Clustering in Wireless Sensor Networks

Author(s):  
Enamul Haque ◽  
Norihiko Yoshida

Applications of Wireless Sensor Networks (WSN) have been expanded from industrial operation to daily common use. With the pace of development, a good number of state-of-the-art routing protocols have been proposed for WSN. Among many of these protocols, hierarchical or cluster-based protocol technique is adopted from the wired network because of its scalability, better manageability, and implicit energy efficiency. In this chapter, the authors have surveyed Low Energy Adaptive Clustering Hierarchy, Power-Efficient Gathering in Sensor Information Systems, Adaptive Periodic Threshold-Sensitive Energy Efficient Sensor Network, and Hybrid Energy-Efficient Distributed Routing Protocols. These protocols exhibit notable characteristics and advantages compared to their contemporaries. Again, context aware computing and applications have been greatly emphasized in recent articles by renowned technologists. This approach is considered as a momentous technology that will change the way of interaction with information devices. Accordingly, context aware clustering technique carries a great deal of importance among WSN routing protocols. Therefore, the authors have investigated noteworthy context aware routing protocols such as: Context Adaptive Clustering, Data-Aware Clustering Hierarchy, Context-Aware Clustering Hierarchy, and Context-Aware Multilayer Hierarchical Protocol. Their investigation and analysis of these protocols has been included in this chapter with useful remarks. Context awareness is considered an integral part of Body Sensor Networks (BSN), which is one kind of WSN. Thus, the authors have also discussed issues related to context aware techniques used in BSN.

Author(s):  
A. Radhika ◽  
D. Haritha

Wireless Sensor Networks, have witnessed significant amount of improvement in research across various areas like Routing, Security, Localization, Deployment and above all Energy Efficiency. Congestion is a problem of  importance in resource constrained Wireless Sensor Networks, especially for large networks, where the traffic loads exceed the available capacity of the resources . Sensor nodes are prone to failure and the misbehaviour of these faulty nodes creates further congestion. The resulting effect is a degradation in network performance, additional computation and increased energy consumption, which in turn decreases network lifetime. Hence, the data packet routing algorithm should consider congestion as one of the parameters, in addition to the role of the faulty nodes and not merely energy efficient protocols .Nowadays, the main central point of attraction is the concept of Swarm Intelligence based techniques integration in WSN.  Swarm Intelligence based Computational Swarm Intelligence Techniques have improvised WSN in terms of efficiency, Performance, robustness and scalability. The main objective of this research paper is to propose congestion aware , energy efficient, routing approach that utilizes Ant Colony Optimization, in which faulty nodes are isolated by means of the concept of trust further we compare the performance of various existing routing protocols like AODV, DSDV and DSR routing protocols, ACO Based Routing Protocol  with Trust Based Congestion aware ACO Based Routing in terms of End to End Delay, Packet Delivery Rate, Routing Overhead, Throughput and Energy Efficiency. Simulation based results and data analysis shows that overall TBC-ACO is 150% more efficient in terms of overall performance as compared to other existing routing protocols for Wireless Sensor Networks.


2010 ◽  
Vol 34-35 ◽  
pp. 1019-1023
Author(s):  
Zhao Feng Yang ◽  
Ai Wan Fan

Wireless sensor networks consist of hundreds or thousands of sensor nodes that involve numerous restrictions including computation capability and battery capacity. In this paper we propose an optimal algorithm with genetic algorithm taken into consideration, and compare it with three well known and widely used approaches, i.e., LEACH and LEACH-C, in performance evaluation. Experimental results show that the proposed approach increases the overall network lifetime, and data delivery at the base station than the other routing protocols. Key words: Wireless sensor networks, base station, heuristic optimized genetic algorithm, low energy adaptive clustering hierarchy


In Wireless Sensor Networks (WSNs) lifetime of the system relies upon the vitality of the hubs, where vitality utilization is for the most part utilized for information transmission as opposed to detecting and preparing. A critical test in remote sensor systems is the ideal utilization of hub assets. Bunching of sensor hubs helps to utilize the hub vitality ideally and delay the lifetime of vitality compelled remote sensor arrange. Also, in WSN, the decision of steering convention assumes a significant job in using the vitality of hubs effectively. In this paper, another A2S LEACH (Active ↔Sleep - Low Energy Adaptive Clustering Hierarchy) directing strategy is proposed, which joins the two significant classes of various leveled conventions in particular bunch based methodology and chain based methodology. The proposed system is reproduced utilizing NS2 and the outcomes are examined. Reenactment results shows that the proposed A2S LEACH steering convention altogether diminishes vitality utilization and expands the all-out lifetime of the remote sensor organize when contrasted with the LEACH convention.


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