also presents experimental data analysis. The results and discussion section provide a set of experiments like estimated transmission delay calculation for LoRa, Wi-Fi, and Bluetooth, a coverage area calculation for LoRa with RSSI and SNR values, and a System Usability Scale (SUS). The scheme has achieved a SUS score of 93%. However, the proposed architecture can be called an outright package for smart home and will be very workable, abuzz, and handy.

Ensuring Quality of Service (QoS) in next-generation networks would be challenging because of the expected manifolds increase in network traffic volume and the massive number of connected Internet of Things (IoT) devices. The increased resources on end-devices have made it possible to make decisions on the client-side for Access Point (AP) selection. On the other hand, due to power constraints on the client-side, energy efficiency is also essential. This paper presents a client-side energy-efficient AP selection approach for QoS provisioning in hybrid Wireless Fidelity (WiFi) and Light Fidelity (LiFi) networks. Compared to conventional WiFi and LiFi approaches, the proposed technique outperforms them in energy efficiency at any data rate and in QoS provisioning at data rates higher than 10 Mbps for a network of 50 nodes. It is also shown that adapting the uplink transmission power improves the IoT node’s energy efficiency by transmitting at minimal transmission power required to satisfy the throughput QoS constraint. This paper’s contributions include the proposed algorithm, complexity and convergence analyses of the algorithm, simulation-based evaluation, and analysis of the uplink transmission power adaption. The results show that the presented technique could be integrated into next-generation networks for QoS provisioning and improving energy efficiency.

Industrial control systems present numerous challenges from the communication systems perspective: clock synchronization, deterministic behavior, low latency, high reliability, flexibility, and scalability. These challenges are mostly solved with standard technologies over Ethernet, e.g., Time-Sensitive Networking (TSN). As a research trend, it is expected that TSN will converge with wireless, leading to the Wireless TSN paradigm. Also, Wireless TSN is expected to be integrated with Ethernet TSN to create large-scale wired-wireless (Hybrid) TSN networks. The first step towards Hybrid TSN is the distribution of the clock reference from the wired to the wireless domain. In this paper, we leverage existing Ethernet TSN and wireless technologies implementations (Wi-Fi and w-SHARP) and we present two hardware architectures specifically engineered to enable the clock synchronization distribution among the network domains. The hardware architectures have been implemented over a System-on-Chip (SoC) Field Programmable Gate Array (FPGA) platform. We demonstrate through several experiments that the implementation is able to fulfill the synchronization performance required by TSN., Comment: This paper has been accepted by IEEE Transaction on Industrial informatics 2021

Recently, the progression in Internet of Thing (IoT) has extensively influenced the model of wireless networking. As numerous wireless devices were emerged, the new Medium Access Control (MAC) and routing protocols has been introduced for assuring the end-to-end network efficiency. This paper aims to focus on the IEEE 802.15.4 MAC standards, where the security field is included in MAC header. The sensitive data security authentication on this MAC header is completely based on the method with the introduction of optimum authentication key using partially homomorphic encryption named ElGamal public key cryptosystem. More importantly, in this work, the ElGamal public key cryptosystem for securing IoT data is progressed by generating the optimal private key as well. For this optimal selection of key, this paper aims to establish a new hybrid optimization algorithm that hybrids the concept of Lion Algorithm (LA) and Cuckoo Search Algorithm (CS) named Cuckoo Mated-Lion Algorithm (CM-LA). Finally, the performance of the proposed working strategy is compared over other state-of-the-arts models by concerning various attacks, convergence and key sensitivity analysis, respectively.

Many real-time process-control and industrial control systems, such as Supervisory Control and Data Acquisition (SCADA), use a distributed software architecture and rely on trusted message exchanges among software components. This paper presents the Trust but Verify (TBV) middleware that promotes the idea that software components should not blindly trust each other. The TBV intercepts messages between a sender and a receiver to verify the consistency of the messages against rules associated with message types; this verification considers the system state. Based on the verification, a message is either delivered to the recipient or blocked. Even when components are mutually authenticated, it is possible that their counterparts are faulty or acting maliciously, persuading the receiver to take harmful actions. The contributions of this paper are: (1) The design of the TBV middleware. (2) A proof-of-concept implementation of the TBV on a cyberphysical system—a water treatment facility. (3) An experimental validation of the TBV through several attack scenarios that allow compromised or faulty components to randomly send erroneous messages. These experiments measure the TBV's detection rate as well as its overhead. (4) An evaluation of the TBV overhead and performance degradation.

This paper proposes a new transmission policy for intelligent reflecting surface (IRS) empowered wireless powered internet of things systems. Particularly, an energy station (ES) wirelessly charges for multiple IoT devices during downlink wireless energy transfer (WET) and then these devices deliver their own message to an access point (AP) during uplink wireless information transfer (WIT). Also, an IRS is deployed to improve energy harvesting and data transmission capabilities. To enhance self-sustainability of the IRS, the IRS harvests energy from the ES based on the harvest-then-transmit protocol. In this paper, we maximize the sum throughput via optimizing the phase shifts of the IRS, the transfer time scheduling as well as the power splitting ratio. Due to the non-convexity of the formulated problem, we divide the problem into two sub-problems, each of which can be handled separately. Then, we adopt an alternating optimization (AO) algorithm with the semidefinite programming (SDP) relaxation. Also, we consider a special case where the circuit power consumption of IoT devices can be neglected. In this case, we derive a closed form solution for the optimal transmission time slots, power allocation and phase shift by the Lagrange dual method. Finally, numerical evaluations validate effectiveness of the proposed scheme, which significantly benefits from the IRS in improving network throughput.

