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In data driven deep learning, distributed sensing and joint computing bring heavy load for computing and communication. To face the challenge, over-the-air computation (OAC) has been proposed for multi-sensor data aggregation, which enables the server to receive a desired function of massive sensing data during communication. However, the strict synchronization and accurate channel estimation constraints in OAC are hard to be satisfied in practice, leading to time and channel-gain misalignment. The paper formulates the misalignment problem as a non-blind image deblurring problem. At the receiver side, we first use the Wiener filter to deblur, followed by a U-Net network designed for further denoising. Our method is capable to exploit the inherent correlations in the signal data via learning, thus outperforms traditional methods in term of accuracy. Our code is available at https://github.com/auto-Dog/MOAC_deep, Comment: Accepted by PICASSO@MobiCom' 24

Smart-city services are typically developed as closed systems within each city's vertical, communicating and interacting with cloud services while remaining isolated within each provider's domain. With the emergence of 5G private domains and the introduction of new M2M services focusing on autonomous systems, there is a shift from the cloud-based approach to a distributed edge computing paradigm, in a \textit{continuum} orchestration. However, an essential component is missing. Current orchestration tools, designed for cloud-based deployments, lack robust workload isolation, fail to meet timing constraints, and are not tailored to the resource-constrained nature of edge devices. Therefore, new orchestration methods are needed to support MEC environments. The work presented in this paper addresses this gap. Based on the real needs of a smart-city testbed - the Aveiro Living Lab-, we developed a set of orchestration components to facilitate the seamless orchestration of both cloud and edge-based services, encompassing both critical and non-critical services. This work extends the current Kubernetes orchestration platform to include a novel location-specific resource definition, a custom scheduler to accommodate real-time and legacy services, continuous service monitoring to detect sub-optimal states, and a refined load balancing mechanism that prioritizes the fastest response times.

In this article, we present the results of experiments with finding an efficient radio transmission method for an electric energy measurement system called OneMeter 2.0. This system offers a way of collecting energy usage data from beacons attached to regular, non-smart meters. In our study, we compared several low power wide area network (LPWAN) protocols, out of which we chose the LoRaWAN protocol. We verified the energy consumption of a LoRa-based transmission unit, as well as the transmission range between network nodes in urban conditions. We discovered that LoRaWAN-based transmission was highly energy-efficient and offered decent coverage, even in a difficult, dense urban environment., Comment: 7 pages, 8 figures

Recent advancements in Artificial Intelligence, and particularly Large Language Models (LLMs), offer promising prospects for aiding system administrators in managing the complexity of modern networks. However, despite this potential, a significant gap exists in the literature regarding the extent to which LLMs can understand computer networks. Without empirical evidence, system administrators might rely on these models without assurance of their efficacy in performing network-related tasks accurately. In this paper, we are the first to conduct an exhaustive study on LLMs' comprehension of computer networks. We formulate several research questions to determine whether LLMs can provide correct answers when supplied with a network topology and questions on it. To assess them, we developed a thorough framework for evaluating LLMs' capabilities in various network-related tasks. We evaluate our framework on multiple computer networks employing proprietary (e.g., GPT4) and open-source (e.g., Llama2) models. Our findings in general purpose LLMs using a zero-shot scenario demonstrate promising results, with the best model achieving an average accuracy of 79.3%. Proprietary LLMs achieve noteworthy results in small and medium networks, while challenges persist in comprehending complex network topologies, particularly for open-source models. Moreover, we provide insight into how prompt engineering can enhance the accuracy of some tasks.

The emerging technology of quantum computing has the potential to change the way how problems will be solved in the future. This work presents a centralized network control algorithm executable on already existing quantum computer which are based on the principle of quantum annealing like the D-Wave Advantage. We introduce a resource reoccupation algorithm for traffic engineering in wide-area networks. The proposed optimization algorithm changes traffic steering and resource allocation in case of overloaded transceivers. Settings of active components like fiber amplifiers and transceivers are not changed for the reason of stability. This algorithm is beneficial in situations when the network traffic is fluctuating in time scales of seconds or spontaneous bursts occur. Further, we developed a discrete-time flow simulator to study the algorithm's performance in wide-area networks. Our network simulator considers backlog and loss modeling of buffered transmission lines. Concurring flows are handled equally in case of a backlog. This work provides an ILP-based network configuring algorithm that is applicable on quantum annealing computers. We showcase, that traffic losses can be reduced significantly by a factor of 2 if a resource reoccupation algorithm is applied in a network with bursty traffic. As resources are used more efficiently by reoccupation in heavy load situations, overprovisioning of networks can be reduced. Thus, this new form of network operation leads toward a zero-margin network. We show that our newly introduced network simulator enables analyses of short-time effects like buffering within fat-pipe networks. As the calculation of network configurations in real-sized networks is typically time-consuming, quantum computing can enable the proposed network configuration algorithm for application in real-sized wide-area networks., Comment: 7 pages, 9 figures, accepted for publication at "IEEE International Conference on High Performance Switching and Routing 2024"

With the growing need for automation and the ongoing merge of OT and IT, industrial networks have to transport a high amount of heterogeneous data with mixed criticality such as control traffic, sensor data, and configuration messages. Current advances in IT technologies furthermore enable a new set of automation scenarios under the roof of Industry 4.0 and IIoT where industrial networks now have to meet new requirements in flexibility and reliability. The necessary real-time guarantees will place significant demands on the networks. In this paper, we identify IIoT use cases and infer real-time requirements along several axes before bridging the gap between real-time network technologies and the identified scenarios. We review real-time networking technologies and present peer-reviewed works from the past 5 years for industrial environments. We investigate how these can be applied to controllers, systems, and embedded devices. Finally, we discuss open challenges for real-time communication technologies to enable the identified scenarios. The review shows academic interest in the field of real-time communication technologies but also highlights a lack of a fixed set of standards important for trust in safety and reliability, especially where wireless technologies are concerned., Comment: IEEE Internet of Things Journal 2023 | Journal article DOI: 10.1109/JIOT.2023.3332507

In this study, the Active Control in an Intelligent and Distributed Environment (ACIDE) media distribution model solution and algorithms are proposed for livestreaming in capacity efficient mobile wireless networks. The elements of the ACIDE model are a base station and a cluster formed by a number of peers able to establish peer to peer communications. The cluster peers are selected from a group of users interested in livestreaming the same media. The ACIDE model solution minimizes the bandwidth allocated to a cluster of n peers such that an uninterrupted media play for all peers is guaranteed. The livestream media is sent to the peers in packages and every media package is divided into n blocks. The blocks are distributed to the n peers of a cluster in two phases, such that the base station bandwidth is utilized during first phase only. The allocated bandwidth, the amount of bandwidth the base station has to allocate to a cluster, is minimized and its lower bound is equal to the bandwidth required for multicasting. In this study, the ACIDE model is used to address the problem of how to find the maximum number of peers n, chosen from a group of N users, that can be admitted to a cluster knowing the given allocated bandwidth, the amount of bandwidth that a base station allocates to a cluster in advance, prior to admitting users. When users become peers of an ACIDE cluster, the network capacity, the total number of users who are able to access live media, increases meaning that network resources are used more efficiently. The problem of finding the maximum number of peers n is addressed as an optimization problem, with the objective of having the entire given allocated bandwidth used by the peers admitted to the cluster. This problem is NP-complete and a non-optimal solution is proposed for peers selection such that all admitted peers play media continuously., Comment: 8 pages, 6 figures, 3 tables; Accepted for publication in: Proceedings of the 2023 International Conference on Computational Science and Computational Intelligence (CSCI'23: December 13-15, 2023, Las Vegas, Nevada, USA); Publisher: IEEE Computer Society (CPS)

In this paper, a media distribution model, Active Control in an Intelligent and Distributed Environment (ACIDE), is proposed for bandwidth efficient livestreaming in mobile wireless networks. Two optimization problems are addressed. The first problem is how to minimize the bandwidth allocated to a cluster of n peers such that a continuous media play for all peers is guaranteed. The second problem is how to find the maximum number of peers n, chosen from a group of N users, that can be admitted to a cluster knowing the given allocated bandwidth, the amount of bandwidth that a base station allocates to a cluster prior to admitting users. Media is sent in packages and each package is divided into n blocks. The distribution of blocks to the peers follows a two-phase, multi-step approach. For the first problem a solution is proposed to find the optimal block sizes such that the allocated bandwidth is minimized, and its lower bound is the bandwidth required for multicasting. The second problem is NP-complete and a greedy strategy is proposed to calculate a near optimal solution for peer selection such that the network capacity, the total number of users who are able to access livestream media, increases., Comment: 13 pages, 12 figures, 3 tables, This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

The advancements in 5G mobile networks and Edge computing offer great potential for services like augmented reality and Cloud gaming, thanks to their low latency and high bandwidth capabilities. However, the practical limitations of achieving optimal latency on real applications remain uncertain. This paper aims to investigate the actual latency and bandwidth provided by 5G Networks and YouTube Edge service in London, UK. We analyze how latency and bandwidth differ between 4G LTE and 5G networks and how the location of YouTube Edge servers impacts these metrics. Our research reveals over 10 significant observations and implications, indicating that the primary constraints on 4G LTE and 5G capabilities are the ecosystem and energy efficiency of mobile devices down-streaming data. Our study demonstrates that to fully unlock the potential of 5G and it's applications, it is crucial to prioritize efforts aimed at improving the ecosystem and enhancing the energy efficiency.

Deterministic real-time communication with bounded delay is an essential requirement for many safety-critical cyber-physical systems, and has received much attention from major standardization bodies such as IEEE and IETF. In particular, Ethernet technology has been extended by time-triggered scheduling mechanisms in standards like TTEthernet and Time-Sensitive Networking. Although the scheduling mechanisms have become part of standards, the traffic planning algorithms to create time-triggered schedules are still an open and challenging research question due to the problem's high complexity. In particular, so-called plug-and-produce scenarios require the ability to extend schedules on the fly within seconds. The need for scalable scheduling and routing algorithms is further supported by large-scale distributed real-time systems like smart energy grids with tight communication requirements. In this paper, we tackle this challenge by proposing two novel algorithms called Hierarchical Heuristic Scheduling (H2S) and Cost-Efficient Lazy Forwarding Scheduling (CELF) to calculate time-triggered schedules for TTEthernet. H2S and CELF are highly efficient and scalable, calculating schedules for more than 45,000 streams on random networks with 1,000 bridges as well as a realistic energy grid network within sub-seconds to seconds.

Unencrypted DNS traffic between users and DNS resolvers can lead to privacy and security concerns. In response to these privacy risks, many browser vendors have deployed DNS-over-HTTPS (DoH) to encrypt queries between users and DNS resolvers. Today, many client-side deployments of DoH, particularly in browsers, select between only a few resolvers, despite the fact that many more encrypted DNS resolvers are deployed in practice. Unfortunately, if users only have a few choices of encrypted resolver, and only a few perform well from any particular vantage point, then the privacy problems that DoH was deployed to help address merely shift to a different set of third parties. It is thus important to assess the performance characteristics of more encrypted DNS resolvers, to determine how many options for encrypted DNS resolvers users tend to have in practice. In this paper, we explore the performance of a large group of encrypted DNS resolvers supporting DoH by measuring DNS query response times from global vantage points in North America, Europe, and Asia. Our results show that many non-mainstream resolvers have higher response times than mainstream resolvers, particularly for non-mainstream resolvers that are queried from more distant vantage points -- suggesting that most encrypted DNS resolvers are not replicated or anycast. In some cases, however, certain non-mainstream resolvers perform at least as well as mainstream resolvers, suggesting that users may be able to use a broader set of encrypted DNS resolvers than those that are available in current browser configurations.

