A Multi-Objective Crowding Optimization Solution for Efficient Sensing as a Service in Virtualized Wireless Sensor Networks

被引:7
|
作者
Othman, Ramy A. [1 ]
Darwish, Saad M. [2 ]
Abd El-Moghith, Ibrahim A. [3 ]
机构
[1] World Trans Grp, Alexandria 5423002, Egypt
[2] Alexandria Univ, Inst Grad Studies & Res, Dept Informat Technol, Alexandria 21544, Egypt
[3] Almotaheda Co Construct & Paving Rd, Alexandria 5432078, Egypt
关键词
fault tolerance; virtualization; internet-of-things; multi-objective optimization; evolutionary crowding algorithm; RESOURCE-ALLOCATION ALGORITHM; IOT; MODEL;
D O I
10.3390/math11051128
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The Internet of Things (IoT) encompasses a wide range of applications and service domains, from smart cities, autonomous vehicles, surveillance, medical devices, to crop control. Virtualization in wireless sensor networks (WSNs) is widely regarded as the most revolutionary technological technique used in these areas. Due to node failure or communication latency and the regular identification of nodes in WSNs, virtualization in WSNs presents additional hurdles. Previous research on virtual WSNs has focused on issues such as resource maximization, node failure, and link-failure-based survivability, but has neglected to account for the impact of communication latency. Communication connection latency in WSNs has an effect on various virtual networks providing IoT services. There is a lack of research in this field at the present time. In this study, we utilize the Evolutionary Multi-Objective Crowding Algorithm (EMOCA) to maximize fault tolerance and minimize communication delay for virtual network embedding in WSN environments for service-oriented applications focusing on heterogeneous virtual networks in the IoT. Unlike the current wireless virtualization approach, which uses the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), EMOCA uses both domination and diversity criteria in the evolving population for optimization problems. The analysis of the results demonstrates that the proposed framework successfully optimizes fault tolerance and communication delay for virtualization in WSNs.
引用
收藏
页数:23
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