Abstract
Wireless sensor networks (WSNs) are an emerging technology for monitoring physical world. Different from the traditional wireless networks and ad hoc networks, the energy constraint of WSNs makes energy saving become the most important goal of various routing algorithms. For this purpose, a cluster based routing algorithm LEACH (low energy adaptive clustering hierarchy) has been proposed to organize a sensor network into a set of clusters so that the energy consumption can be evenly distributed among all the sensor nodes. Periodical cluster head voting in LEACH, however, consumes non-negligible energy and other resources. While another chain-based algorithm PEGASIS (power- efficient gathering in sensor information systems) can reduce such energy consumption, it causes a longer delay for data transmission. In this paper, we propose a routing algorithm called CCM (Chain-Cluster based Mixed routing), which makes full use of the advantages of LEACH and PEGASIS, and provide improved performance. It divides a WSN into a few chains and runs in two stages. In the first stage, sensor nodes in each chain transmit data to their own chain head node in parallel, using an improved chain routing protocol. In the second stage, all chain head nodes group as a cluster in a self- organized manner, where they transmit fused data to a voted cluster head using the cluster based routing. Experimental results demonstrate that our CCM algorithm outperforms both LEACH and PEGASIS in terms of the product of consumed energy and delay, weighting the overall performance of both energy consumption and transmission delay.
Original language | English |
---|---|
Pages (from-to) | 1305-1313 |
Number of pages | 9 |
Journal | Journal of Intelligent Manufacturing |
Volume | 23 |
Issue number | 4 |
DOIs | |
Publication status | Published - 1 Aug 2012 |
Externally published | Yes |
Keywords
- Chain based routing
- Cluster based routing
- Mobile and ubiquitous computing
- Wireless sensor network
ASJC Scopus subject areas
- Software
- Industrial and Manufacturing Engineering
- Artificial Intelligence