Paper id 28201419

Paper id 28201419

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  International Journal ofResearch in Advent Technology, Vol.2, No.8, August 2014 E-ISSN: 2321-9637 36 A Study on Topology Control in Wireless Sensor Network Arathy S.lal1,Remya Annie Eapen2 Department of ECE 1, 2, PG Student1 , Assistant Professor2 Email: [email protected],[email protected] Abstract- The sensor nodes in the Wireless Sensor Networks (WSNs) are prone to deterioration due to many reasons, for example, harsh environment or running out of battery therefore, the WSNs are expected to be able to retain network connectivity. Topology Control (TC) is one of the most important technique used to reduce energy utilization . This technique integrate the decisions of network nodes about their transmission power for prolong network lifetime to save energy while preserving network connectivity. The topology control is a crucial process to maximize the network lifetime of wireless sensor networks. Index Terms- Wireless Sensor Network (WSN), Topology Control, Network lifetime 1. INTRODUCTION Wireless Sensor Networks (WSNs) have become a looming technology that has a extensive range of potential functioning including object tracking, environment monitoring, scientific forecasting and observing , traffic control and etc. The nodes in WSNs are more likely to be detached from each other. In WSNs, hundreds or thousands of sensor nodes are often randomly setup in inaccessible areas where battery cannot to be recharged or replaced .On the other hand, the sensor nodes are subject to unpredictable node flaw, for example, deployment in a hostile environment. The main idea of TC techniques is to regulate nodes’ transmission power to achieve several purpose such as reducing interference, reducing energy consumption, and increasing network. Transmission power control has very crucial effects on throughput and energy-efficiency of WSNs. A convenient transmission power for a node transmitting a packet to its neighboring node can save battery power, at the same time, the traffic carrying capacity of network can be upgraded if every node can adjust its transmission power to appropriate level when it is transmitting the relevant information. Topology control has three phases: sensor deployment, topology construction, and topology maintenance. First, the sensor deployment phase is common to all WSN applications. After this initialization phase, the second phase is to build a new unique topology, called the topology construction phase. In this phase, a new topology is constructed while preserving connectivity. The main goal of the topology construction phase is to construct a topology that saves energy and retain network connection. Soon after the topology construction phase the topology maintenance phase must begin. During this phase, nodes updates topology status and provoke a new topology construction phase. Over a network’s lifetime, this cycle continues until node energy is drained. 2. LITERATURE REVIEW 1. Paper [1] proposes a distributed protocol called COMPOW, in which the minimum common transmitting range is adopted for network connectivity .From the result analysis its evident that the value of transmitting range has the valuable effects, of reducing the controversy to access the wireless channel, maximizing network capacity and minimizing the energy consumption for wireless sensor network. 2. As in paper [2] an Optimal Geographical Density Control (OGDC) algorithm is proposed which addresses both connectivity and sensing coverage in wireless sensor networks. The intention of the algorithm is to compute the minimum number of nodes that must be kept awake such that both sensing coverage and connectivity are preserved. The algorithm is decentralized but demands the network to be sufficiently dense to assure connectivity. 3. In [3], the authors introduce a distributed algorithm called Local Minimum Spanning Tree (LMST) for topology control based on the construction of spanning trees by adjusting the transmission range . Each node runs an algorithm to build a spanning tree and control the transmission power to get the one hop nodes in the tree. The major drawback of LMST is that it needs the development of a spanning tree for each node, which urges a large overhead. 4. In [4], the authors found out that the average range calculated by using a variable transmission range is half than when using the common transmission range. The network capacity does not depend on the number of nodes in the network, so the density of the network does not affect the network capacity, unlike the case of the common transmission range.