In this paper, we focus on the use of Low-Eart Orbit (LEO) satellites providing the Narrowband Internet of Things (NB-IoT) connectivity to the on-ground user equipment (UEs). Conventional resource allocation algorithms for the NBIoT systems are particularly designed for terrestrial infrastructures, where devices are under the coverage of a specific base station and the whole system varies very slowly in time. The existing methods in the literature cannot be applied over LEO satellite-based NB-IoT systems for several reasons. First, with the movement of the LEO satellite, the corresponding channel parameters for each user will quickly change over time. Delaying the scheduling of a certain user would result in a resource allocation based on outdated parameters. Second, the differential Doppler shift, which is a typical impairment in communications over LEO, directly depends on the relative distance among users. Scheduling at the same radio frame users that overcome a certain distance would violate the differential Doppler limit supported by the NB-IoT standard. Third, the propagation delay over a LEO satellite channel is around 4-16 times higher compared to a terrestrial system, imposing the need for message exchange minimization between the users and the base station. In this work, we propose a novel uplink resource allocation strategy that jointly incorporates the new design considerations previously mentioned together with the distinct channel conditions, satellite coverage times and data demands of various users on Earth. The novel methodology proposed in this paper can act as a framework for future works in the field., Tis work has been submitted to the IEEE IoT Journal for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

This paper deals with providing privacy-preserving access control in Internet of Things (IoT) systems. Here, a user/IoT device requests access to services provided by other IoT devices and multiple requests are combined to a request-specific service chain. An anonymous delegated credential based system architecture is proposed, where the requester’s identity is not exposed to the services. The paper presents the proposed architecture’s various components including the security aspects. Various options for implementing the architecture on resource-full and resource-constrained services are presented. A prototype of the proposed architecture is then implemented using Linux-based containers to emulate the services. Two representative systems, namely, a small-scale home automation system using a short service chain and a large-scale industrial automation system using a long service chain are considered. Timing measurements from the implementation are presented to demonstrate that the architecture is feasible and can be adapted for practical use in large-scale IoT systems.

This paper studies the privacy preserving average consensus (PPAC) of wireless sensor networks (WSNs). Note that most of the PPAC schemes only focus on the consensus of one-dimensional state, which is not suitable for the actual scenarios. In view of this, the multi-dimensional privacy-preserving average consensus (MPPAC) problem is considered in this paper, where the nodes are divided into two types, the sink nodes and the ordinary ones. A novel MPPAC algorithm is proposed by introducing the super-increasing sequence as well as the RSA algorithm, where the super-increasing sequence plays a key role in tackling the multi-dimensional measurement of the sensors, and the RSA algorithm realizes the privacy preserving average consensus among sink nodes. Simulation results illustrate the effectiveness of this proposed scheme.

In virtual power plants (VPPs), distributed devices (such as residential appliances, energy storage, and electric vehicles) communicate with control centers via wireless access points (APs). Nevertheless, with a massive number of devices connected to APs, VPPs would be adversely affected by packet loss and consequently suffer from revenue reduction. Therefore, devices’ access connections need to be delicately designated to mitigate these negative impacts. This paper studies the device access optimization problem from the perspective of VPP operations. An optimization model to minimize the revenue reduction induced by packet loss is first formulated to designate APs for devices in heterogeneous communication networks. The significance of various device data is determined by revenue reduction as a result of packet loss. Additionally, the heterogeneous access network model is established to characterize different types of APs. To make the model implementable, this paper further proposes a layered decomposition solution algorithm, which decomposes optimization tasks into small-scale sub-problems and successively assigns them to different layers of APs. Sub-problems are further decomposed for APs to greedily cut revenue reduction by evaluating devices’ marginal contributions to revenue reduction. Numerical case studies are also conducted to verify the benefits of device access optimization.

The controller area network (CAN) is the most widely used intra-vehicular communication network in the automotive industry. Because of its simplicity in design, it lacks most of the requirements needed for a security-proven communication protocol. However, a safe and secured environment is imperative for autonomous as well as connected vehicles. Therefore CAN security is considered one of the important topics in the automotive research community. In this paper, we propose a four-stage intrusion detection system that uses the chi-squared method and can detect any kind of strong and weak cyber attacks in a CAN. This work is the first-ever graph-based defense system proposed for the CAN. Our experimental results show that we have a very low 5.26% misclassification for denial of service (DoS) attack, 10% misclassification for fuzzy attack, 4.76% misclassification for replay attack, and no misclassification for spoofing attack. In addition, the proposed methodology exhibits up to 13.73% better accuracy compared to existing ID sequence-based methods., This paper is accepted to IEEE Transactions on Intelligent Transportation Systems for publication

Smart contracts in Ethereum blockchain network are self-executable scripts used for managing tokenized assets and access rights between different entities on the blockchain network. They are significant addition to blockchain technology for achieving data transparency and reliability in maintaining the digital relationship between two or more entities. However, the smart contract is in its nascent stage and suffers from various limitations, including immutability and code secrecy. In this paper, we address the inability of smart contracts to access the on-chain data. The smart contract currently fetches the on-chain data by taking external oracle assistance, which can be compromised to influence the customers. To address the issue, we propose a decentralized mechanism for accessing the blockchain data directly from the smart contracts by indexing single or multiple parameters of a transaction in each block using the Merkle-Patricia Trie (MPT). The idea is to increase the data transparency of blockchain applications. The paper provides a sequential search methodology that can retrieve transactions from N blocks, satisfying specific conditions, in O(N). The complexity is further reduced to O(N/k) by partitioning the blockchain data into k disjoint subsets to achieve parallelism in the search procedure. We experimentally verify the effectiveness of the proposed methodology with a case study on the Ethereum blockchain data.

