当前位置: X-MOL 学术J. Parallel Distrib. Comput. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Artificial intelligence inspired energy and spectrum aware cluster based routing protocol for cognitive radio sensor networks
Journal of Parallel and Distributed Computing ( IF 3.4 ) Pub Date : 2020-04-24 , DOI: 10.1016/j.jpdc.2020.04.007
Thompson Stephan , Fadi Al-Turjman , K. Suresh Joseph , Balamurugan Balusamy , Sweta Srivastava

A Cognitive Radio Sensor Network (CRSN) is a distributed network of sensor nodes, which senses event signals and collaboratively communicates over dynamically available spectrum bands in a multi-hop mode. All nodes participating in CRSN have to be cognitive of the network environment and autonomous in decision making for resolving issues related to throughput maximization, delay, and energy minimization. Clustering in CRSN is proven to tackle such issues and enlarges the network’s lifetime. However, the existing clustering algorithms designed for WSNs do not consider the CR functionalities and challenges, and CR based networks work on the assumption of unlimited energy. This paper proposes an energy and spectrum aware unequal cluster based routing (ESUCR) protocol intending to resolve the issues of clustering and routing in CRSN. In ESUCR, cluster formation is mainly performed considering the residual energy of the secondary users (SUs) and relative spectrum awareness such that the common data channels for clusters are selected based on the appearance probability of PUs. ESUCR performs energy-efficient channel sensing by deciding the channel state with the statistic previous channel states. The premature death of cluster heads (CHs) is minimized by selecting and rotating the CHs based on intra-cluster channel stability, energy, distance, and neighbor connectivity. During event detection, ESUCR performs energy-efficient data routing towards the sink node by employing hop by hop forwarding through the CHs and primary/secondary gateways. The performance of the proposed ESUCR protocol is proved through extensive simulations and compared to those of the state-of-the-art protocols under a dynamic spectrum-aware data transmission environment.



中文翻译:

人工智能启发了基于能量和频谱感知簇的认知无线电传感器网络路由协议

认知无线电传感器网络(CRSN)是传感器节点的分布式网络,它可以感知事件信号,并以多跳模式在动态可用频谱带上进行协作通信。参与CRSN的所有节点必须对网络环境具有认知能力,并在决策中具有自主权,以解决与吞吐量最大化,延迟和能量最小化相关的问题。实践证明,CRSN中的群集可以解决此类问题并延长网络的使用寿命。然而,现有的为WSN设计的聚类算法没有考虑CR的功能和挑战,基于CR的网络是在无限能量的假设下工作的。本文提出了一种能量和频谱感知的基于不等分簇的路由协议(ESUCR),旨在解决CRSN中的分簇和路由问题。在ESUCR中,群集的形成主要是考虑到辅助用户(SU)的剩余能量和相对频谱感知,从而基于PU的出现概率选择群集的公共数据通道。ESUCR通过使用统计的先前信道状态确定信道状态来执行节能信道检测。通过根据群集内通道的稳定性,能量,距离和邻居连接性来选择和旋转CH,可以最大程度地减少簇头(CH)的过早死亡。在事件检测期间,ESUCR通过在CH和主要/辅助网关之间逐跳转发,实现了向宿节点的节能数据路由。

更新日期:2020-04-24
down
wechat
bug