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Sensor grid resource management: model and implementation issues.

Chunlin Li¹, LaYuan Li²

¹Department of Computer Science, Wuhan University of Technology, Wuhan 430063, PR China; State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China.

ISA Transactions

|June 8, 2014

Summary

This summary is machine-generated.

This study optimizes sensor grid resource management using nonlinear optimization. A novel pricing algorithm balances user quality of service (QoS) and system preferences for improved performance.

Keywords:

Grid computing Sensor grid Sensor network

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Area of Science:

Computer Science
Optimization Theory
Network Management

Background:

Sensor grids require efficient resource allocation to meet user demands.
Existing sensor management approaches may not adequately balance user Quality of Service (QoS) with system-wide optimization.
Constraints include sensor resources, energy consumption, and budget limitations.

Purpose of the Study:

To develop an optimal sensor resource management strategy for sensor grids.
To introduce a pricing-based algorithm that considers user preferences and QoS.
To enhance overall sensor system performance and efficiency.

Main Methods:

Formalization of the problem using nonlinear optimization theory.
Development of a pricing-based iterative algorithm for sensor management.
Incorporation of sensor resource constraints, energy, and expense budgets.
Simulation-based performance evaluation.

Main Results:

The proposed algorithm effectively balances user QoS requirements with system optimization goals.
The pricing-based approach demonstrates superior performance compared to previous methods.
Implementation considerations for sensor management are addressed.

Conclusions:

The developed nonlinear optimization framework provides an effective approach to sensor resource management.
The pricing-based iterative algorithm offers a practical solution for optimizing sensor grids.
The study highlights the benefits of user-centric optimization in sensor network management.