In this paper, the resilient controller design and synthesis issues of networked control systems under denial-of-service (DoS) attacks are investigated via an adaptive event-triggered strategy. In a networked control system, DoS attacks have serious impacts on the security of communication, possibly causing degraded stability performance of the system. To remove threats from DoS attacks, an adaptive event-triggered communication mechanism is proposed, which also provides benefits in reducing the consumption of communication resources and relieving the pressure on network bandwidth. Since the system state information is usually not fully known, an observer-based controller is developed to stabilize the system and maintain a desired performance index despite the occurrence of stochastic attacks. Furthermore, a joint design method is proposed to obtain the controller gain, observer gain and event-triggered weight matrix. Finally, practical examples based on a four-tank system, an Internet-based three-tank system and an Internet-based test rig system are presented to illustrate the effectiveness of the proposed techniques to respond and eliminate the impact of DoS attacks.

IEC61850 is the mainstream of the development for substation automation. This paper presents a practical consideration and analysis for implementing a secure sampled measured value (SeSV) message in substation automation system. Due to the lack of security features in the standard, IEC Working Group 15 of Technical Committee 57 published IEC62351 on security for IEC61850 profiles. However, the use of authentication methods for SV based on IEC62351 standards are still not integrated, and computational capabilities and performance are not validated and tested with commercial grade equipment. Hence, this paper shows the performance of security feature enabled SeSV packets transmitted between protection and control devices by appending a message authentication code (MAC) to the extended IEC61850 packets. A prototype implementation on a low cost commodity embedded system has proved that the MAC-enabled SV message can fully secure the process bus communication in the digital substation with negligible time delay.

Background and Objective: The present issues faced by the transport systems include enormous traffic jams and congestion, unexpected road accidents, unwanted time delays, pedestrians' crossings on main roads, wastage of fuel, and many more. ITS and some other technologies work together to overcome such factors contributing to a much more desirable transport system. This paper aims to identify the security measures that could increase the security of the routing protocol and improve the performance of the DSR routing protocol. If the number of establishing links is frequently broken, then the performance of the DSR routing protocol is not very good. A new modified DSR algorithm has been designed that would help in reducing the network overhead and increase the network quality. A comparison between the performances of both algorithms has also been studied, and the results show that improved DSR routing protocol has better efficiency in parameters like end-to-end network load delays and packet delivery ratio. Methods & Materials: The paper mainly focuses on securing the Dynamic Source routing algorithm by designing its modified version and simulating it. We have Proposed Modified DSR and discussed so far that the basic functionality of the DSR algorithm, its advantages and disadvantages. The main drawbacks include the end-to-end Delay, network overhead and packet delivery ratio. Following is a modified version of the dynamic source routing algorithm, which tries to overcome all the limitations of the basic algorithm at a certain level. In the Dynamic Source Routing algorithm, the Route Maintenance phase is used for the successful propagation of the packet within the network. The nodes that are involved in the transmission acknowledge the receiving of the packet to the preceding node. Results and Discussion: The present study aims at modifying the existing algorithm and designing a new modified algorithm that has less routing overhead, less Delay in packet transmission and high network quality. Modified DSR routing algorithm is examined on the parameters like E-2-E delay, Normalize Routing Overhead, PDR. When we compare the performance of the proposed method with the Existing protocol AODV, and DSR at a number of nodes equal to 50 then we get the Proposed DSR, which has the least end-to-end Delay among all the three protocols. Conclusion: In this paper, acomparison of Exiting DSR and Modified DSR in terms of end-to-end Delay, routing load and packet delivery ratio is made. After studying the readings, the conclusion drawn was that there is less network overhead and a high delivery ratio in modified DSR as compared to the existing DSR algorithm. The corrupted and destroyed packets are detected by the receiver, and in DSR, the mobility of mobile nodes is moderate. Under certain conditions, bidirectional and unidirectional links can be accepted. DSR routing protocols are highly dependent on the parameters such as area size, packet size, packet type, and others.

Caching is an efficient way to reduce network traffic congestion during peak hours by storing some content at the users' local caches. For the shared-link network with end-user-caches, Maddah-Ali and Niesen proposed a two-phase coded caching strategy. In practice, users may communicate with the server through intermediate relays. This paper studies the tradeoff between the memory size $M$ and the network load $R$ for networks where a server with $N$ files is connected to $H$ relays (without caches), which in turn are connected to $K$ users equipped with caches of $M$ files. When each user is connected to a different subset of $r$ relays, i.e., $K = \binom{H}{r}$, the system is referred to as a {\it combination network with end-user-caches}. In this work, converse bounds are derived for the practically motivated case of {\it uncoded} cache contents, that is, bits of the various files are directly pushed into the user caches without any coding. In this case, once the cache contents and the user demands are known, the problem reduces to a general index coding problem.This paper shows that relying on a well-known "acyclic index coding converse bound" results in converse bounds that are not tight for combination networks with end-user-caches. A novel converse bound that leverages the network topology is proposed, which is the tightest converse bound known to date. As a result of independent interest, an inequality that generalizes the well-known sub-modularity of entropy is derived. Several novel caching schemes are proposed, based on the Maddah-Ali and Niesen cache placement. The proposed schemes are proved: (i) to be (order) optimal for some $(N,M,H,r)$ parameters regimes under the constraint of uncoded cache placement, and (ii) to outperform the state-of-the-art schemes in numerical evaluations., 22 pages, 3 figures; accepted by IEEE TIT

