Design and optimization of QoS-based medium access control protocols for next-generation wireless LANs

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In recent years, there have been tremendous advances in wireless & mobile communications, including wireless radio techniques, networking protocols, and mobile devices. It is expected that different broadband wireless access technologies, e.g., WiFi (IEEE 802.11) and WiMAX (IEEE 802.16) will coexist in the future. In the meantime, multimedia applications have experienced an explosive growth with increasing user demands. Nowadays, people expect to receive high-speed video, audio, voice and web services even when being mobile. The key question that needs to be answered, then, is how do we ensure that users always have the "best" network performance with the "lowest" costs in such complicated situations? The latest IEEE 802.11n standards attains rates of more than 100 Mbps by introducing innovative enhancements at the PHY and MAC layer, e.g. MIMO and Frame Aggregation, respectively. However, in this thesis we demonstrate that frame aggregation's performance adheres due to the EDCA scheduler's priority mechanism and consequently resulting in the network's poor overall performance. Short waiting times for high priority flows into the aggregation queue resolves to poor channel utilization. A Delayed Channel Access algorithm was designed to intentionally postpone the channel access procedure so that the number of packets in a formed frame can be increased and so will the network's overall performance. However, in some cases, the DCA algorithm has a negative impact on the applications that utilize the TCP protocol, especially the when small TCP window sizes are engaged. So, the TCP process starts to refrain from sending data due to delayed acknowledgements and the overall throughput drops. In this thesis, we address the above issues by firstly demonstrating the potential performance benefits of frame aggregation over the next generation wireless networks. The efficiency and behaviour of frame aggregation within a single queue, are mathematically analysed with the aid of a M=G[a;b]=1=K model. Results show that a trade-off choice has to be taken into account over minimizing the waiting time or maximizing utilization. We also point out that there isn't an optimum batch collection rule which can be assumed as generally valid but individual cases have to be considered separately. Secondly, we demonstrate through extensive simulations that by introducing a method, the DCA algorithm, which dynamically determines and adapts batch collections based upon the traffic's characteristics, QoS requirements and server's maximum capacity, also improves e ciency. Thirdly, it is important to understand the behaviour of the TCP ows over the WLAN and the influence that DCA has over the degrading performance of the TCP protocol. We investigate the cause of the problem and provide the foundations of designing and implementing possible solutions. Fourthly, we introduce two innovative proposals, one amendment and one extension to the original DCA algorithm, called Adaptive DCA and Selective DCA, respectively. Both solutions have been implemented in OPNET and extensive simulation runs over a wide set of scenarios show their effectiveness over the network's overall performance, each in its own way.This study was supported by the Engineering and Physical Sciences Research Council (EPSRC)

Overlapping Multi-hop Clustering for Wireless Sensor Networks

Clustering is a standard approach for achieving efficient and scalable performance in wireless sensor networks. Traditionally, clustering algorithms aim at generating a number of disjoint clusters that satisfy some criteria. In this paper, we formulate a novel clustering problem that aims at generating overlapping multi-hop clusters. Overlapping clusters are useful in many sensor network applications, including inter-cluster routing, node localization, and time synchronization protocols. We also propose a randomized, distributed multi-hop clustering algorithm (KOCA) for solving the overlapping clustering problem. KOCA aims at generating connected overlapping clusters that cover the entire sensor network with a specific average overlapping degree. Through analysis and simulation experiments we show how to select the different values of the parameters to achieve the clustering process objectives. Moreover, the results show that KOCA produces approximately equal-sized clusters, which allows distributing the load evenly over different clusters. In addition, KOCA is scalable; the clustering formation terminates in a constant time regardless of the network size

Lightweight mobile and wireless systems: technologies, architectures, and services

1Department of Information and Communication Systems Engineering (ICSE), University of the Aegean, 81100 Mytilene, Greece 2Department of Information Engineering and Computer Science (DISI), University of Trento, 38123 Trento, Italy 3Department of Informatics, Alexander Technological Educational Institute of Thessaloniki, Thessaloniki, 574 00 Macedonia, Greece 4Centre Tecnologic de Telecomunicacions de Catalunya (CTTC), 08860 Barcelona, Spain 5North Carolina State University (NCSU), Raleigh, NC 27695, US

DynaMO—Dynamic Multisuperframe Tuning for Adaptive IEEE 802.15.4e DSME Networks

Recent advancements in the IoT domain have been pushing for stronger demands of Qualityof-Service (QoS) and in particular for improved determinism for time-critical wireless communications under power constraints. The IEEE 802.15.4e standard protocol introduced several new MAC behaviors that provide enhanced time-critical and reliable communications. The Deterministic Synchronous Multichannel Extension (DSME) is one of its prominent MAC behaviors that combines contention-based and contentionfree communication, guaranteeing bounded delays and improved reliability and scalability by leveraging multi-channel access and CAP reduction. However, DSME has a multi-superframe structure, which is statically defined at the beginning of the network. As the network evolves dynamically by changing its traffic characteristics, these static settings can affect the overall throughput and increase the network delay because of improper allocation of bandwidth. In this paper, we address this problem, and we present a dynamic multi-superframe tuning technique that dynamically adapts the multi-superframe structure based on the size of the network. This technique improves the QoS by providing 15-30% increase in throughput and 15-35% decrease in delay when compared to static DSME networksinfo:eu-repo/semantics/publishedVersio