Energy Efficient Topology Control Algorithm For Wireless Sensor Networks

Despite the considerable research efforts devoted to extending the lifetime of wireless sensor networks (WSNs) by making them more energy efficient, there are still a number of unresolved issues. Among the possible solutions for improving their overall energy efficiency, topology control has significant potential. Distributed topology control is a difficult problem, and optimal solutions are not possible except for very simple topologies. Because of this, heuristic methods are used, but the solutions proposed in the research literature are usually tested with overly simplistic simulation models and consequently they fail to perform satisfactorily in real networks. The research project reported in this thesis proposes three new topology control methods that are tested on highly realistic simulation models calibrated with data collected on an experimental wireless sensor network. These models accurately handle interference effects, realistic transmission ranges and imperfect communication links. Additionally, the correctness of the proposed methods was verified using theoretical analysis. Two leading algorithms were used as benchmarks. Based on the outcomes of a thorough literature review and analysis of existing techniques, distributed connected dominating set (CDS) approach was selected as the starting point for the design of the proposed algorithms. The proposed algorithms are not only distributed but also use localized information for computing a CDS. Given that the CDS serves various tasks in a WSN, a fair load distribution strategy was adopted to prolong the network lifetime. This strategy takes into account the remaining energy levels at each node when choosing the eligible CDS nodes. The first topology control technique called the three-phase single initiator (TPSI) was developed to form a small CDS for medium and dense networks (i.e., in deployments when average node degree is relatively high) with minimal communication overhead, computational complexity and energy consumption. The simulation results demonstrate that the TPSI algorithm generates a small CDS for both medium and dense networks but not for sparse networks. These results also prove that the impact of network density on performance of an algorithm is significant and cannot be ignored. The second technique, single-phase single initiator (SPSI) on the other hand was proposed for applications that require fast convergence, and is best suited to WSN applications that have sparse topologies. The simulation results show that SPSI can generate a small CDS for sparse networks using low message overhead and energy consumption, and compute a CDS faster than the TPSI algorithm. The third one, the Two-phase multiple initiator (TPMI) algorithm adapts well to dynamic topology changes, thus it is suitable for applications that require frequent topology updates. Instead of relying on a single initiator to construct the CDS as in the TPSI and SPSI, the TPMI algorithm uses multiple initiators. The simulation results show that although the CDS size of TPMI is larger than the ones generated by TPSI or SPSI, it outperforms them in terms of energy consumption, network lifetime and convergence time in networks with rapidly changing topologies. Best suited algorithm for a particular installation can be selected manually, or by using some measurement techniques, the structure of a network can be probed to activate the optimal method automatically.

The eld of wireless sensor networks continues to evolve and grow in both practical and research domains. More and more wireless sensor networks are being used to gather information in real life applications. It is common to see how this technology is being applied in irrigation systems, intelligent buildings, bridges, security mec- nisms,militaryoperations,transportation-relatedapplications,etc.Atthesametime, new developments in hardware, software, and communication technologies are - panding these possibilities. As in any other technology, research brings new dev- opments and re nements and continuous improvements of current approaches that push the technology even further. Looking toward the future, the technology seems even more promising in two directions. First, a few years from now more powerful wireless sensor devices will be available, and wireless sensor networks will have applicability in an endless number of scenarios, as they will be able to handle traf c loads not possible today, make more computations, store more data, and live longer because of better energy sources. Second,a few years from now, the opposite scenario might also be possible. The availability of very constrained, nanotechnology-made wireless sensor devices will bring a whole new world of applications, as they will be able to operate in - vironments and places unimaginable today. These two scenarios, at the same time, will both bring new research challenges that are always welcome to researchers.

Topology control is fundamental to solving scalability and capacity problems in large-scale wireless ad hoc and sensor networks. Forthcoming wireless multi-hop networks such as ad hoc and sensor networks will allow network nodes to control the communication topology by choosing their transmitting ranges. Briefly, topology control (TC) is the art of co-ordinating nodes’ decisions regarding their transmitting ranges, to generate a network with the desired features. Building an optimized network topology helps surpass the prevalent scalability and capacity problems. Topology Control in Wireless Ad Hoc and Sensor Networks makes the case for topology control and provides an exhaustive coverage of TC techniques in wireless ad hoc and sensor networks, considering both stationary networks, to which most of the existing solutions are tailored, and mobile networks. The author introduces a new taxonomy of topology control and gives a full explication of the applications and challenges of this important topic. Topology Control in Wireless Ad Hoc and Sensor Networks: Defines topology control and explains its necessity, considering both stationary and mobile networks. Describes the most representative TC protocols and their performance. Covers the critical transmitting range for stationary and mobile networks, topology optimization problems such as energy efficiency, and distributed topology control. Discusses implementation and ‘open issues’, including realistic models and the effect of multi-hop data traffic. Presents a case study on routing protocol design, to demonstrate how TC can ease the design of cooperative routing protocols. This invaluable text will provide graduate students in Computer Science, Electrical and Computer Engineering, Applied Mathematics and Physics, researchers in the field of ad hoc networking, and professionals in wireless telecoms as well as networking system developers with a single reference resource on topology control.