Abstract: WSN has been exhilarated in many application areas such as military, medical, environment, etc. Due to the rapid increase in applications, it causes proportionality to security threats. Mostly, nodes used, are independent of human reach and dependent on their limited resources, the major challenges can be framed as energy consumption and resource reliability. Introduction: Due to the limitation of resources in the sensor nodes, the traditionally intensive security mechanism is not feasible for WSNs. This limitation brought the concept of Digital watermarking in existence. The intent of this paper is to investigate the security related issues and role of watermarking in wireless sensor networks. Watermarking is an effective way to provide security, integrity, data aggregation and robustness in WSN. Mehtod: Digital watermarking is essential in WSN since it provides security in various forms such as confidentiality, service availability and data freshness. We have briefly discussed the various security requirements in the wireless sensor networks. Several issues and challenges, as well as the various threats of WMSN, is also considered. The related work, suggests that lots of research work are required to improve the security and authentication issues of WMSN by digital watermarking. This survey contribution will be helpful for researcher to accomplish effective watermarking scheme for WSN. Result: WSN is the collection of sensors that are spread in the environment. They measure and monitor physical conditions like temperature, sound, pressure, humidity, etc. and organize the collected data at the main location. The base station then forwards the data to end-users who analyze and make strategic decisions. Nowadays the modern network is bi-directional i.e. we can control the activity of the sensor. The central stations, unlike another sensor network, have infinite power, plenty of memory, powerful processors and a high bandwidth link. Whereas sensors are small in size, have fewer computation abilities, transfer wirelessly and are power-driven by small batteries Conclusion: Watermarking is an effective way to provide security, integrity, data aggregation and robustness in WSN. Digital watermarking is essential in WSN since it provides security in various forms such as confidentiality, data integrity, service availability and data freshness. In this paper, we have briefly discussed the various security requirements in the wireless sensor networks. We have also discussed work done by several authors in WSN with watermarking techniques Discussion: Wireless network faces more challenges as compared to wired network. In WSN, maximum amount of data and information can be stealed and effortlessly accessed during transmission. The nodes in a wireless sensor network (WSN) are resources constrained. Due to which WSNs have certain challenges i.e. processing power, storage and computational capacity and high bandwidth demand. Security schemes are not easy to design since the network tends to be large and ad-hoc. The analysis for privacy and security have been explored by some authors like J. Zhu et al. In recent years, a cryptography-based security designs have been proposed for WSNs. Cryptography is the process of concealing the information into the cipher text by encrypting it.

The Internet of Vehicles (IoV) environment consists of a number of latency-critical and data-intensive application (e.g., real-time video analytics). In this paper, we posit the potential of leveraging the sixth generation (6G) mobile networks to minimize communications delay, particularly for latency-critical task execution. In particular, 6G-enabled network in boxes (NIBs) deployed in the vehicles can communicate in real-time with the edge servers or the NIBs in other vehicles. Although, NIBs are capable of providing dynamic and flexible computing resources to support real-time IoV services, there are significant energy costs associated with the communication and computing activities. Seeking to achieve an optimal balance between energy consumption and time cost during service migration, we design a NIB task migration method (NTM) for IoV in this paper. In our approach, the IoV framework is designed and the routing mechanism is established. The Strength Pareto Evolutionary Algorithm (SPEA2) is then utilized to determine the migration strategy. Findings from our experiments demonstrate the reliability and efficiency of our proposed approach.

The integration of IoT and industry reveals the industrial manufacturing developments, resulting in industry internet of things (IIoT) which is to provide a general interconnect system for the access of various industry devices. However, as the amount and type of terminal increase, the creditability and privacy protection of terminal devices are hard to be guaranteed in IIoT, since the data and digital identity of access devices are nearly transparent for more devices in networks. It is a critical issue for the security of IIoT whether the access and service of device are trustworthy. In this paper, we present a novel private blockchain-enabled trusted anonymous access (BlockTrust) architecture for IIoT, where the distributed cloud radio and optical access networks (C-RON) is considered to provide a risk reduction of privacy leakage. Based on BlockTrust architecture, a blockchain-enabled tripartite anonymous identification trusted service provisioning (TriTrustServ) scheme is further proposed to guarantee a balanced tradeoff among the credibility, confidentiality and efficiency in IIoT, including digital identity generation, anonymous access identification, and trusted resource provisioning. Note that for the sake of a high credibility in IIoT networks, a tripartite authentication is presented in this paper with the first-time among device manufacturer, devices and network operator for the access process of device in IIoT networks. The feasibility and efficiency of BlockTrust architecture are experimentally verified in the realistic testbed, and the performances of TriTrustServ scheme are evaluated by comparing with two benchmark schemes in the terms of average mistrust rate, resource utilization and identification cost.

