EAGER: Optimization in Wireless Mobile and Sensor Networks: A Novel Paradigm Based on Differential Evolution
EAGER: Optimization in Wireless Mobile and Sensor Networks: A Novel Paradigm Based on Differential Evolution
批准号:
1049427
负责人:
Uday Chakraborty
金额:
$12.11万
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
项目状态:
已结题
起止时间:
2010-09-01 至 2012-08-31
中文摘要
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英文摘要
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.
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会议论文
RI: Small: Model-Directed Hybridization: Principled Design of Hybrids of Model Building, Metaheuristics and More Traditional Optimization Techniques
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批准号:1115352
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项目类别:Standard Grant
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资助金额:$44.6万
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财政年份:2011
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负责人:Uday Chakraborty
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依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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批准号:--
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项目类别:合作创新研究团队
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资助金额:--
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批准年份:2024
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负责人:姚韬
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依托单位:
供应链管理中的稳健型(Robust)策略分析和稳健型优化(Robust Optimization )方法研究
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批准号:70601028
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项目类别:青年科学基金项目
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资助金额:7.0万元
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批准年份:2006
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负责人:王明征
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依托单位: