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Performance optimization of a de-centralized task allocation protocol via bandwidth and buffer management
By: Hong, B.; Prasanna, V.K.;
2004 / IEEE / 0-7695-2115-0
This item was taken from the IEEE Conference ' Performance optimization of a de-centralized task allocation protocol via bandwidth and buffer management ' Sharing the resources among various users and the lack of a centralized control are two key characteristics of many distributed heterogeneous computing systems. A critical challenge for designing applications in such systems is to coordinate the resources in a decentralized fashion while adapting to the changes in the system. In this paper, we consider the computation of a large set of equal-sized independent tasks. This represents the computation paradigm for a variety of large scale applications such as SETI@home and Monte Carlo simulations. We focus on the performance optimization for a decentralized adaptive task allocation protocol. We develop a bandwidth allocation strategy based on our decentralized task allocation algorithm, and a simple task buffer management policy. Simulation results show that our task allocation protocol achieves close to the optimal system throughput.
Bandwidth Allocation Strategy
Decentralized Task Allocation Protocol
Distributed Heterogeneous Computing System
Monte Carlo Simulations
Signal Processing Algorithms
Data Flow Computing