Broadcasting is one of the essential features in the Internet Protocol Ver 4 (IPv4). Attackers often exploit this feature of the IP protocol to launch several attacks against a network or an individual host. Attackers may either be a part of a Local Area Network (LAN) or outside a LAN to launch these attacks. There are numerous papers available in the literature to solve problems resulting from IP broadcasting. However, all these solutions target a specific problem that results from IP broadcasting. Furthermore, these solutions use either a computationally-intensive cryptographic scheme, the a priori relation between the host and the network or a modified protocol stack at every host. In this paper, we provide a seamless and transparent solution to eliminate IP broadcasting and thus eliminate all problems related to IP broadcasting. Our proposed solution is crypto-free and does not need any modification to the protocol stack.

IoT becomes more complicated due to its large size. The existing techniques of Wireless Sensor Networks (WSN) are not useful directly to the IoT; that is why using energyefficient schemes for the IoT is a challenging issue. Due to battery-constrained IoT devices, energy efficiency is of great importance. This paper gives an overview and broad survey on IoT, WSN in IoT, challenges in IoT and WSN, energy-conserving issues and solutions and different Node Deployment patterns. This paper addresses energy competence issues for green IoT by proposing an energy-efficient heuristic for a regular and particular deployment scheme. QCMCSC heuristic is implemented for Strip Based Deployment Pattern and analyzed in terms of Energy Efficiency and Life Time of a sensor on Energy Latency Density Design Space, a topology management application that is power efficient. QC-MCSC for Strip-based deployment patterns and random deployment patterns are compared.

In the last twenty years, optical networks have witnessed recurrent changes in their management and control architecture. In this paper, we present an historical timeline and a future perspective of the evolution of optical network management and control deployed for Wavelength Switched Optical Networks (WSON), Elastic Optical Networks (EON) and (multilayer) Data Center Networks. Early implementations of WSON envisaged a static and centralized provisioning approach supported by the Management Plane only. Gradually, the requirement of accommodating more network dynamicity in WSON, and later in EON, pushed the adoption of a distributed control, mostly supported by vendordependent implementations of the Generalized MultiProtocol Label Switching (GMPLS) protocol suite. The drawbacks of the fully distributed GMPLS-based control, such as resource contention, suboptimal resource usage, and complex computations (e.g., to account for physical layer constraints) showed the necessity to bring back some of the routing/provisioning functions to a centralized Path Computation Element (PCE) capable of accounting for e.g. physical impairments and interworking with GMPLS. The centralized control then gained its momentum and brought a radical change in network control, through the separation of data and control plane introduced by the paradigm of Software Defined Networking (SDN). Such an approach has been gradually extended to optical network control. The paper, eventually, presents the most advanced control techniques, namely the intent-based networking, the observe/decide/act state-based approach providing for autonomic optical network and the (closed-loop) zero-touch service management approach. Advanced traffic conditioning techniques are also detailed, namely the in-band telemetry and the exploitation of Programming Protocol-Independent Packet Processors (P4) language capabilities as well as solutions tailored for data center networks: all of them are still in a research stage and to be integrated within future optical network architectures.

Wireless sensor networks (WSN) are essential technologies of modern smart industry and their reliability is crucial for industrial information integration. This paper contributes by modeling the reliability of a linear multi-state consecutively connected system (LMCCS), which consists of a WSN providing the signal source, some intermediate nodes, and a sink node. The wireless sensors (WS) constituting the WSN are deployed around monitored objects to sense their conditions and transmit the sensed signal to a base station. The base station of the WSN serves as the source node of the LMCCS. The intermediate nodes of the LMCCS are sequentially arranged along a line to provide coverage and transmission of signal from the WSN base station to the sink node. Each node may assume multiple states, characterized by different signal coverage and transmission ranges of the connection element (CE) deployed in the node. As the state of each node is random, the signal coverage of the entire LMCCS is also random. Existing works on LMCCSs have mainly focused on studying the continuity of signal transmission (in particular, the probability that the sink node or signal receiver can successfully receive the signal from the source node or signal emitter). However, in some practical applications (e.g., risk source monitoring systems), the signal coverage area is a more important performance metric than the signal receiving probability. This paper proposes a universal generating function-based method to model and analyze the reliability and expected signal coverage of the LMCCS with WSN. The optimal CEs allocation problem is then solved with the objective of minimizing the cost of the entire system while meeting pre-specified requirements on the expected signal coverage and system reliability. The CEs allocation policy obtained should strike the balance among the system reliability, signal coverage and cost.

The dynamic distributed topology of a Mobile Ad Hoc Network (MANET) provides many challenges including decentralized infrastructure wherein each node acts as both the host and router for transiting traffic. MANET nodes provide the transmission capability to receive, transmit and route traffic from a sender node to the destination node.In this paper, we design an artificial immune system-based security method for MANET by simulating the mechanism of the human immune system. This paper presents a new bio inspired algorithm namely Artificial Immune System Based Algorithm (AISBA) to select selfish nodes in MANET, which utilizes principles of Artificial Immune Systems (AIS) that in turn mimics the strategy of the Human Immune System. Unlike Combined Immune Theories Algorithm, AISBA does not utilize a learning stage. In AISBA two different Trust models are developed as well to distinguish between a genuine node as well as a selfish node. An average detection rate of 93.41 % was achieved with this bio inspired approach. The Simulation results demonstrating the superiority of the proposed scheme compared to the well known secured AODV (SAODV) protocol in terms of packet delivery ratio (about 87 % of packet delivery ratio is achieved compared to about 37 % in the case of SAODV) and about 94 % of detection rate for the proposed scheme compared to 86 % for SAODV in the presence of misbehaved nodes. The statistical analysis of the false positive probability is also conducted to assess the efficiency of the obtained results, showing promising results with respect to the effect of weight and trust on threshold.