ABSTRACT: Wireless Sensor Networks (WSN) offer a flexible low-cost solution to the problem of event monitoring, especially in places with limited accessibility or that represent danger to humans. WSNs are made of resource-constrained wireless devices, which require energy efficient mechanisms, algorithms and protocols. One of these mechanisms is Topology Control (TC) composed of two mechanisms, Topology Construction and Topology Maintenance. This dissertation expands the knowledge of TC in many ways. First, it introduces a comprehensive taxonomy for topology construction and maintenance algorithms for the first time. Second, it includes four new topology construction protocols: A3, A3Lite, A3Cov and A3LiteCov. These protocols reduce the number of active nodes by building a Connected Dominating Set (CDS) and then turning off unnecessary nodes. The A3 and A3-Lite protocols guarantee a connected reduced structure in a very energy efficient manner. The A3Cov and A3LiteCov protocols are extensions of their predecessors that increase the sensing coverage of the network. All these protocols are distributed -they do not require localization information, and present low message and computational complexity. Third, this dissertation also includes and evaluates the performance of four topology maintenance protocols: Recreation (DGTRec), Rotation (SGTRot), Rotation and Recreation (HGTRotRec), and Dynamic Local-DSR (DLDSR). Finally, an event-driven simulation tool named Atarraya was developed for teaching, researching and evaluating topology control protocols, which fills a need in the area of topology control that other simulators cannot. Atarraya was used to implement all the topology construction and maintenance cited, and to evaluate their performance. The results show that A3Lite produces a similar number of active nodes when compared to A3, while spending less energy due to its lower message complexity. A3Cov and A3CovLite show better or similar coverage than the other distributed protocols discussed here, while preserving the connectivity and energy efficiency from A3 and A3Lite. In terms of network lifetime, depending on the scenarios, it is shown that there can be a substantial increase in the network lifetime of 450% when a topology construction method is applied, and of 3200% when both topology construction and maintenance are applied, compared to the case where no topology control is used.

This book provides an essential overview of IoT, energy-efficient topology control protocols, motivation, and challenges for topology control for Wireless Sensor Networks, and the scope of the research in the domain of IoT. Further, it discusses the different design issues of topology control and energy models for IoT applications, different types of simulators with their advantages and disadvantages. It also discusses extensive simulation results and comparative analysis for various algorithms. The key point of this book is to present a solution to minimize energy and extend the lifetime of IoT networks using optimization methods to improve the performance. Features: Describes various facets necessary for energy optimization in IoT domain. Covers all aspects to achieve energy optimization using latest technologies and algorithms, in wireless sensor networks. Presents various IoT and Topology Control Methods and protocols, various network models, and model simulation using MATLAB®. Reviews methods and results of optimization with Simulation Hardware architecture leading to prolonged life of IoT networks. First time introduces bio-inspired algorithms in the IoT domain for performance optimization This book aims at Graduate Students, Researchers in Information Technology, Computer Science and Engineering, Electronics and Communication Engineering.

For a wide spectrum of applications, the wireless sensor network (WSN) technology exhibited revolutionary advantages when compared to traditional solutions. Among all the energy-saving and network throughput improvement schemes, topology control has been well recognized as an effective one. In traditional topology control, a wireless network is represented using the deterministic model that assumes a pair of nodes is either connected or disconnected. Rich empirical studies have shown that in most practical environments, lossy links of intermittent connections account the dominating majority of WSNs because various reasons.By successfully leveraging these lossy links, higher energy-efficiency and network capacities are feasible. By traditional approaches, however, WSN topologies can hardly be well characterized. Motivated by this, we in this book discuss a new model call probabilistic topology control, fully taking the lossy links into account. We prove that in general PTC is a NP-hard problem. Based PTC we propose two algorithms CONREAP and BRASP, and one routing algorithm. Analysis and experimental results showed that these algorithms are very effectively.

First Published in 2018. This book covers the concepts of architecture and applications on wireless ad hoc networks and wireless sensor networks, including topology control, the clustering algorithm in topology control, and virtual backbone construction algorithms, focusing on connected dominating set construction, including various transformations for dominating sets.

Energy Management in Wireless Sensor Networks discusses this unavoidable issue in the application of Wireless Sensor Networks (WSN). To guarantee efficiency and durability in a network, the science must go beyond hardware solutions and seek alternative software solutions that allow for better data control from the source to delivery. Data transfer must obey different routing protocols, depending on the application type and network architecture. The correct protocol should allow for fluid information flow, as well as optimizing power consumption and resources – a challenge faced by dense networks. The topics covered in this book provide answers to these needs by introducing and exploring computer-based tools and protocol strategies for low power consumption and the implementation of routing mechanisms which include several levels of intervention, ranging from deployment to network operation. Explores ways to manage energy consumption during the design and implementation of WSN Helps users implement an increase in network longevity Presents intrinsic characteristics of wireless sensor networks