The first low earth orbit satellite networks for internet service have recently been deployed and are growing in size, yet will face deployment challenges in many practical circumstances of interest. This paper explores how a dual-band, electronically tunable smart surface can enable dynamic beam alignment between the satellite and mobile users, make service possible in urban canyons, and improve service in rural areas. Our design is the first of its kind to target dual channels in the Ku radio frequency band with a novel dual Huygens resonator design that leverages radio reciprocity to allow our surface to simultaneously steer and modulate energy in the satellite uplink and downlink directions, and in both reflective and transmissive modes of operation. Our surface, Wall-E, is designed and evaluated in an electromagnetic simulator and demonstrates 94% transmission efficiency and an 85% reflection efficiency, with at most 6 dB power loss at steering angles over a 150-degree field of view for both transmission and reflection. With a 75 sq cm surface, our link budget calculations predict a 4 dB and 24 dB improvement in the SNR of a link entering the window of a rural home in comparison to the free-space path and brick wall penetration, respectively., Comment: 9 pages including references, 9 figures

Offering support for real-time communications on top of a wireless network infrastructure is both a hot topic and still an open challenge. Wireless networks are not on the same level of safety, dependability, and timeliness observed in the wired realm, but they are evolving towards it. Instead of focusing on the results that need to be delivered, the key factors of wireless real-time networks are on the foundation of the network operation, defining their capability of being dependable, safe, and timely on their roots. IEEE 802.15.4 and ISA100.11a are part of this context, which we show how to be strengthened. From dealing with network inaccessibility to touching the needs of reliable communication protocols to ensure the safe and sound exchange of information, this white paper describes how we can go from dependability to timeliness. This is achieved by visiting the roots of the network operation for securing the provided communication service as a dependable, safe, and timely asset for industrial automation. Keywords: Dependability, Safety, Timeliness, Resilience, Real-Time Wireless Networks, Industrial Automation.

WLANs, which have overtaken wired networks to become the primary means of connecting devices to the Internet, are prone to performance issues due to the scarcity of space in the radio spectrum. As a response, IEEE 802.11ax and subsequent amendments aim at increasing the spatial reuse of a radio channel by allowing the dynamic update of two key parameters in wireless transmission: the transmission power (TX_POWER) and the sensitivity threshold (OBSS_PD). In this paper, we present INSPIRE, a distributed solution performing local Bayesian optimizations based on Gaussian processes to improve the spatial reuse in WLANs. INSPIRE makes no explicit assumptions about the topology of WLANs and favors altruistic behaviors of the access points, leading them to find adequate configurations of their TX_POWER and OBSS_PD parameters for the "greater good" of the WLANs. We demonstrate the superiority of INSPIRE over other state-of-the-art strategies using the ns-3 simulator and two examples inspired by real-life deployments of dense WLANs. Our results show that, in only a few seconds, INSPIRE is able to drastically increase the quality of service of operational WLANs by improving their fairness and throughput.

Nowadays, Vehicle-To-Everything (V2X) networks are actively developing. Most of the already deployed V2X networks are based on the IEEE 802.11p standard. However, these networks can provide only basic V2X applications and will unlikely fulfill stringent requirements of modern V2X applications. Thus, the IEEE has launched a new IEEE 802.11bd standard. A significant novelty of this standard is channel bonding. IEEE 802.11bd describes two channel bonding techniques, which differ from the legacy one used in modern Wi-Fi networks. Our study performs a comparative analysis of the various channel bonding techniques and a single-channel access method from IEEE 802.11p via simulation. We compare them under different contention window sizes and demonstrate that the legacy technique provides the best quality of service in terms of frame transmission delays and packet loss ratio. Moreover, we have found a quasi-optimal contention window size for the legacy technique., Comment: 5 pages, 5 figures

Many networked applications, e.g., in the domain of cyber-physical systems, require strict service guarantees, usually in the form of jitter and latency bounds, for time-triggered traffic flows. It is a notoriously hard problem to compute a network-wide traffic plan that satisfies these requirements, and dynamic changes in the flow set add even more challenges. Existing traffic-planning methods are ill-suited for dynamic scenarios because they either suffer from high computational cost, can result in low network utilization, or provide no explicit guarantees when transitioning to a new traffic plan that incorporates new flows. Therefore, we present a novel approach for dynamic traffic planning of time-triggered flows. Our conflict-graph based modeling of the traffic planning problem allows to reconfigure active flows to increase the network utilization, while also providing per-flow QoS guarantees during the transition to the new traffic plan. Additionally, we introduce a novel heuristic for computing the new traffic plans. Evaluations of our prototypical implementation show that we can efficiently compute new traffic plans in scenarios with hundreds of active flows for a wide range of scenarios.

Connected and autonomous vehicles (CAVs) are an innovative form of traditional vehicles. Automotive Ethernet replaces the controller area network and FlexRay to support the large throughput required by high-definition applications. As CAVs have numerous functions, they exhibit a large attack surface and an increased vulnerability to attacks. However, no previous studies have focused on intrusion detection in automotive Ethernet-based networks. In this paper, we present an intrusion detection method for detecting audio-video transport protocol (AVTP) stream injection attacks in automotive Ethernet-based networks. To the best of our knowledge, this is the first such method developed for automotive Ethernet. The proposed intrusion detection model is based on feature generation and a convolutional neural network (CNN). To evaluate our intrusion detection system, we built a physical BroadR-Reach-based testbed and captured real AVTP packets. The experimental results show that the model exhibits outstanding performance: the F1-score and recall are greater than 0.9704 and 0.9949, respectively. In terms of the inference time per input and the generation intervals of AVTP traffic, our CNN model can readily be employed for real-time detection., Comment: 35 pages, 9 figures, accepted to Vehicular Communications (Elsevier)

In September 2020, the Broadband Forum published a new industry standard for measuring network quality. The standard centers on the notion of quality attenuation. Quality attenuation is a measure of the distribution of latency and packet loss between two points connected by a network path. A vital feature of the quality attenuation idea is that we can express detailed application requirements and network performance measurements in the same mathematical framework. Performance requirements and measurements are both modeled as latency distributions. To the best of our knowledge, existing models of the 802.11 WiFi protocol do not permit the calculation of complete latency distributions without assuming steady-state operation. We present a novel model of the WiFi protocol. Instead of computing throughput numbers from a steady-state analysis of a Markov chain, we explicitly model latency and packet loss. Explicitly modeling latency and loss allows for both transient and steady-state analysis of latency distributions, and we can derive throughput numbers from the latency results. Our model is, therefore, more general than the standard Markov chain methods. We reproduce several known results with this method. Using transient analysis, we derive bounds on WiFi throughput under the requirement that latency and packet loss must be bounded., Comment: 12 pages, 19 figures, Submitted for review to SIGCOMM 2021