IEEE 802.11ax is the standard for the new generation WiFi networks. In this paper, we formulate the problem of joint access point (AP) placement and power-channel-resource unit assignment for 802.11ax-based dense WiFi. The objective is to minimize the number of APs. Two quality-of-service (QoS) requirements are to be fulfilled: (1) a two-tier throughput requirement which ensures that the throughput of each station is good enough, and (2) a fault tolerance requirement which ensures that the stations could still use WiFi even when some APs fail. We prove that this problem is NP-hard. To tackle this problem, we first develop an analytic model to derive the throughput of each station under the OFDMA mechanism and a widely used interference model. We then design a heuristic algorithm to find high-quality solutions with polynomial time complexity. Simulation results under both fixed-user and mobile-user cases show that: (1) when the area is small (50 x 50 m2), our algorithm gives the optimal solutions; when the area is larger (80 x 60 m2), our algorithm can reduce the number of APs by 34.9-87.7% as compared to the Random and Greedy algorithms. (2) Our algorithm can always get feasible solutions that fulfill the QoS requirements.

Programmable metasurfaces constitute an emerging paradigm, envisaged to become a key enabling technology for Reconfigurable Intelligent Surfaces (RIS) due to their powerful control over electromagnetic waves. The HyperSurface (HSF) paradigm takes one step further by embedding a network of customized integrated circuit (IC) controllers within the device with the aim of adding intelligence, connectivity, and autonomy. However, little is known about the traffic that the network needs to support as the target electromagnetic function or boundary conditions change. In this paper, the framework of a methodology is introduced to characterize the workload of programmable metasurfaces which is then used to analyze the beam steering HSFs. The workload characterization leads to many useful insights into traffic behavior, including the spatio-temporal load incurred and the HSF limitations in terms of fine-grained tracking of moving targets. It is observed that the traffic is inherently bursty with an uneven spatial distribution of load and that finer resolution comes at the cost of an increased but less bursty load. An indoor mobility model indicates reasonable signaling load on the deployed surfaces. Finally, a statistical analysis on the traffic patterns is performed, showing that the incoming traffic can be well represented by an ON-OFF model.

In VANETs, it is important to support fast and reliable multi-hop broadcast for safety-related applications. The performance of multi-hop broadcast schemes is greatly affected by relay selection strategies. However, the relationship between the relay selection strategies and the expected broadcast performance has not been fully characterized yet. Furthermore, conventional broadcast schemes usually attempt to minimize the waiting time difference between adjacent relay candidates to reduce the waiting time overhead, which makes the relay selection process vulnerable to internal interference, occurring due to retransmissions from previous forwarders and transmissions from redundant relays. In this paper, we jointly take both of the relay selection and the internal interference mitigation into account and propose a fast, reliable, opportunistic multi-hop broadcast scheme, in which we utilize a novel metric called the expected broadcast speed in relay selection and propose a delayed retransmission mechanism to mitigate the adverse effect of retransmissions from previous forwarders and an expected redundancy probability based mechanism to mitigate the adverse effect of redundant relays. The performance evaluation results show that the proposed scheme yields the best broadcast performance among the four schemes in terms of the broadcast coverage ratio and the end-to-end delivery latency.

In recent years, mobile edge computing (MEC), as a key technology that facilitates the 5G mobile network, has raised a number of new challenges for app vendors, including the Edge User Allocation (EUA) problem. EUA aims to allocate as many app users as possible in an MEC system to minimum edge servers in the system. In non-orthogonal multiple access (NOMA)-based MEC system, multiple app users can be allocated to the same subchannel on an edge server through transmit power allocation based on their intra-cell and inter-cell interference. However, allocating excessive app users to the same subchannel may result in severe interference and consequently impact app users data rates. In addition, in an MEC system, app users join and depart randomly, and thus need to be allocated in an online manner. Existing EUA approaches suffer from poor performance in dynamic real-world NOMA-based MEC systems because they allocate app users in an offline manner and do not consider the complication caused by NOMA. In this paper, we propose OL-EUA, an online approach for solving dynamic EUA problem in NOMA-based MEC systems. Its performance is theoretically analyzed and experimentally evaluated against a baseline approach and two state-of-the-art approaches on a widely-used real-world dataset.

With the continued proliferation of mobile Internet and geo-locating technologies, carpooling as a green transport mode is widely accepted and becoming tremendously popular worldwide. In this paper, we focus on a popular carpooling service called ride hitching, which is typically implemented using a publish/subscribe approach. In a ride hitching service, drivers subscribe ride orders published by riders and continuously receive matching ride orders until one is picked. The current systems (e.g., Didi Hitch) adopt a threshold-based approach to filter out ride orders. That is, a new ride order will be sent to all subscribing drivers whose planned trips can match the ride order within a pre-defined detour threshold. A limitation of this approach is that it is difficult for drivers to specify a reasonable detour threshold in practice. In addressing this problem, we propose a novel top-k subscription query called Top-k Ride Subscription (TkRS) query, which continuously returns the best k ride orders that match drivers' trip plans to them. We propose two efficient algorithms to enable the top-k results maintenance. We also design a novel hybrid index and a two-level buffer to efficiently track the top- $k$ results. Finally, extensive experiments on real-life datasets suggest that our algorithms can achieve desirable performance in practical settings.

