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Sensors: A Cross-Layer Approach for Energy Efficiency in Wireless Sensor Networks

Project: Research

Project Details

Description

Sensors: A Cross-Layer Approach for Energy Efficiency in Wireless Sensor Networks (Proposal ECS-0427345) Abstract This Sensor proposal focuses on developing a battery-aware and density-aware cross-layer mechanism with dynamic power management that provides a comprehensive solution to achieve high energy efficiency in sensor networks. This research includes following tasks: (1) develop battery-aware routing protocols to maximize battery lifetime of sensor nodes by considering mathematical battery models and collaborative nature of sensor nodes; (2) investigate promising, realistic approaches for more accurate traffic prediction on sensor nodes to reduce power consumption of sensor nodes while enabling them to function fully in sensing and routing activities; (3) design density-aware routing algorithms for sensor networks in a dynamic power management approach to reduce traffic redundancy and minimize power consumption of packet routing; (4) integrate the above approaches into a cross-layer mechanism that can globally optimize various power saving solutions to achieve high energy efficiency and low packet loss rate network-wide. The intrinsic merit of the research lies in development of viable solutions for cross-layer energy optimization for future generation sensor networks. The research will have a significant impact on fundamental design principles and infrastructures for the development of future sensor networks. The outcome of this project will be applicable to a wide spectrum of applications. The broader impact of the project will be evident through integrating graduate students into the project and disseminating important findings to the research community and by facilitating the partnership between industry and academia through New York State Center of Excellence in Wireless Networking and Information Technology and Center for Advanced Tec
StatusFinished
Effective start/end date09/1/0408/31/09

Funding

  • National Science Foundation: $250,000.00

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