EAGER: Optimization in Wireless Mobile and Sensor Networks: A Novel Paradigm Based on Differential Evolution

EAGER：无线移动和传感器网络的优化：基于差分进化的新范式

• 批准号: 1049427
• 负责人: Uday Chakraborty
• 金额: $ 12.11万
• 依托单位: University of Missouri-Saint Louis
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1049427&HistoricalAwards=false
• 关键词: EAGER; Optimization; Wireless; Mobile; Sensor

This EAGER proposal seeks to develop new, improved approaches, based on single- and multi-objective differential evolution, to the following important problems:(i) QoS-based multicast routing in mobile networks; (ii) Energy-efficient routing in hierarchical (two-tiered) wireless sensor networks; (iii) Stability-aware clustering in mobile ad hoc networks with special consideration of group mobility; and (iv) Cross-layer optimization in wireless sensor networks by joint routing and link scheduling in the presence of energy constraints, link interference and noise.The goal is to achieve higher energy saving, better network performance and extended network lifetimes.The novelty of this proposal is that it brings the power of differential evolution, a cutting-edge strategy in present-day computational intelligence research, to a group of outstanding, NP-hard problems in computer networks. It presents novel schemes for encoding of trial solutions and also for designing the differential operator for these problems. This research cuts across conventional subject lines ? it embodies an interdisciplinary and transformative application of ideas from electrical engineering, computer communications, computational intelligence, and statistical machine learning. This has the potential to open up a radically new direction in networking research.The broader impact of this research is far-reaching in this era of ubiquitous and pervasive computing. The efficiency, flexibility, and controllability provided in the proposed methods can be used to save costs and improve the quality of the final products in the industry. The proposal also includes well-thought out plans for integrating research and education. The PI will use this project to involve high-school students, women, and undergraduate/graduate students in computer science research.

该EAGER建议寻求开发新的、改进的方法，基于单目标和多目标差分进化，以解决以下重要问题：（i）移动的网络中基于QoS的多播路由;（ii）分层网络中的能量有效路由;（iii）分层网络中基于QoS的多播路由。（iii）移动的ad hoc网络中的稳定性感知分簇，特别考虑组移动性;以及（iv）在存在能量约束、链路干扰和噪声的情况下，通过联合路由和链路调度来实现无线传感器网络的跨层优化，目标是实现更高的能量节省，更好的网络性能和更长的网络寿命。该提案的新奇在于，它带来了差分进化的力量，差分进化是当今计算智能研究的前沿策略，一组突出的，NP-难的问题在计算机网络。它提出了新的方案，编码的审判解决方案，并为这些问题设计的微分算子。这项研究跨越了传统的主题？它体现了电气工程，计算机通信，计算智能和统计机器学习的跨学科和变革性应用。这有可能为网络研究开辟一个全新的方向，在这个无处不在和普及计算的时代，这一研究的广泛影响是深远的。所提出的方法提供的效率、灵活性和可控性可用于节省成本和提高工业中最终产品的质量。该提案还包括经过深思熟虑的整合研究和教育的计划。PI将利用这个项目让高中生、妇女和本科生/研究生参与计算机科学研究。