Free space optics (FSO) has been demonstrated as a secure and high-speed solution for long distance and line-of-sight wireless communications. Applying FSO as fronthaul/backhaul communications between base stations (BSs) and the gateway can significantly increase the fronthaul/backhaul link capacity. Traditionally, the gateway has to be equipped with multiple FSO transceivers, each of which is used to communicate with a BS by establishing a dedicated FSO. In this paper, we propose to use a steerable FSO system, where the gateway is equipped with a steerable FSO transceiver to communicate with multiple FSO transceivers at different BSs in a time division multiplexing manner. Applying the steerable FSO system can reduce the number of FSO transceivers at the gateway, and thus reduce the capital cost of implementing an FSO based fronthaul/backhaul network. We formulate the transmission scheduling problem in the steerable FSO system to optimize the active time for each FSO link associated with the steerable FSO transceiver such that the overall delay of transmitting a packet from geo-distributed BSs to the steerable FSO transceiver at the gateway is minimized, while the latency requirements of the BSs are met. We propose the laTency aWare transmIssion Scheduling for sTeerable FSO (TWIST) algorithm to efficiently solve the proposed problem.

The exponential growth of the Internet of Everything (IoE), in recent times, has revealed many underlying security vulnerabilities of the nodes forming IoE networks. The extension of conventional security protocol to these devices has been greatly complicated by the prevalence of restricted computational hardware and limited battery life. Modern learning-based algorithms have shown the potential to secure the IoE networks without undue duress on the nodes’ limited capabilities. In this paper, a machine learning-based architecture has been proposed to identify malicious and benign nodes in an IoE network operating with big data. A novel approach for the cooperation of XGBoost and Deep Learning models along with a Genetic Particle Swarm Optimization (GPSO) algorithm to discover the optimal architectures of individual machine learning models has been proposed. Through simulations, it is shown that GPSO-based learning algorithms provide reliable, robust, and scalable solutions. The proposed model significantly outperforms other security protocols in the classification of malicious and benign nodes forming an IoE network.

Edge computing can provide high bandwidth and low-latency service for big data tasks by leveraging the edge side’s computing, storage, and network resources. With the development of microservice and docker technology, service providers can flexibly and dynamically cache microservice at the edge side to respond efficiently with limited resources. Automatically caching needed services on the nearest edge nodes and dynamically scheduling users’ requests can realize that computing power and software services flow with the users to provide continuous services. However, achieving the goal needs to overcome many challenges, such as the significant fluctuation of user devices’ requests at the edge side and the lack of collaboration among edge nodes. In this paper, dynamic computing power scheduling and collaborative task scheduling among edge nodes are comprehensively developed. The problem is considered a multi-objective optimization problem, including sequentially minimizing the deadline missing rate of requests and the average task completion time. We propose an adaptive mechanism for dynamically collaborative computing power and task scheduling (ADCS) in the edge environment to solve this problem. It adopts the greedy decision method to schedule computing tasks to meet their deadline requirements. At the same time, it uses the best-fit method to adjust the computing resources according to the changes of users’ requests. The simulation results show that ADCS can decrease the deadline missing rate and reduce the average completion time. Compared with DSR and CoDSR, the deadline missing rate is reduced by 59.91% and 19.95%, respectively. The average completion time is decreased by 37.87%, 6.71%.

As the Wi-Fi technology transitions into its sixth generation (Wi-Fi 6), there is a growing consensus on the need to support security and coordination functions at the Physical (PHY) layer. In contrast to the costly approach of extending the PHY-layer header to support new functions (e.g., Spatial Reuse field in the 802.11ax-based Wi-Fi frame), we propose to turn specific parts of the frame preamble into a reliable data field while maintaining its primary functions. Specifically, in this paper, we develop a scheme called extensible preamble modulation (eP-Mod) for 802.11n/ac/ax protocols that are built on multiple-input-multiple-output (MIMO) and orthogonal frequency-division multiplexing (OFDM). For each frame, eP-Mod can embed up to 144 user bits into the 802.11ac preamble of an 8×8 MIMO 40MHz transmission. The proposed scheme is adaptive to channel conditions and enables several promising PHY-layer services, such as PHY-layer encryption and channel/device authentication, and PHY-layer signaling. At the same time, it allows legacy (eP-Mod-unaware) devices to continue to process the received preamble as normal by guaranteeing that the proposed preamble waveforms satisfy the structural properties of a standardized preamble. Through numerical analysis, extensive simulations, and hardware experiments, we validate the practicality and reliability ofeP-Mod.

Applications deployed on edge servers improve users experience, when compared to deployments on cloud servers. Existing works usually assume that a central scheduler helps in making decisions, but they are often inefficient, inaccurate, or time-consuming. In this paper, we present a proactive application deployment system, which consists of three modules (i.e., incentive, profit, and latency). Based on the architecture of a fully distributed edge network, our system includes SELL, a Spontaneous Edge depLoyment aLgorithm in the incentive module. SELL lets edge servers compete with each other in a two-stage Stackelberg game to win deployment rights, and the winners get paid for their deployment efforts. The other two modules help recursively adjust service prices and deployment intentions in view of their own profits. Simulations on the proactive edge application deployment system demonstrate that SELL can help an application provider find appropriate edge servers to deploy applications while maximizing the profits for both parties in a low latency.

