ILSM:Incorporated Lightweight Security Model for Improving QOS in WSN  

作　　者：Ansar Munir Shah Mohammed Aljubayri Muhammad Faheem Khan Jarallah Alqahtani Mahmood ul Hassan Adel Sulaiman Asadullah Shaikh 

机构地区：[1]Insitute of Southern Punjab,Multan,Pakistan [2]College of Computer Science and Information Systems,Najran University,Najran,Saudi Arabia [3]Department of Computer Skills,Deanship of Preparatory Year,Najran University,Najran,Saudi Arabia

出　　处：《Computer Systems Science & Engineering》2023年第8期2471-2488,共18页计算机系统科学与工程（英文）

基　　金：The authors are thankful to the Deanship of Scientific Research at Najran University for funding this work under the Research Collaboration Funding program grant code NU/RC/SERC/11/7。

摘　　要：In the network field,Wireless Sensor Networks(WSN)contain prolonged attention due to afresh augmentations.Industries like health care,traffic,defense,and many more systems espoused the WSN.These networks contain tiny sensor nodes containing embedded processors,TinyOS,memory,and power source.Sensor nodes are responsible for forwarding the data packets.To manage all these components,there is a need to select appropriate parameters which control the quality of service of WSN.Multiple sensor nodes are involved in transmitting vital information,and there is a need for secure and efficient routing to reach the quality of service.But due to the high cost of the network,WSN components have limited resources to manage the network.There is a need to design a lightweight solution that ensures the quality of service in WSN.In this given manner,this study provides the quality of services in a wireless sensor network with a security mechanism.An incorporated hybrid lightweight security model is designed in which random waypoint mobility(RWM)model and grey wolf optimization(GWO)is used to enhance service quality and maintain security with efficient routing.MATLAB version 16 andNetwork Stimulator 2.35(NS2.35)are used in this research to evaluate the results.The overall cost factor is reduced at 60%without the optimization technique and 90.90%reduced by using the optimization technique,which is assessed by calculating the signal-to-noise ratio,overall energy nodes,and communication overhead.

关 键 词：Wireless sensor networks quality of service random waypoint mobility model grey wolf optimization security 

分 类 号：TN92[电子电信—通信与信息系统]