چکیده مقاله
Wireless sensor networks WSNs are currently adopted in a vast variety of domains where sensor energy consumption is a critical challenge because of the existing power constraints Sleep scheduling approaches have recently attracted the interest of the scientific community, as they give the opportunity of turning off the redundant nodes of a network to save energy and prolong the lifetime of the network without suspending the monitoring activities performed by the WSN Our study focuses on the problem of partial coverage, targeting scenarios in which the continuous monitoring of a limited portion of the area of interest is enough In this paper we present PCLA, a novel algorithm that relies on Learning Automata to implement sleep scheduling approaches It aims at minimizing the number of sensors to activate for covering a desired portion of the region of interest preserving the connectivity among sensors Simulation results show how PCLA can select sensors in an efficient way to satisfy the imposed constraints, thus guaranteeing good performance in terms of time complexity, working node ratio, scalability, and WSN lifetime Moreover, compared to the state of the art, PCLA is able to guarantee better performance
نویسندگان
Mahsa Abassi
مقاله A sleep scheduling approach based on learning automata for WSN partial coverage
شیوه ارجاع
Abassi, Mahsa,1398,A sleep scheduling approach based on learning automata for WSN partial coverage,The 6th National Conference on Computer Science and Engineering and Information Technology - January 2019,Babol
ارائهشده در
مجموعه مقالات ششمین کنفرانس ملی علوم و مهندسی کامپیوتر و فناوری اطلاعات29 فروردین 1398 · بابل