The LP WAN networks use gateways or base stations to communicate with devices distributed on large distances, up to tens of kilometres. The selection of optimal gateway locations in wireless networks should allow providing the complete coverage for a given set of nodes, taking into account the limitations, such as the number of nodes served per access point or required redundancy. In this paper, we describe the problem of selecting the base stations in a network using the concept of $k$-dominating set. In our model, we include information about the required redundancy and spectral efficiency. We consider the additional requirements on the resulting connections and provide the greedy algorithm for solving the problem. The algorithm is evaluated in randomly generated network topologies and using the coordinates of sample real smart metering networks., Comment: 14 pages, 7 figures

Coexistence between cellular systems and Wi-Fi gained the attention of the research community when LTE License Assisted Access (LAA) entered the unlicensed band. The recent introduction of NR-U as part of 5G introduces new coexistence opportunities because it implements scalable numerology (flexible subcarrier spacing and OFDM symbol lengths), and non-slot based scheduling (mini-slots), which considerably impact channel access. This paper analyzes the impact of NR-U settings on its coexistence with Wi-Fi networks and compares it with LAA operation using simulations and experiments. First, we propose a downlink channel access simulation model, which addresses the problem of the dependency and non-uniformity of transmission attempts of different nodes, as a result of the synchronization mechanism introduced by NR-U. Second, we validate the accuracy of the proposed model using FPGA-based LAA, NR-U, and Wi-Fi prototypes with over-the-air transmissions. Additionally, we show that replacing LAA with NR-U would not only allow to overcome the problem of bandwidth wastage caused by reservation signals but also, in some cases, to preserve fairness in channel access for both scheduled and random-access systems. Finally, we conclude that fair coexistence of the aforementioned systems in unlicensed bands is not guaranteed in general, and novel mechanisms are necessary for improving the sharing of resources between scheduled and contention-based technologies., Comment: 20 double-column single-spaced pages, 10 figures, 3 tables, 39 references, journal submission

The proper setting of contention window (CW) values has a significant impact on the efficiency of Wi-Fi networks. Unfortunately, the standard method used by 802.11 networks is not scalable enough to maintain stable throughput for an increasing number of stations, yet it remains the default method of channel access for 802.11ax single-user transmissions. Therefore, we propose a new method of CW control, which leverages deep reinforcement learning (DRL) principles to learn the correct settings under different network conditions. Our method, called centralized contention window optimization with DRL (CCOD), supports two trainable control algorithms: deep Q-network (DQN) and deep deterministic policy gradient (DDPG). We demonstrate through simulations that it offers efficiency close to optimal (even in dynamic topologies) while keeping computational cost low., Comment: 6 pages, 6 figures, published in 2021 IEEE Wireless Communications and Networking Conference (WCNC)

Network operators are looking towards LTE License Assisted Access (LAA) as a means of extending capacity by offloading traffic to unlicensed bands. However, operation in these bands requires abiding to certain coexistence rules in terms of channel access. The description of these rules in existing literature is not always in line with the latest standards. Therefore, in this paper, we clarify the operation of LAA, focusing on channel access and methods of providing Quality of Service (QoS) support. In terms of coexistence, we evaluate the impact of LAA under its various QoS settings on Wi-Fi performance in an experimental testbed. Finally, we describe the upcoming research challenges for LTE-based technologies in unlicensed bands considering the latest developments., Comment: 7 pages, 4 figures, 2 tables

The smooth operation of largely deployed Internet of Things (IoT) applications will depend on, among other things, effective infrastructure failure detection. Access failures in wireless network Base Stations (BSs) produce a phenomenon called "sleeping cells", which can render a cell catatonic without triggering any alarms or provoking immediate effects on cell performance, making them difficult to discover. To detect this kind of failure, we propose a Machine Learning (ML) framework based on the use of Key Performance Indicator (KPI) statistics from the BS under study, as well as those of the neighboring BSs with propensity to have their performance affected by the failure. A simple way to define neighbors is to use adjacency in Voronoi diagrams. In this paper, we propose a much more realistic approach based on the nature of radio-propagation and the way devices choose the BS to which they send access requests. We gather data from large-scale simulators that use real location data for BSs and IoT devices and pose the detection problem as a supervised binary classification problem. We measure the effects on the detection performance by the size of time aggregations of the data, the level of traffic and the parameters of the neighborhood definition. The Extra Trees and Naive Bayes classifiers achieve Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) scores of 0.996 and 0.993, respectively, with False Positive Rate (FPR) under 5 %. The proposed framework holds potential for other pattern recognition tasks in smart-city wireless infrastructures, that would enable the monitoring, prediction and improvement of the Quality of Service (QoS) experienced by IoT applications., Comment: Submitted to the IEEE Access Journal

Understanding and predicting mobility are essential for the design and evaluation of future mobile edge caching and networking. Consequently, research on prediction of human mobility has drawn significant attention in the last decade. Employing information-theoretic concepts and machine learning methods, earlier research has shown evidence that human behavior can be highly predictable. Despite existing studies, more investigations are needed to capture intrinsic mobility characteristics constraining predictability, and to explore more dimensions (e.g. device types) and spatio-temporal granularities, especially with the change in human behavior and technology. We analyze extensive longitudinal datasets with fine spatial granularity (AP level) covering 16 months. The study reveals device type as an important factor affecting predictability. Ultra-portable devices such as smartphones have "on-the-go" mode of usage (and hence dubbed "Flutes"), whereas laptops are "sit-to-use" (dubbed "Cellos"). The goal of this study is to investigate practical prediction mechanisms to quantify predictability as an aspect of human mobility modeling, across time, space and device types. We apply our systematic analysis to wireless traces from a large university campus. We compare several algorithms using varying degrees of temporal and spatial granularity for the two modes of devices; Flutes vs. Cellos. Through our analysis, we quantify how the mobility of Flutes is less predictable than the mobility of Cellos. In addition, this pattern is consistent across various spatio-temporal granularities, and for different methods (Markov chains, neural networks/deep learning, entropy-based estimators). This work substantiates the importance of predictability as an essential aspect of human mobility, with direct application in predictive caching, user behavior modeling and mobility simulations.