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  International Journal ofResearch in Advent Technology, Vol.2, No.8, August 2014 E-ISSN: 2321-9637 37 5. Moscibroda et al. [5] studied the drawback of traditional network models and resolved the impact of topology control on link scheduling based on a physical.Signal-to-Interference-plus-Noise-Ratio (SINR) model. In contradiction to the deterministic graph models, a network model that is convenient for lossy WSNs has been proposed. 6. Burri et al.[6] introduced a data-gathering protocol Dozer, that united considers topology control, medium access control (MAC) layer, and routing to save energy. Dozer utilize a tree-based network structure so as to coordinate the nodes sleeping schedules, to route the data, and achieves low radio duty cycles.. A simple network topology is proposed to estimate network lifetime and energy consumption. 7. The enormous majority of the topology control results is been evaluated in various literatures. It is challenging to assess the real feasibility of clarification to real network scenarios, where many of the hypothesis made during the analysis may not hold true any longer. Even though much work has been done on the implementation of real-life test bed for WSNs, out of that hardly few papers have appeared on experimental studies of power control and topology solutions for sensor networks, with the prominent omissions provided by [7] and [8]. 8. A distributed energy-efficient topology control (DETC) algorithm for home machine-to-machine (M2M) networks was has been established by the authors’in [9]. The DETC algorithm can execute only in home M2M networks. In this system, nodes create and maintain energy- efficient links autonomously and accomplish pro- longed lifetime with weaken energy cost. 9. Ding et al.[10] enforced an adaptive partitioning scheme for node scheduling and topology control in sensor networks with the objective of reducing energy consumption. The connectivity-based partition scheme (CPA) divides nodes based on their measured connectivity instead of assuming connectivity based on their positions. This scheme guarantees connectivity for the backbone network. 10. In [11], a node placement algorithm was proposed for a linear network topology. The proposed node placement algorithm recognize the number of forwarding message of each sensor and tries to balance the energy consumption of all sensor nodes. The research mainly focused on linear network topology and did not consider the two dimensional network topology. Even more, the developed deployment algorithm cannot balance the energy consumption for a randomly deployed WSN. 11.As in [12] & [13] proposed the first approximate algorithms to estimate a virtual backbone using a Connected Dominating Set(CDS).The most popular method for energy-efficient(TC) in WSNs is the CDS based topology control(TC).TC has two phases specifically: topology construction and topology maintenance. In the topology construction phase, a desirable topological property is settled in the network while providing connectivity. Once the topology is constructed, topology maintenance phase begins in which nodes switch. In the reduced constructed topology CDS works as a virtual backbone. 3. CONCLUSION In this paper, an extensive study on topology control issues in WSNs has been discussed. In this survey, reviewed the basic rules of topology control to realize the state of the arts. Different algorithms have been devised by many authors each of those tend to maintain energy efficient routing. ACKNOWLEDGEMENT I would like to thank the almighty for giving me the strength to work on this subject and t hereby coming up with this review paper. I am grateful to my guide and family members for supporting me and praying for me. I would like to express my gratitude towards the professors of Mar Baselios College of Engineering and Technology for their valuable guidance throughout. 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  International Journal ofResearch in Advent Technology, Vol.2, No.8, August 2014 E-ISSN: 2321-9637 38 synchronization and topology control for in-building sensor network applications, in: Proceedings of the 2nd ACM Int. Workshop on Wireless Sensor Networks and Applications, WSNA, 2003, pp. 38_49 [8] S. Lin, J. Zhang, G. Zhou, L. Gu, J. Stankovic, T. He, ATPC: Adaptive transmission power control for wireless sensor networks, in: Proceedings of the 4th ACM Int. Conference On Embedded Networked Sensor Systems, SenSys, 2006, pp. 223_236 [9] Lee C-Y, Yang Chu-Sing. Distributed energy-efficient topology control algorithm in home M2M networks. International Journal of Distributed Sensor Networks 2012:8. [10] Ding Y, Wang C, Xiao Li. An adaptive partitioning scheme for sleep scheduling and topology control in wireless sensor networks. IEEE Transactions on Parallel and DistributedSystems 2009;20(9):1352–65. [11] P. Cheng, C.N. Chuah, X. Liu, Energy-aware node placement in wireless sensor networks, in: Proceedings of IEEE Global Telecommunications Conference(GLOBECOM), November 2004, pp.3210–3214. [12] Ephremides A, Wieselthier J, Baker D. “A design concept for reliable mobile radio networks with frequency hopping signaling”. Proceedings of IEEE 1987;75(1):56–73. [13] Guha S, Khuller S. “Approximation algorithms for connected dominating sets” 1998;20(April):374–87.