Self-organizing TDMA: a distributed contention-resolution MAC protocol

This paper presents a self-organizing time division multiple access (SO-TDMA) protocol for contention resolution aiming to support delay-sensitive applications. The proposed SOTDMA follows a cognition cycle where each node independently observes the operation environment, learns about the network traffic load, and then makes decisions to adapt the protocol for smart coexistence. Channel access operation in SO-TDMA is similar to carrier-sense multiple-access (CSMA) in the beginning, but then quickly converges to TDMA with an adaptive pseudo-frame structure. This approach has the benefits of TDMA in a highload traffic condition, and overcomes its disadvantages in lowload, heterogeneous traffic scenarios. Furthermore, it supports distributed and asynchronous channel-access operation. These are achieved by adapting the transmission-opportunity duration to the common idle/busy channel state information acquired by each node, without any explicit message passing among nodes. The process of adjusting the transmission duration is modeled as a congestion control problem to develop an additive-increasemultiplicative-decrease (AIMD) algorithm, which monotonically converges to fairness. Furthermore, the initial access phase of SO-TDMA is modeled as a Markov chain with one absorbing state and its required convergence time is studied accordingly. Performance of SO-TDMA in terms of effective capacity, system throughput, collision probability, delay-outage probability and fairness is investigated. Simulation results illustrate its effectiveness in performance improvement, approaching the ideal case that needs complete and precise information about the queue length and the channel conditions of all nodes

A Survey on Multi-AP Coordination Approaches over Emerging WLANs: Future Directions and Open Challenges

Recent advancements in wireless local area network (WLAN) technology include IEEE 802.11be and 802.11ay, often known as Wi-Fi 7 and WiGig, respectively. The goal of these developments is to provide Extremely High Throughput (EHT) and low latency to meet the demands of future applications like as 8K videos, augmented and virtual reality, the Internet of Things, telesurgery, and other developing technologies. IEEE 802.11be includes new features such as 320 MHz bandwidth, multi-link operation, Multi-user Multi-Input Multi-Output, orthogonal frequency-division multiple access, and Multiple-Access Point (multi-AP) coordination (MAP-Co) to achieve EHT. With the increase in the number of overlapping APs and inter-AP interference, researchers have focused on studying MAP-Co approaches for coordinated transmission in IEEE 802.11be, making MAP-Co a key feature of future WLANs. Moreover, similar issues may arise in EHF bands WLAN, particularly for standards beyond IEEE 802.11ay. This has prompted researchers to investigate the implementation of MAP-Co over future 802.11ay WLANs. Thus, in this article, we provide a comprehensive review of the state-of-the-art MAP-Co features and their shortcomings concerning emerging WLAN. Finally, we discuss several novel future directions and open challenges for MAP-Co.Comment: The reason for the replacement of the previous version of the paper is due to a change in the author's list. As a result, a new version has been created, which serves as the final draft version before acceptance. This updated version contains all the latest changes and improvements made to the pape

ANALYSIS OF USER MOBILITY PERFORMANCE ON SOFTWARE DEFINED WIRELESS NETWORK USING DIJKSTRA ALGORITHM

  Over the last decade, wireless devices have developed rapidly until predictions will develop with high complexity and dynamic. So that new capabilities are needed for wireless problems in this problem. Software Defined Network (SDN) is generally a wire-based network, but to meet the needs of users in terms of its implementation, it has begun to introduce a Wireless-based SDN called Software Defined Wireless Network (SDWN) which provides good service quality and reach and higher tools, so as to be able to provide new capabilities to wireless in a high complexity and very dynamic. When SDN is implemented in a wireless network it will require a routing solution that chooses paths due to network complexity. In this paper, SDWN is tested by being applied to mesh topologies of 4,6 and 8 access points (AP) because this topology is very often used in wireless-based networks. To improve network performance, Dijkstra's algorithm is added with the user mobility scheme used is RandomDirection. The Dijkstra algorithm was chosen because it is very effective compared to other algorithms. The performance measured in this study is Quality of Service (QoS), which is a parameter that indicates the quality of data packets in a network. The measurement results obtained show that the QoS value in this study meets the parameters considered by the ITU-T G1010 with a delay value of 1.3 ms for data services and packet loss below 0.1%. When compared with the ITU-T standard, the delay and packet loss fall into the very good category

Machine Learning Aided Methods for Resilient Industrial Wireless Sensor Network

Le Wireless Sensor Network (WSN) possono essere definite come un’ infrastruttura composta da sensori/dispositivi in grado di calcolare comunicare e effettuare sensing sul ambiente che gli circonda processando e analizzando i dati in modo da reagire a eventi e fenomeni che possono occorrere durante la comunicazione. Questo motiva un enorme effort nella ricerca, standardizzazione e investimento industriale in questo campo, nell’ultimo decennio. L’uso delle WSN nell’ambiente industriale è soggetto a diverse problematiche, dovuto all’ostilità dell’ambiente, come rumore, shadwoing, multi-percorso e interferenze. Nel nostro progetto, proponiamo un meccanismo basato sulle condizioni di propagazione del canale e algoritmi di machine learning che ci permettono di classificare lo stato del canale (LOS o NLOS) e migliorare qualità, sicurezza e in particolar modo l’affidabilità del sistema radio link da noi esaminato in differenti ambienti