Multi-hop wireless networks with autonomous nodes are susceptible to selfish traffic remapping attacks (TRAs). Nodes launching TRAs leverage the underlying channel access function to receive unduly high quality of service (QoS) for packet flows traversing source-to-destination routes. TRAs are easy to execute, impossible to prevent, difficult to detect, and harmful to the QoS of honest nodes. Recognizing the need for providing QoS security, we use a novel network-oriented QoS metric to propose a self-enforcing game-theoretic mitigation approach. By switching between TRA and honest behavior, selfish nodes engage in a noncooperative multistage game in pursuit of high QoS. We analyze feasible node strategies and design a distributed signaling mechanism called DISTRESS, under which, given certain conditions, the game produces a desirable outcome: after an upper-bounded play time, honesty tends to become a selfish node's best-reply behavior, while yielding acceptable QoS to most or all nodes. We verify these findings by Monte Carlo and ns-3 simulations of static and mobile nodes., Comment: 16 pages, 11 figures, 3 tables, journal version of conference paper arXiv:1704.04053

The problem of Wi-Fi and LTE coexistence has been significantly debated in the last years, with the emergence of LTE extensions enabling the utilization of unlicensed spectrum for carrier aggregation. Rather than focusing on the problem of resource sharing between the two technologies, in this paper, we study the effects of LTE's structured transmissions on the Wi-Fi random access protocol. We show how the scheduling of periodic LTE transmissions modifies the behavior of 802.11's distributed coordination function (DCF), leading to a degradation of Wi-Fi performance, both in terms of channel utilization efficiency and in terms of channel access fairness. We also discuss the applicability and limitations of a persistent DCF model in analyzing Wi-Fi performance under periodic LTE interference., Comment: 4 pages, 2 figures, 2 tables, 13 references, accepted for publication in IEEE Communications Letters

In this paper, Decentralized Periodic Approach for Adaptive Fault Diagnosis (DP-AFD) algorithm is proposed for fault diagnosis in distributed systems with arbitrary topology. Faulty nodes may be either unresponsive, may have either software or hardware faults. The proposed algorithm detects the faulty nodes situated in geographically distributed locations. This algorithm does not depend on a single node or leader to detect the faults in the system. However, it empowers more than one node to detect the fault-free and faulty nodes in the system. Thus, at the end of each test cycle, every fault-free node acts as a leader to diagnose faults in the system. This feature of the algorithm makes it applicable to any arbitrary network. After every test cycle of the algorithm, all the nodes have knowledge about faulty nodes and each node is tested only once. With this knowledge, there can be redistribution of load, which was earlier assigned to the faulty nodes. Also, the algorithm permits repaired node re-entry and new node entry. In a system of n nodes, the maximum number of faulty nodes can be (n-1) which is detected by DP-AFD algorithm. DP-AFD is periodic in nature which executes test cycles after regular intervals to detect the faulty nodes in the given distributed system., Comment: 19 pages, 13 figures, 1 table

We envision future mobile networks to be human-centric supporting interest-aware delivery, where an interest maybe based on behavior, such as mobility pattern, location, or web browsing (or user profile) such as affiliation, attributes, or activity. An essential capability in future networks will be the ability to provide scalable group communication. Current communication paradigms, including unicast and multicast, require explicit identification of destination nodes (through node IDs or group membership protocols), while directory services translate logical, interest-specific queries into destination IDs where parties are then connected using interest-oblivious protocols. The power and scalability of such paradigms is quite limited in the context of future, highly dynamic mobile social networks, where it is desirable in many scenarios to support implicit membership based on interest. In such scenarios, membership in interest-groups is not explicitly expressed by users, it is rather autonomously inferred by network protocols based on behavioral profiles. This removes the dependence on third parties (via directory lookup), the need for explicit expression of interest (or human intervention), and minimizes delivery overhead to uninterested users. While existing types of social networks will likely evolve in the context of mobile networks, we provide a novel paradigm of communication, deviating significantly from existing approaches and subsequently enabling qualitatively different capabilities for future services in mobile societies. In addition, our services and protocol design philosophy begins by analyzing the context in which the service is to be deployed, unlike most existing wireless networking approaches of designing general purpose protocols., Comment: 18 pages, 7 figures, successful project proposal 2008-2013, published for sharing and educational purposes to benefit other potential proposers

Mobility and network traffic have been traditionally studied separately. Their interaction is vital for generations of future mobile services and effective caching, but has not been studied in depth with real-world big data. In this paper, we characterize mobility encounters and study the correlation between encounters and web traffic profiles using large-scale datasets (30TB in size) of WiFi and NetFlow traces. The analysis quantifies these correlations for the first time, across spatio-temporal dimensions, for device types grouped into on-the-go Flutes and sit-to-use Cellos. The results consistently show a clear relation between mobility encounters and traffic across different buildings over multiple days, with encountered pairs showing higher traffic similarity than non-encountered pairs, and long encounters being associated with the highest similarity. We also investigate the feasibility of learning encounters through web traffic profiles, with implications for dissemination protocols, and contact tracing. This provides a compelling case to integrate both mobility and web traffic dimensions in future models, not only at an individual level, but also at pairwise and collective levels. We have released samples of code and data used in this study on GitHub, to support reproducibility and encourage further research (https://github.com/BabakAp/encounter-traffic)., Comment: Technical report with details for conference paper at MSWiM 2018, v3 adds GitHub link

