International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 124

M.Tech / M.E / PhD Thesis | Computer Science & Engineering | India | Volume 5 Issue 4, April 2016


Load Balanced Algorithm for Location Based Routing Around Dead Nodes in Wireless Sensor Networks

Battula Santhi Pavani


Abstract: Adaptive load balancing algorithm is a protocol for converge casting in wireless sensor networks. Converge casting is the process of collection of data information in the network towards the base station. ALBA-R features the cross-layer integration of geographic routing with contention-based MAC for, relay selection and load balancing (ALBA), as well as a mechanism to detect and route around dead node. ALBA and Rainbow (ALBA-R) together solve the problem of routing around a dead end without overhead-intensive techniques such as graph planarization and face routing. The protocol is localized and distributed, and adapts efficiently to varying traffic and node deployments. Through extensive ns2 based simulations, we show that ALBA-R significantly outperforms other converge casting protocols and solutions for dealing with dead nodes, especially in critical traffic conditions and low-density networks. Our results show that ALBA-R is an energy-efficient protocol that achieves remarkable performance in terms of packet delivery ratio and end-to-end latency in different scenarios, thus being suitable for real network deployments.


Keywords: Wireless sensor network, converge casting, geographic routing, graph planarization, face routing


Edition: Volume 5 Issue 4, April 2016,


Pages: 132 - 136


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How to Cite this Article?

Battula Santhi Pavani, "Load Balanced Algorithm for Location Based Routing Around Dead Nodes in Wireless Sensor Networks", International Journal of Science and Research (IJSR), Volume 5 Issue 4, April 2016, pp. 132-136, https://www.ijsr.net/get_abstract.php?paper_id=NOV162500

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