Abstract
The GA(genetic algorithms) was applied to find routing trees with minimal maximal sensor load thus extend network lifetime in wireless sensor networks. However, the existing algorithmlimits search space of GA to avoid generating cycles by dividing sensors into layers and stipulating that a sensor only can select a sensor in its lower layer as its new parent. In this paper, we have found that how cycles are generated during GA operations, and proposed a solution based on subtree to avoid generating cycles during GA operations.The solution only requires a sensor not to change its parent to a sensor in the subtree with it as the root. And layers are no longer considered. As a result, GA has more search space and GA operations can be performed more freely. Thus more optimal routing trees are obtained and network lifetime is extended. The experiment shows that our proposed algorithm extend network lifetime notably.
Highlights
Wireless sensor networks have gradually become a key technique that is widely used in military, environmental protection, industry, agriculture, space exploration, and transportation, etc. [1,2,3,4,5,6,7,8,9]
Many routing algorithms have been researched to prolong network lifetime by improving energy efficiency
We have found that cycles are generated during GA operation because a sensor selects a sensor in the subtree with it as the root as its new parent
Summary
Wireless sensor networks have gradually become a key technique that is widely used in military, environmental protection, industry, agriculture, space exploration, and transportation, etc. [1,2,3,4,5,6,7,8,9]. Many routing algorithms have been researched to prolong network lifetime by improving energy efficiency. Some dynamic routing algorithms require all sensors periodically inform their current residual energy to the sink. Proposed static routing algorithms aim at constructing an optimal routing tree to improve energy efficiency. With Power Efficient Data Gathering and Aggregation Protocol (PEDAP), a routing tree is constructed based on Minimum Spanning Tree (MST) [18] Another routing algorithm, Least Energy Tree (LET) was proposed in [14]. GA operations are only implemented between adjacent layers, i.e. a sensor only can select its new parent in its lower layer [9] This limits search space of GA and the performance of the algorithm. The structure of the remainder of the paper is as follows: Related studies of routing algorithms are described in Section 2; in Section 3, the model of our work is presented; in Section 4, we describe the proposed algorithm in detail; in Section 5, we provide and analyze experimental results; in Section 6, we have concluded this paper
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