With the ever-increasing demand for wireless traffic and quality of serives (QoS), wireless local area networks (WLANs) have developed into one of the most dominant wireless networks that fully influence human life. As the most widely used WLANs standard, Institute of Electrical and Electronics Engineers (IEEE) 802.11 will release the upcoming next generation WLANs standard amendment: IEEE 802.11ax. This article comprehensively surveys and analyzes the application scenarios, technical requirements, standardization process, key technologies, and performance evaluations of IEEE 802.11ax. Starting from the technical objectives and requirements of IEEE 802.11ax, this article pays special attention to high-dense deployment scenarios. After that, the key technologies of IEEE 802.11ax, including the physical layer (PHY) enhancements, multi-user (MU) medium access control (MU-MAC), spatial reuse (SR), and power efficiency are discussed in detail, covering both standardization technologies as well as the latest academic studies. Furthermore, performance requirements of IEEE 802.11ax are evaluated via a newly proposed systems and link-level integrated simulation platform (SLISP). Simulations results confirm that IEEE 802.11ax significantly improves the user experience in high-density deployment, while successfully achieves the average per user throughput requirement in project authorization request (PAR) by four times compared to the legacy IEEE 802.11. Finally, potential advancement beyond IEEE 802.11ax are discussed to complete this holistic study on the latest IEEE 802.11ax. To the best of our knowledge, this article is the first study to directly investigate and analyze the latest stable version of IEEE 802.11ax, and the first work to thoroughly and deeply evaluate the compliance of the performance requirements of IEEE 802.11ax., Comment: 155 pages, 53 figures

In wireless networks, stations can improve their received quality of service (QoS) by handling packets of source flows with higher priority. Additionally, in cooperative relay networks, the relays can handle transit flows with lower priority. We use game theory to model a two-hop relay network where each of the two involved stations can commit such selfish QoS manipulation. We design and evaluate a reputation-based incentive scheme called RISC2WIN, whereby a trusted third party (e.g., an access point) can limit selfish behavior and preserve appropriate QoS for both stations., Comment: 7 pages, 4 figures, 12 numbered equations

To achieve high-speed (giga-bit) connectivity for short-range wireless multimedia applications, the millimeter-wave (mmWave) wireless personal area networks with directional antennas are gaining increased interest. Due to the use of directional antennas and mmWave communications, the probability of non-interfering transmissions increases in a localized region. Network throughput can be increased immensely by the concurrent time allocation of non-interfering transmissions. The problem of finding optimum time allocation for concurrent transmissions is an NP-hard problem. In this paper, we propose two enhanced versions of previously proposed multi-hop concurrent transmission (MHCT) schemes. To increase network capacity, the proposed schemes efficiently make use of the free holes in the time-allocation map of the MHCT scheme; thus, making it more compact., Comment: 11 pages, 10 figures, published in ETRI Journal, Volume 36, Number 3, pp. 374-384, June 2014

Two major factors affecting mobile network performance are mobility and traffic patterns. Simulations and analytical-based performance evaluations rely on models to approximate factors affecting the network. Hence, the understanding of mobility and traffic is imperative to the effective evaluation and efficient design of future mobile networks. Current models target either mobility or traffic, but do not capture their interplay. Many trace-based mobility models have largely used pre-smartphone datasets (e.g., AP-logs), or much coarser granularity (e.g., cell-towers) traces. This raises questions regarding the relevance of existing models, and motivates our study to revisit this area. In this study, we conduct a multidimensional analysis, to quantitatively characterize mobility and traffic spatio-temporal patterns, for laptops and smartphones, leading to a detailed integrated mobility-traffic analysis. Our study is data-driven, as we collect and mine capacious datasets (with 30TB, 300k devices) that capture all of these dimensions. The investigation is performed using our systematic (FLAMeS) framework. Overall, dozens of mobility and traffic features have been analyzed. The insights and lessons learnt serve as guidelines and a first step towards future integrated mobility-traffic models. In addition, our work acts as a stepping-stone towards a richer, more-realistic suite of mobile test scenarios and benchmarks., Comment: 12 pages, 17 figures, conference paper at IEEE INFOCOM 2018, plus appendix (v3 fixes some typographical errors)

In this paper, a novel Extended Cognitive Mobile Terminal (ExCogNet-MT) scheme is presented. In this scheme, a "test bench" at receiver's Mobile Terminal (MT) can estimate the channel Signal to Noise Ratio (SNR) and can detect the jamming signal. The estimation scheme compares the Standard Deviation (SD) of received signal and processed signal, and on the bases of this comparison the "test bench" can determine the BER and corresponding SNR value of the channel. Simulation results demonstrated that under certain scenarios estimated SNR value can be helpful for tuning the parameters of protocol stack of 802.11a and WiMaxm., Comment: 6 pages, 4 figures, paper presented in conference, IEEE ICIET Karachi 2010

The future mobile networks facing many challenges and to cope these challenges, different standards and project has been proposed so far. Most recently Cognitive Networks has opened a new ground to present suitable architecture and mechanism for these challenges. The objective of this paper is to identify and discuss the challenges to the future mobile networks and to discuss some workable solutions to these challenges. Finally, on the basis of discussion a simple flexible network architecture is proposed., Comment: 6 pages, 4 figures, paper presented at JCICT 2011, China

Meeting the ever-growing information rate demands has become of utmost importance for optical communication systems. However, it has proven to be a challenging task due to the presence of Kerr effects, which have largely been regarded as a major bottleneck for enhancing the achievable information rates in modern optical communications. In this work, the optimisation and performance of digital nonlinearity compensation are discussed for maximising the achievable information rates in spectrally-efficient optical fibre communication systems. It is found that, for any given target information rate, there exists a trade-off between modulation format and compensated bandwidth to reduce the computational complexity requirement of digital nonlinearity compensation., Comment: Invited paper

Security experts have demonstrated numerous risks imposed by Internet of Things (IoT) devices on organizations. Due to the widespread adoption of such devices, their diversity, standardization obstacles, and inherent mobility, organizations require an intelligent mechanism capable of automatically detecting suspicious IoT devices connected to their networks. In particular, devices not included in a white list of trustworthy IoT device types (allowed to be used within the organizational premises) should be detected. In this research, Random Forest, a supervised machine learning algorithm, was applied to features extracted from network traffic data with the aim of accurately identifying IoT device types from the white list. To train and evaluate multi-class classifiers, we collected and manually labeled network traffic data from 17 distinct IoT devices, representing nine types of IoT devices. Based on the classification of 20 consecutive sessions and the use of majority rule, IoT device types that are not on the white list were correctly detected as unknown in 96% of test cases (on average), and white listed device types were correctly classified by their actual types in 99% of cases. Some IoT device types were identified quicker than others (e.g., sockets and thermostats were successfully detected within five TCP sessions of connecting to the network). Perfect detection of unauthorized IoT device types was achieved upon analyzing 110 consecutive sessions; perfect classification of white listed types required 346 consecutive sessions, 110 of which resulted in 99.49% accuracy. Further experiments demonstrated the successful applicability of classifiers trained in one location and tested on another. In addition, a discussion is provided regarding the resilience of our machine learning-based IoT white listing method to adversarial attacks.

