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A Novel Load Balancing Scheduling Algorithm for Wireless Sensor Networks
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DOI：10.1007/s10922-018-9473-0.png)
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摘要
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Clustering is a well-known approach to cope with large nodes density and efficiently conserving energy in wireless sensor networks (WSN). Load balancing is an effective approach for optimizing resources like channel bandwidth, the main objective of this paper is to combine these two valuable approaches in order to significantly improve the main WSN service such as information routing. So, our proposal is a routing protocol in which load traffic is shared among cluster members in order to reduce the dropping probability due to queue overflow at some nodes. To this end, a novel hierarchical approach, called Distributed Energy efficient Adaptive Clustering Protocol (DEACP) with data gathering and Load-balancing is proposed. The DEACP approach aims to fulfill the following purposes: decreasing the overall network energy consumption, balancing the energy dissipation among the sensor nodes and as direct consequence: extending the lifetime of the network. In fact, the cluster-heads are optimally determined and suitably distributed over the area of interest allowing the member nodes reaching them with adequate energy dissipation and appropriate load balancing utilization. In addition, nodes radio are turned off for fixed time duration according to sleeping control rules optimizing so their energy consumption. The performance evaluation of the proposed protocol is carried out through the well-known NS2 simulator and the exhibited results are convincing. Like this, the residual energy of sensor nodes was measured every 20s throughout the duration of simulation, in order to calculate the total number of alive nodes. Based on the simulation results, we concluded that our proposed DEACP protocol increases the profit of energy, and prolongs the network lifetime duration from 32 to 40% compared to DEEAC reference protocol and from 25 to 28% compared to FEMCHRP protocol. The authors also note that the proposed protocol is 41.7% better than DEEAC with respect to fist node die, and 25.5% better than FEMCHRP with respect to last node die while maintaining the average data transmission delay. We found also that DEACP achieved 66.5% and 40.6% more rounds than DEEAC and FEMCHRP respectively.
Keyword:
Energy saving
Cluster-heads distribution
Load balancing
Life time duration
DEACP approach
NS2 simulator
Wireless sensor networks
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PROCEEDINGS OF THE IEEE
OAAI
PROCEEDINGS OF THE IEEEIF25.9
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OAAI
OAAI分享收藏An adaptive clustering approach to dynamic load balancing and energy efficiency in wireless sensor networksENERGY
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