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Bimonthly Since 1986 |
ISSN 1004-9037
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Publication Details |
Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
Distributed by:
China: All Local Post Offices
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Abstract
Wireless Sensor Networks (WSN) have been used in a wide range of applications because of their salient characteristics. They have been deployed by various organizations to provide services to the users and customers. However, like any other networks, they have their own deficiency. The sensor nodes of WSN have been fabricated with the radio device which is capable of transmitting or receiving the radio signals within a specific range. This restricts the communication of sensor with the faraway node directly. In terms of data transmission, the source and destination would be located in different of geography. Still, to perform data transmission, they involve in cooperative transmission. Here, the energy of sensor nodes comes into play which is more essential resource for the sensor nodes. The sensor nodes come with limited power which get depleted at each data transmission. So, both energy and transmission range have great impact on the performance of WSN. This increases the need for performing cluster-based routing to maximize the lifetime of the network and improve the QoS performance. To handle this problem, a number of approaches are available in literature but they fail to achieve higher performance. For example, the hop count based approaches selects a route with least hop count but suffer to achieve higher performance due to the higher traffic present in the intermediate nodes. Similarly, the traffic-based approaches select the route based on the traffic with least traffic route. This introduces longer hop count and increases the latency which in turn affects the throughput performance. So, all the methods struggle to get the peak performance and suffer due to poor QoS performance. To handle these constraints, different approaches are presented in this research work.
Keyword
WSN, CH, CM, GW, REAS.
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