arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1609.04069cs.NI
收藏

无线传感器网络多目标优化研究综述:模型、算法与开放问题

A Survey of Multi-Objective Optimization in Wireless Sensor Networks: Metrics, Algorithms and Open Problems

Zesong Fei, Bin Li, Shaoshi Yang, Chengwen Xing, Hongbin Chen, Lajos Hanzo

摘要:

无线传感器网络(WSNs)吸引了大量的研究兴趣,特别是在执行监测和监视任务的背景下。然而,在各种相互冲突的优化标准(例如网络的能量消耗、分组丢失率、覆盖范围和生命周期)之间取得令人信服的权衡是具有挑战性的。本文提供了一个教程和调查最近的研究和开发工作,解决这个问题,使用多目标优化(MOO)的技术。首先,我们提供了一个概述,在无线传感器网络中使用的主要优化目标。然后,我们详细阐述了各种流行的方法,如家庭的数学规划为基础的标量化方法,家庭的优化算法,以及各种其他先进的优化技术。此外,我们总结了一系列最近的研究MOO在无线传感器网络的背景下,这是为了提供有用的指导方针,研究人员了解参考文献。最后,我们讨论了一系列开放的问题,以解决未来的研究。

英文摘要:

Wireless sensor networks (WSNs) have attracted substantial research interest, especially in the context of performing monitoring and surveillance tasks. However, it is challenging to strike compelling trade-offs amongst the various conflicting optimization criteria, such as the network's energy dissipation, packet-loss rate, coverage and lifetime. This paper provides a tutorial and survey of recent research and development efforts addressing this issue by using the technique of multi-objective optimization (MOO). First, we provide an overview of the main optimization objectives used in WSNs. Then, we elaborate on various prevalent approaches conceived for MOO, such as the family of mathematical programming based scalarization methods, the family of heuristics/metaheuristics based optimization algorithms, and a variety of other advanced optimization techniques. Furthermore, we summarize a range of recent studies of MOO in the context of WSNs, which are intended to provide useful guidelines for researchers to understand the referenced literature. Finally, we discuss a range of open problems to be tackled by future research.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