Abstract
The most important issue that must be solved in designing a data gathering algorithm for wireless sensor networks (WSNS) is how to save sensor node energy while meeting the needs of applications/users. In this paper, we propose a novel energy-aware routing protocol (EAP) for a long-lived sensor network. EAP achieves a good performance in terms of lifetime by minimizing energy consumption for in-network communications and balancing the energy load among all the nodes. EAP introduces a new clustering parameter for cluster head election, which can better handle the heterogeneous energy capacities. Furthermore, it also introduces a simple but efficient approach, namely, intra-cluster coverage to cope with the area coverage problem. We use a simple temperature sensing application to evaluate the performance of EAP and results show that our protocol significantly outperforms LEACH and HEED in terms of network lifetime and the amount of data gathered.
Highlights
With the advances in micro-electro-mechanical system technologies, embedding system technology and wireless communication with low power consumption, it is possible to produce micro wireless sensors for sensing, wireless communication and information processing
We propose a distributed and energyefficient protocol, called energy-aware routing protocol (EAP) for data gathering in wireless sensor networks
We present EAP, a novel energy efficient data gathering protocol with intra-cluster coverage
Summary
With the advances in micro-electro-mechanical system technologies, embedding system technology and wireless communication with low power consumption, it is possible to produce micro wireless sensors for sensing, wireless communication and information processing. These inexpensive and power-efficient sensor nodes work together to form a network for monitoring the target region. Each sensor node is usually powered by a battery and expected to work for several months to one year without recharging Such an expectation cannot be achieved without carefully scheduling the energy utilization, especially when sensors are densely deployed (up to 20 nodes/m3 [1]), which causes severe problems such as scalability, redundancy, and radio channel contention.
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