An Energy Balancing Routing Algorithm for Mobile Sensor Networks

作者：Wu, Chunxue; Du, Junhui; Liu, Yi; Xiong, Naixue^*; Jeong, Kitae; Yang, Guisong; Gao, Liping

来源：Sensor Letters, 2013, 11(9): 1783-1791.

DOI：10.1166/sl.2013.3011

• Ant Colony Optimization (ACO)
• Internet of Things (IoT)
• Load Balance
• Low Energy Adaptive Clustering Hierarchy (LEACH)

Efficient use of the limited energy resources of wireless sensor networks (WSNs) nodes is critically important in WSNs, so designing energy efficient clustering protocols have a profound impact on networks' lifetime. Generally speaking, hierarchical clustering protocols, such as low energy adaptive clustering hierarchy (LEACH) protocol, are more efficient in energy conservation than flat routing protocols. However, the typical protocol still has drawbacks of unequal and high energy depletion in clusterheads due to the different transmission distance from each clusterhead to the sink node. Moreover, directed towards mobility of Internet of Things (IoT), involvement of multimedia and big data, the paper proposed a routing algorithm called energy balancing ant colony routing algorithm (EBACRA), aiming at load balance for mobile sensor networks, which selects clusterheads considering residual energy of nodes, density of neighbor nodes, distances to the sink node and the moving speeds. The algorithm also regards the residual energy of clusterheads and the distances to the sink node as the influence factors to shape the clusters so that the scales of clusters decrease with the decrease of distances to the sink node to conserve more energy near the sink node for transmitting data, and introduces ant colony optimization (ACO) to construct multi-hop mechanism among clusterheads to save energy. The simulation results show the proposed EBACRA is more energy-efficient than traditional LEACH protocol, prolonging the lifetime of networks.

• 出版日期2013-9
• 单位上海理工大学