Energy efficient medium access protocol for DS-CDMA based wireless sesor networks.

Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2012.Wireless Sensor Networks (WSN), a new class of devices, has the potential to revolutionize the capturing, processing, and communication of critical data at low cost. Sensor networks consist of small, low-power, and low-cost devices with limited computational and wireless communication capabilities. These sensor nodes can only transmit a finite number of messages before they run out of energy. Thus, reducing the energy consumption per node for end-to-end data transmission is an important design consideration for WSNs. The Medium Access Control (MAC) protocols aim at providing collision-free access to the wireless medium. MAC protocols also provide the most direct control over the utilization of the transceiver, which consumes most of the energy of the sensor nodes. The major part of this thesis is based on a proposed MAC protocol called Distributed Receiver-oriented MAC (DRMACSN) protocol for code division multiple access (CDMA) based WSNs. The proposed MAC protocol employs the channel load blocking scheme to reduce energy consumption in the network. The performance of the proposed MAC protocol is verified through simulations for average packet throughput, average delay and energy consumption. The performance of the proposed MAC protocol is also compared to the IEEE 802.15.4 MAC and the MAC without the channel load sensing scheme via simulations. An analytical model is derived to analyse the average packet throughput and average energy consumption performance for the DRMACSN MAC protocol. The packet success probability, the message success and blocking probabilities are derived for the DRMACSN MAC protocol. The discrete-time multiple vacation queuing models are used to model the delay behaviour of the DRMACSN MAC protocol. The Probability Generating Functions (PGF) of the arrivals of new messages in sleep, back-off and transmit states are derived. The PGF of arrivals of retransmitted packets of a new message are also derived. The queue length and delay expressions for both the Bernoulli and Poisson message arrival models are derived. Comparison between the analytical and simulation results shows that the analytical model is accurate. The proposed MAC protocol is aimed at having an improved average packet throughput, a reduced packet delay, reduced energy consumption performance for WSN

Modelling and performability evaluation of Wireless Sensor Networks

This thesis presents generic analytical models of homogeneous clustered Wireless Sensor Networks (WSNs) with a centrally located Cluster Head (CH) coordinating cluster communication with the sink directly or through other intermediate nodes. The focus is to integrate performance and availability studies of WSNs in the presence of sensor nodes and channel failures and repair/replacement. The main purpose is to enhance improvement of WSN Quality of Service (QoS). Other research works also considered in this thesis include modelling of packet arrival distribution at the CH and intermediate nodes, and modelling of energy consumption at the sensor nodes. An investigation and critical analysis of wireless sensor network architectures, energy conservation techniques and QoS requirements are performed in order to improve performance and availability of the network. Existing techniques used for performance evaluation of single and multi-server systems with several operative states are investigated and analysed in details. To begin with, existing approaches for independent (pure) performance modelling are critically analysed with highlights on merits and drawbacks. Similarly, pure availability modelling approaches are also analysed. Considering that pure performance models tend to be too optimistic and pure availability models are too conservative, performability, which is the integration of performance and availability studies is used for the evaluation of the WSN models developed in this study. Two-dimensional Markov state space representations of the systems are used for performability modelling. Following critical analysis of the existing solution techniques, spectral expansion method and system of simultaneous linear equations are developed and used to solving the proposed models. To validate the results obtained with the two techniques, a discrete event simulation tool is explored. In this research, open queuing networks are used to model the behaviour of the CH when subjected to streams of traffic from cluster nodes in addition to dynamics of operating in the various states. The research begins with a model of a CH with an infinite queue capacity subject to failures and repair/replacement. The model is developed progressively to consider bounded queue capacity systems, channel failures and sleep scheduling mechanisms for performability evaluation of WSNs. Using the developed models, various performance measures of the considered system including mean queue length, throughput, response time and blocking probability are evaluated. Finally, energy models considering mean power consumption in each of the possible operative states is developed. The resulting models are in turn employed for the evaluation of energy saving for the proposed case study model. Numerical solutions and discussions are presented for all the queuing models developed. Simulation is also performed in order to validate the accuracy of the results obtained. In order to address issues of performance and availability of WSNs, current research present independent performance and availability studies. The concerns resulting from such studies have therefore remained unresolved over the years hence persistence poor system performance. The novelty of this research is a proposed integrated performance and availability modelling approach for WSNs meant to address challenges of independent studies. In addition, a novel methodology for modelling and evaluation of power consumption is also offered. Proposed model results provide remarkable improvement on system performance and availability in addition to providing tools for further optimisation studies. A significant power saving is also observed from the proposed model results. In order to improve QoS for WSN, it is possible to improve the proposed models by incorporating priority queuing in a mixed traffic environment. A model of multi-server system is also appropriate for addressing traffic routing. It is also possible to extend the proposed energy model to consider other sleep scheduling mechanisms other than On-demand proposed herein. Analysis and classification of possible arrival distribution of WSN packets for various application environments would be a great idea for enabling robust scientific research

WLAN aware cognitive medium access control protocol for IoT applications

© 2020 by the authors. Internet of Things (IoT)-based devices consist of wireless sensor nodes that are battery-powered; thus, energy efficiency is a major issue. IEEE 802.15.4-compliant IoT devices operate in the unlicensed Industrial, Scientific, and Medical (ISM) band of 2.4 GHz and are subject to interference caused by high-powered IEEE 802.11-compliant Wireless Local Area Network (WLAN) users. This interference causes frequent packet drop and energy loss for IoT users. In this work, we propose a WLAN Aware Cognitive Medium Access Control (WAC-MAC) protocol for IoT users that uses techniques, such as energy detection based sensing, adaptive wake-up scheduling, and adaptive backoff, to reduce interference with the WSN and improve network lifetime of the IoT users. Results show that the proposedWAC-MAC achieves a higher packet reception rate and reduces the energy consumption of IoT nodes

Energy efficient wireless sensor network protocols for monitoring and prognostics of large scale systems

In this work, energy-efficient protocols for wireless sensor networks (WSN) with applications to prognostics are investigated. Both analytical methods and verification are shown for the proposed methods via either hardware experiments or simulation. This work is presented in five papers. Energy-efficiency methods for WSN include distributed algorithms for i) optimal routing, ii) adaptive scheduling, iii) adaptive transmission power and data-rate control --Abstract, page iv

Industry 4.0: Industrial IoT Enhancement and WSN Performance Analysis

L'abstract è presente nell'allegato / the abstract is in the attachmen

Smart Wireless Sensor Networks

The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig