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We present a general theoretical framework based on Markov random fields (MRF) for analysing the communication parameters of ad hoc and sensor networks. The applicability and adaptability of MRF's to this type of analysis is discussed. Simulation results based on alternative representations within the MRF framework are also presented.
Grid scheduling is a key problem for grid to improve the resource management and application performance. It has been proven to be a NP-hard problem for the computation of optimal grid schedules, which is responsible to allocate resources to user jobs with the objective such as minimizing the completion time or cost. Therefore, it is more difficult for Grid scheduling system to cope with the dynamically...
In this paper, we present a new general framework allowing sensor networks design using random Markov fields (MRF) theory. We explain how the principles underlying MRF theory naturally fit design requirements in sensor networks in particular the need to rely on decentralised and distributed methods to solve global optimisation problems. We illustrate the potential of this new general concept with...
Simulated annealing (SA) is a general-purpose optimization technique widely used in various combinatorial optimization problems. However, the main drawback of this technique is a long computation time required to obtain a good quality of solution. Clusters have emerged as a feasible and popular platform for parallel computing in many applications. Computing nodes on many of the clusters available...
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