In recent years, edge computing has become an increasingly popular computing paradigm to enable real-time data processing and mobile intelligence. Edge computing allows computing at the edge of the network, where data is generated and distributed at the nearby edge servers to reduce the data access latency and improve data processing efficiency. One of the key challenges in data-intensive edge computing is how to place the data at the edge clouds effectively such that the access latency to the data is minimized. In this paper, we study such a data placement problem in edge computing while different data items have diverse popularity. We propose a popularity based placement method which maps both data items and edge servers to a virtual plane and places or retrieves data based on its virtual coordinate in the plane. We then further propose additional placement strategies to handle load balancing among edge servers via either offloading or data duplication. Simulation results show that our proposed strategies efficiently reduce the average path length of data access and the load-balancing strategies indeed provide an effective relief of storage pressures at certain overloaded servers.

IoT (IoTs) is a collection of autonomous things. IoTs is a new pattern that includes the existing presence of different devices. It is one of the latest technologies that provide global connectivity, management of sensors, users and information. The connectivity helps devices to be connected in a ubiquitous manner. Therefore, it can be deployed in different domains such as smart home, health, city, retail, logistics, industries and farming. This has brought a new dimension to connect with objects. There are many issues associated with IoTs such as fading, energy consumption, data security, network security, etc. The ultimate aim of this assessment is to show the different kinds of routing methods to solve the problem of network routing attacks in IoTs. This paper categorizes the attacks in terms of sinkhole, black hole and wormhole attacks in tabular format.

According to the latest news, the 3rd Generation cooperation Project has been taken the inventiveness of creating an interworking architecture involving cellular and WLAN as an additional feature to the cellular network requirements of 3GPP. This article provides an overview of an interworking infrastructure that allows mobile operators to provide the public WLAN dependent entrance service to various 3GPP network subscribers. The enabling features include 3GPP membership reuse, network availability, authentications relying on 3GPP systems, security keys agreement, USIM /SIM card authorization, user data service access and routing, as well as end-user paying. The function of interworking is accomplished without setting any particular 3GPP specifications for the new WLAN entrance networks, but instead by depend on existing features available in the traditional WLAN entrance networks centered on the IEEE 802.11 principles. In this paper, authors have focused on two key aspects of MTC devices, as currently discussed in 3GPP-Release 10. These are named as “the control of subscriptions” and the “congestion/overload control of the network”. A new solution is proposed for the latter one based on the handling of the bulk signals.

In future next Generation wireless networks, it is expected to have multi-mode wireless interface devices with common IP core communication. The user will be having multiple option of radio access technology (RAT) for data and voice service. This multi-mode provides the terminal seamless mobility across the heterogeneous wireless network. Mobile terminals transferring their communication sessions from one RAT to other, such transferring ongoing call process is known as vertical handover. With the rise in popularity of multimode mobile devices, switching between networks will be in high demand for users to move seamlessly through the network, either because users were moving away from an access point or because the network currently does not provide quality. service (QoS), but in both situations, a better network should be available, so a good network selection algorithm should take into account the possibility of multiple users performing a handover simultaneously in the same area. The objectives of this paper are to develop a handover mechanism that Provides good quality of service to the end user.

The advancement in the communication and services demand for better QoS, but in parallel the increase in network traffic demands for an effective and significant traffic controlling model to manage high network traffic and also reduce congestion. In case of MANET circumstances it is further difficult to control and manage due to high mobilizing nodes and limited resource restrictions. Even MANET’s dynamic mobility creates high maintenance overhead for effective communication. In the past most of the designed routing protocols utilize reactive routing mechanism, which are primary source driven. In case of a link failure and data failure it has to update the source node and source node only have to decide next course of action. This will generates an additional overhead in the network and may reduce throughput of the protocols. This paper aims to propose a novel Traffic Controlling Model (TCM) to efficiently manage the routing overhead in MANET. The TCM will handle heavy traffic, which is the main cause of network congestion and overhead. It first determines the network traffic and evaluates the probable Node Link Life (NLL) to recommend the TCM process. The analysis of the results generated through the experiment evaluation shows that the data routing has improved and substantiates the effectiveness of the proposal in compared to the existing routing approaches.

International audience; Internet of Things (IoT) applications often require the processing of data streams generated by devices dispersed over a large geographical area. Traditionally, these data streams are forwarded to a distant cloud for processing, thus resulting in high application end-to-end latency. Recent work explores the combination of resources located in clouds and at the edges of the Internet, called cloud-edge infrastructure, for deploying Data Stream Processing (DSP) applications. Most previous work, however, fails to scale to very large IoT settings. This paper introduces deployment strategies for the placement of DSP applications on to cloud-edge infrastructure. The strategies split an application graph into regions and consider regions with stringent time requirements for edge placement. The proposed Aggregate End-to-End Latency Strategy with Region Patterns and Latency Awareness (AELS+RP+LA) decreases the number of evaluated resources when computing an operator’s placement by considering the communication overhead across computing resources. Simulation results show that, unlike the state-of-the-art, AELS+RP+LA scales to environments with more than 100k resources with negligible impact on the application end-to-end latency.

In recent era, IoT-assisted robotics (IoRT) plays a major part in collaborating IoT sensor nodes, robots and human beings to establish a collaborative communication. In this paper, we develop an IoRT system with a modern architecture that encompasses the integration of IoT sensor nodes and robots in smart cities. The study develops a cloud platform to access smart vehicle mobility data in smart cities without collision. A framework is then developed to assist the robots and IoT sensor node in managing and making quick decisions on traffic collision. Hence, it is developed to connect, share, and exchange the information between the cloud and the IoT nodes/robots. The experimental validation shows improved traffic control and collision free traffic in smart cities than other smart city traffic management mechanism.