دانلود رایگان مقاله انگلیسی انتخاب سنسور بر اساس منطق فازی و تعادل بار در شبکه های حسگر بی سیم چند سینک - اشپرینگر 2017

Abstract

Using multiple sink nodes in wireless sensor networks can greatly improve the lifetime and throughput of the network. One of the important issues in multi-sink wireless sensor networks is the congestion problem in sink nodes which reduces the effectiveness of data processing in sink nodes and increases the energy consumption of the sensor nodes. To prevent congestion in the sink nodes, in this paper, a distributed fuzzy logic-based sink selection algorithm is presented for one-hop sensor networks which makes each sensor node able to independently select a sink node based on the congestion situations in all the sink nodes. This scheme can effectively prevent congestion in the sink nodes and provide load balancing among them. Moreover, it reduces the delay of successful data transmissions to the sink nodes and improves the lifetime of wireless sensor networks by reducing the number of packet retransmissions. Simulation results indicate the effectiveness of our proposed solution.

6 Conclusion

The lifetime of the wireless sensor networks can be improved by multiple sink nodes deployment. Congestion is an important issue in multi-sink sensor networks which mitigates the effectiveness and lifetime of the network. Irregular and non-uniform distribution of the sensor nodes and unbalanced loads of the sink nodes are important factors which deteriorate the congestion situation in the sink nodes.

To mitigate the congestion problem in sink nodes and benefit from the multiple sink deployment, in this paper, a fuzzy logic-based sink selection algorithm is presented for one-hop wireless sensor networks. In the proposed distributed sink selection scheme, each sink node should declare its average load with a Hello message to the network. When a sensor node receives this message, it can recognize the congestion situation in the sink node and by using the Received Signal Strength of this message, it can determine its distance with the sink. Then this information along with remaining battery power are applied to a fuzzy inference system to select the nearest uncongested sink node. Extensive simulations indicate the effectiveness of the proposed solution in load balancing the sink nodes, reducing congestion in sink nodes, and mitigating the delay and energy consumption of data transmissions.

In the upcoming researches and studies, we will try to adapt our proposed fuzzy sink selection solution to the multi-hop wireless sensor networks with multiple mobile sink nodes.