Blind spots are one of the causes of road accidents in the hilly and flat areas. These blind spot accidents can be decreased by establishing an Internet of Vehicles (IoV) using Vehicle-2-Vehicle (V2V) and Vehicle-2-Infrastrtructure (V2I) communication systems. But the problem with these IoV is that most of them are using DSRC or single Radio Access Technology (RAT) as a wireless technology, which has been proven to be failed for efficient communication between vehicles. Recently, Cognitive Radio (CR) based IoV have to be proven best wireless communication systems for vehicular networks. However, the spectrum mobility is a challenging task to keep CR based vehicular networks interoperable and has not been addressed sufficiently in existing research. In our previous research work, the Cognitive Radio Site (CR-Site) has been proposed as in-vehicle CR-device, which can be utilized to establish efficient IoV systems. H In this paper, we have introduced the Emotions Inspired Cognitive Agent (EIC_Agent) based spectrum mobility mechanism in CR-Site and proposed a novel emotions controlled spectrum mobility scheme for efficient syntactic interoperability between vehicles. For this purpose, a probabilistic deterministic finite automaton using fear factor is proposed to perform efficient spectrum mobility using fuzzy logic. In addition, the quantitative computation of different fear intensity levels has been performed with the help of fuzzy logic. The system has been tested using active data from different GSM service providers on Mangla-Mirpur road. This is supplemented by extensive simulation experiments which validate the proposed scheme for CR based high-speed vehicular networks. The qualitative comparison with the existing-state-of the-art has proven the superiority of the proposed emotions controlled syntactic interoperable spectrum mobility scheme within cognitive radio based IoV systems., Comment: 33 pages, 16 figures

Communication networks, in general, and internet technology, in particular, is a fast-evolving area of research. While it is important to keep track of emerging trends in this domain, it is such a fast-growing area that it can be very difficult to keep track of literature. The problem is compounded by the fast-growing number of citation databases. While other databases are gradually indexing a large set of reliable content, currently the Web of Science represents one of the most highly valued databases. Research indexed in this database is known to highlight key advancements in any domain. In this paper, we present a Complex Network-based analytical approach to analyze recent data from the Web of Science in communication networks. Taking bibliographic records from the recent period of 2014 to 2017, we model and analyze complex scientometric networks. Using bibliometric coupling applied over complex citation data we present answers to co-citation patterns of documents, co-occurrence patterns of terms, as well as the most influential articles, among others, We also present key pivot points and intellectual turning points. Complex network analysis of the data demonstrates a considerably high level of interest in two key clusters labeled descriptively as "social networks" and "computer networks". In addition, key themes in highly cited literature were clearly identified as "communication networks," "social networks," and "complex networks"., Comment: 5 pages, 4 figures, 3 tables

Mobility Management (MM) techniques have conventionally been centralized in nature, wherein a single network entity has been responsible for handling the mobility related tasks of the mobile nodes attached to the network. However, an exponential growth in network traffic and the number of users has ushered in the concept of providing Mobility Management as a Service (MMaaS) to the wireless nodes attached to the 5G networks. Allowing for on-demand mobility management solutions will not only provide the network with the flexibility that it needs to accommodate the many different use cases that are to be served by future networks, but it will also provide the network with the scalability that is needed alongside the flexibility to serve future networks. And hence, in this paper, a detailed study of MMaaS has been provided, highlighting its benefits and challenges for 5G networks. Additionally, the very important property of granularity of service which is deeply intertwined with the scalability and flexibility requirements of the future wireless networks, and a consequence of MMaaS, has also been discussed in detail., Comment: Submitted to 14th International Symposium on Wireless Communication Systems

The achievable information rates of optical communication networks have been widely increased over the past four decades with the introduction and development of optical amplifiers, coherent detection, advanced modulation formats, and digital signal processing techniques. These developments promoted the revolution of optical communication systems and the growth of Internet, towards the direction of high-capacity and long-distance transmissions. The performance of long-haul high-capacity optical fiber communication systems is significantly degraded by transmission impairments, such as chromatic dispersion, polarization mode dispersion, laser phase noise and Kerr fiber nonlinearities. With the entire capture of the amplitude and phase of the signals using coherent optical detection, the powerful compensation and effective mitigation of the transmission impairments can be implemented using the digital signal processing in electrical domain. This becomes one of the most promising techniques for next-generation optical communication networks to achieve a performance close to the Shannon capacity limit. This chapter will focus on the introduction and investigation of digital signal processing employed for channel impairments compensation based on the coherent detection of optical signals, to provide a roadmap for the design and implementation of realtime optical fiber communication systems.

In multi-hop ad hoc networks, selfish nodes may unduly acquire high quality of service (QoS) by assigning higher priority to source packets and lower priority to transit packets. Such traffic remapping attacks (TRAs) are cheap to launch, impossible to prevent, hard to detect, and harmful to non-selfish nodes. While studied mostly in single-hop wireless network settings, TRAs have resisted analysis in multi-hop settings. In this paper we offer a game-theoretic approach: we derive a formal model of opportunistic TRAs, define a TRA game with a heuristic rank-based payoff function, and propose a boundedly rational multistage attack strategy that both selfish and non-selfish nodes are free to use. Thus non-selfish nodes are allowed to respond in kind to selfish ones. We characterize the form of equilibrium that the multistage play reaches and verify via simulation that it often coincides with a Nash equilibrium in which harmful TRAs are curbed in the first place, whereas harmless ones need not be., Comment: Accepted for IEEE GLOBECOM 2017

