Abstract
Planning of energy-efficient protocols is critical for Wireless Sensor Networks (WSNs) because of the constraints on the sensor nodes' energy. The routing protocol should be able to provide uniform power dissipation during transmission to the sink node. In this paper, we present a self-optimization scheme for WSNs which is able to utilize and optimize the sensor nodes' resources, especially the batteries, to achieve balanced energy consumption across all sensor nodes. This method is based on the Ant Colony Optimization (ACO) metaheuristic which is adopted to enhance the paths with the best quality function. The assessment of this function depends on multi-criteria metrics such as the minimum residual battery power, hop count and average energy of both route and network. This method also distributes the traffic load of sensor nodes throughout the WSN leading to reduced energy usage, extended network life time and reduced packet loss. Simulation results show that our scheme performs much better than the Energy Efficient Ant-Based Routing (EEABR) in terms of energy consumption, balancing and efficiency.
Highlights
Even though Sensor Nodes (SNs) may link directly to the processing sinks through local area networks [1], extending these SNs to gather data and transmit them to a central sink is more useful because future applications may demand hundreds or thousands of SNs to be deployed, which are Sensors 2012, 12 often used in remote and inaccessible regions
The results and discussion were presented to validate the effectiveness of the SensorAnt comparing with Efficient Ant-Based Routing (EEABR) results; the results obtained from the QualNet simulator that offers high fidelity simulations for wireless communication
In this paper we described a method to optimize energy consumption in a wireless sensor network, considering that the energy of the sensor nodes is the most critical factor to prevent fast energy depletion
Summary
Even though Sensor Nodes (SNs) may link directly to the processing sinks through local area networks [1], extending these SNs to gather data and transmit them to a central sink is more useful because future applications may demand hundreds or thousands of SNs to be deployed, which are Sensors 2012, 12 often used in remote and inaccessible regions. The motivation of this study was to propose a decentralized energy balancing method that is generic and applicable to most of WSN applications that require reduction of energy consumption and this will extend a network’s life time This is achieved by considering the energy of the sensor nodes as the most critical factor to prevent fast energy depletion. Presenting a new hop function assessment based on multi-criteria metrics such as the minimum residual battery power, hop count and average energy of both route and network, to contribute to the path function choosing the optimal route to the destination We compared their performance and show that it gives a better performance compared with the Energy Efficient Ant-Based Routing algorithm (EEABR) [8].
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