Five Facets of 6G: Research Challenges and Opportunities

Whilst the fifth-generation (5G) systems are being rolled out across the globe, researchers have turned their attention to the exploration of radical next-generation solutions. At this early evolutionary stage we survey five main research facets of this field, namely {\em Facet~1: next-generation architectures, spectrum and services, Facet~2: next-generation networking, Facet~3: Internet of Things (IoT), Facet~4: wireless positioning and sensing, as well as Facet~5: applications of deep learning in 6G networks.} In this paper, we have provided a critical appraisal of the literature of promising techniques ranging from the associated architectures, networking, applications as well as designs. We have portrayed a plethora of heterogeneous architectures relying on cooperative hybrid networks supported by diverse access and transmission mechanisms. The vulnerabilities of these techniques are also addressed and carefully considered for highlighting the most of promising future research directions. Additionally, we have listed a rich suite of learning-driven optimization techniques. We conclude by observing the evolutionary paradigm-shift that has taken place from pure single-component bandwidth-efficiency, power-efficiency or delay-optimization towards multi-component designs, as exemplified by the twin-component ultra-reliable low-latency mode of the 5G system. We advocate a further evolutionary step towards multi-component Pareto optimization, which requires the exploration of the entire Pareto front of all optiomal solutions, where none of the components of the objective function may be improved without degrading at least one of the other components

Framework for Content Distribution over Wireless LANs

Wireless LAN (also called as Wi-Fi) is dominantly considered as the most pervasive technology for Intent access. Due to the low-cost of chipsets and support for high data rates, Wi-Fi has become a universal solution for ever-increasing application space which includes, video streaming, content delivery, emergency communication, vehicular communication and Internet-of-Things (IoT). Wireless LAN technology is defined by the IEEE 802.11 standard. The 802.11 standard has been amended several times over the last two decades, to incorporate the requirement of future applications. The 802.11 based Wi-Fi networks are infrastructure networks in which devices communicate through an access point. However, in 2010, Wi-Fi Alliance has released a specification to standardize direct communication in Wi-Fi networks. The technology is called Wi-Fi Direct. Wi-Fi Direct after 9 years of its release is still used for very basic services (connectivity, file transfer etc.), despite the potential to support a wide range of applications. The reason behind the limited inception of Wi-Fi Direct is some inherent shortcomings that limit its performance in dense networks. These include the issues related to topology design, such as non-optimal group formation, Group Owner selection problem, clustering in dense networks and coping with device mobility in dynamic networks. Furthermore, Wi-Fi networks also face challenges to meet the growing number of Wi Fi users. The next generation of Wi-Fi networks is characterized as ultra-dense networks where the topology changes frequently which directly affects the network performance. The dynamic nature of such networks challenges the operators to design and make optimum planifications. In this dissertation, we propose solutions to the aforementioned problems. We contributed to the existing Wi-Fi Direct technology by enhancing the group formation process. The proposed group formation scheme is backwards-compatible and incorporates role selection based on the device's capabilities to improve network performance. Optimum clustering scheme using mixed integer programming is proposed to design efficient topologies in fixed dense networks, which improves network throughput and reduces packet loss ratio. A novel architecture using Unmanned Aeriel Vehicles (UAVs) in Wi-Fi Direct networks is proposed for dynamic networks. In ultra-dense, highly dynamic topologies, we propose cognitive networks using machine-learning algorithms to predict the network changes ahead of time and self-configuring the network

Delay Performance and Cybersecurity of Smart Grid Infrastructure

To address major challenges to conventional electric grids (e.g., generation diversification and optimal deployment of expensive assets), full visibility and pervasive control over utilities\u27 assets and services are being realized through the integratio

System Security Assurance: A Systematic Literature Review

System security assurance provides the confidence that security features, practices, procedures, and architecture of software systems mediate and enforce the security policy and are resilient against security failure and attacks. Alongside the significant benefits of security assurance, the evolution of new information and communication technology (ICT) introduces new challenges regarding information protection. Security assurance methods based on the traditional tools, techniques, and procedures may fail to account new challenges due to poor requirement specifications, static nature, and poor development processes. The common criteria (CC) commonly used for security evaluation and certification process also comes with many limitations and challenges. In this paper, extensive efforts have been made to study the state-of-the-art, limitations and future research directions for security assurance of the ICT and cyber-physical systems (CPS) in a wide range of domains. We conducted a systematic review of requirements, processes, and activities involved in system security assurance including security requirements, security metrics, system and environments and assurance methods. We highlighted the challenges and gaps that have been identified by the existing literature related to system security assurance and corresponding solutions. Finally, we discussed the limitations of the present methods and future research directions