Grid infrastructures that have provided wide integrated use of resources are becoming the de-facto computing platform for solving large-scale problems in science, engineering and commerce. In this evolution, desktop grid technologies allow the grid communities to exploit the idle cycles of pervasive desktop PC systems to increase the available computing power. In this paper we present DotGrid, a cross-platform grid software. DotGrid is the first comprehensive desktop grid software utilising Microsoft's .NET Framework in Windows-based environments and MONO .NET in Unix-class operating systems to operate. Using DotGrid services and APIs, grid desktop middleware and applications can be implemented conveniently. We evaluated our DotGrid's performance by implementing a set of grid-based applications., Comment: 20 pages, 14 figures

DotGrid platform is a Grid infrastructure integrated with a set of open and standard protocols recently implemented on the top of Microsoft .NET in Windows and MONO .NET in UNIX/Linux. DotGrid infrastructure along with its proposed protocols provides a right and solid approach to targeting other platforms, e.g., the native C/C++ runtime. In this paper, we propose a new file transfer protocol called DotDFS as a high-throughput distributed file transfer component for DotGrid. DotDFS introduces some open binary protocols for efficient file transfers on current Grid infrastructures. DotDFS protocol also provides mechanisms for multiple file streams to gain high-throughput file transfer similar to GridFTP protocol, but by proposing and implementing a new parallel TCP connection-oriented paradigm. In our LAN tests, we have achieved better results than Globus GridFTP implementation particularly in multiple TCP streams and directory tree transfers. Our LAN experiences in memory-to-memory tests show that DotDFS accesses to the 94% bottleneck bandwidth while GridFTP is accessing 91%. In LAN disk-to-disk tests, comparing DotDFS protocol with GridFTP protocol unveils a set of interesting and technical problems in GridFTP for both the nature of the protocol and its implementation by Globus. In the WAN experimental studies, we propose a new idea for analytical modeling of file transfer protocols like DotDFS inspired by sampling, experimentation and mathematical interpolation approaches. The cross-platform and open standard-based features of DotDFS provide a substantial framework for unifying data access and resource sharing in real heterogeneous Grid environments., Comment: 28 pages, 21 figures

In this paper we introduce and describe the highly concurrent xDFS file transfer protocol and examine its cross-platform and cross-language implementation in native code for both Linux and Windows in 32 or 64-bit multi-core processor architectures. The implemented xDFS protocol based on xDotGrid.NET framework is fully compared with the Globus GridFTP protocol. We finally propose the xDFS protocol as a new paradigm of distributed systems for Internet services, and data-intensive Grid and Cloud applications. Also, we incrementally consider different developmental methods of the optimum file transfer systems, and their advantages and disadvantages. The vision of this paper tries as possible to minimize the overhead concerned with the file transfer protocol itself and to examine optimal software design patterns of that protocol. In all disk-to-disk tests for transferring a 2GB file with or without parallelism, the xDFS throughput at minimum 30% and at most 53% was superior to the GridFTP., Comment: 25 pages, 20 figures

Mobile AdHoc NETworks (MANETs) have been identified as a key emerging technology for scenarios in which IEEE 802.11 or cellular communications are either infeasible, inefficient, or cost-ineffective. Smartphones are the most adequate network nodes in many of these scenarios, but it is not straightforward to build a network with them. We extensively survey existing possibilities to build applications on top of ad-hoc smartphone networks for experimentation purposes, and introduce a taxonomy to classify them. We present AdHocDroid, an Android package that creates an IP-level MANET of (rooted) Android smartphones, and make it publicly available to the community. AdHocDroid supports standard TCP/IP applications, providing real smartphone IEEE 802.11 MANET and the capability to easily change the routing protocol. We tested our framework on several smartphones and a laptop. We validate the MANET running off-the-shelf applications, and reporting on experimental performance evaluation, including network metrics and battery discharge rate., Comment: 6 pages, 7 figures, 1 table

Achievable information rates (AIRs) of wideband optical communication systems using ~40 nm (~5 THz) EDFA and ~100 nm (~12.5 THz) distributed Raman amplification are estimated based on a first-order perturbation analysis. The AIRs of each individual channel have been evaluated for DP-64QAM, DP-256QAM, and DP-1024QAM modulation formats. The impact of full-field nonlinear compensation (FF-NLC) and probabilistically shaped constellations using a Maxwell-Boltzmann distribution were studied and compared to electronic dispersion compensation. It is found that a probabilistically shaped DP-1024QAM constellation combined with FF-NLC yields AIRs of ~75 Tbit/s for the EDFA scheme and ~223 Tbit/s for the Raman amplification scheme over 2000 km standard single mode fibre transmission.

The paper presents some theoretical and practical considerations regarding the TV information distribution in local (small and medium) networks, using different technologies and architectures. The SMATV concept is chosen to be presented extensively. The most important design formulae are presented with a software package supporting the network planner to design and optimize the network. A case study is realized, using standard components in SMATV, for a 5 floor building. The study proved that it is possible to design and optimize the entire network, without realizing first a costly experimental setup. It is also possible to run different architectures, optimizing also the costs of the final solution of network., Comment: 4 pages, 5 figures, Acta Technica Napocensis, Electronics and Telecommunications, 2014, No.4

The latest technological advancements in the telecommunications domain (e.g., widespread adoption of mobile devices, introduction of 5G wireless communications, etc.) have brought new stakeholders into the spotlight. More specifically, Over-the-Top (OTT) providers have recently appeared, offering their services over the existing deployed telecommunication networks. The entry of the new players has changed the dynamics in the domain, as it creates conflicting situations with the Internet Service Providers (ISPs), who traditionally dominate the area, motivating the necessity for novel analytical studies for this relationship. However, despite the importance of accessing real observational data, there is no database with the aggregate information that can serve as a solid base for this research. To that end, this document provides a detailed summary report for financial and statistic data for the period 2008-2013 that can be exploited for realistic econometric models that will provide useful insights on this topic. The document summarizes data from various sources with regard to the ISP revenues and Capital Expenditures (CAPEX), the OTT revenues, the Internet penetration and the Gross Domestic Product (GDP), taking into account three big OTT providers (i.e., Facebook, Skype, WhatsApp) and ten major ISPs that operate in seven different countries., Comment: 34 pages