z-logo
open-access-imgOpen Access
Multi-Hop Data Communication Algorithm for Clustered Wireless Sensor Networks
Author(s) -
Dilip Kumar,
R. B. Patel
Publication year - 2011
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2011/984795
Subject(s) - computer science , wireless sensor network , cluster analysis , key distribution in wireless sensor networks , scalability , computer network , energy consumption , distributed computing , base station , brooks–iyengar algorithm , hop (telecommunications) , data aggregator , wireless , wireless network , telecommunications , ecology , database , machine learning , biology
Recently, continued advances in wireless communication technologies have enabled the deployment of large-scale wireless sensor networks (WSNs). A key concern in the design and development of such WSNs is energy consumption. The hierarchical clustering algorithm is a kind of a technique which is used to reduce energy consumption. It can also increase the scalability, stability, and network lifetime. In some clustering schemes, the communication between a sensor node and its designated cluster head (CH) is assumed to be single-hop. However, multihop communication is often required when the communication range of the sensor nodes is limited or the number of sensor nodes is very large in a network. In this paper, we propose a distributed, randomized, multi-hop clustering algorithm to organize the sensor nodes in a WSN into clusters. The data collected by each sensor node communicate with their respective CHs by using multi-hop communication. The selected CHs collect data from member nodes in their respective clusters, aggregate the data, and send it to a base using multi-hop communication. Simulation results show that proposed algorithm efficiently mitigates the hot spot problem in heterogeneous WSN and achieves much improvement in network lifetime and load balance compared to the existing algorithms.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom