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Grid scheduling is one of optimally assigning jobs to resources to achieve maximizing the utilization of resources. We propose a distributed ant colony algorithm based on cross-entropy for multi-constraints scheduling. This is an extremely robust rare event simulation technique which may be employed to solve difficult combinatorial optimization problems. We tailor the CE-ANT method for the requirements...
Grid scheduling is one of the most crucial issue in a grid environment because it strongly affects the performance of the whole system. Taking into account that the issue of allocating jobs on resources is a combinatorial optimization problem, a NP-complete problem, several heuristics have been proposed to provide good performance. In this paper, the proposed approach considers a stochastic optimization...
This paper studies the question of how to overcome inefficiencies due to hidden actions in a rational milieu, such as a grid computing system with open clientele. We consider the so-called principal-agent model known from economic theory, where the members (or agents) of a distributed system collaborate in complex ways. We adopt the perspective of the principal and investigate auditing mechanisms...
Replication in grid file systems can significantly improve I/O performance of data-intensive grid applications, but its manual creation and placement would be impractical in a real grid environment involving thousands to millions of files accessed per application. Although automatic determination of where and how many replicas should be created should be decided with regards to application access...
In grid environment, application systems are generally implemented by composition and cooperation of several grid services. In order to get an optimal service composition plan, appropriate services should be selected to satisfy end-to-end QoS requirements. QoS-aware service selection is a complex combinatorial optimization problem. According to the characteristic of grid services, this paper presents...
In grid system, many users compete for various type and amount of resources to complete user application or tasks, which requires grid resource management system to support co-allocation requests. Combinatorial auction has been argued as an effective economic mechanism to have advantages in resource trading and configuration. In order to allocate resources appropriately and reasonably, we propose...
Computational grid offers a great potential solution to parallel meta-heuristics toward combinatorial optimization. However, it is quite difficult for specialists in combinatorial optimization to develop parallel meta-heuristics in extremely heterogeneous computational environment, starting from scratch without any toolkit. This paper presents a problem solving environment for combinatorial optimization...
Solving exactly Combinatorial Optimization Problems (COPs) using a Branch-and-Bound algorithm requires a huge amount of computational resources. The efficiency of such algorithm can be improved by distributing at large scale the computation required by the exploration of the search tree. In this paper, we propose ParallelBB, which is a P2P-based parallelization of the Branch-and-Bound algorithm for...
Solving optimally large instances of combinatorial optimization problems requires a huge amount of computational resources. In this paper, we propose an adaptation of the parallel branch and bound algorithm for computational grids. Such gridification is based on new ways to efficiently deal with some crucial issues, mainly dynamic adaptive load balancing, fault tolerance, global information sharing...
Cellular network design is a major issue in mobile telecommunication systems. In this paper , a model of the problem in its full practical complexity, based on multiobjective constrained combinatorial optimization, has been investigated. We adopted the Pareto approach at resolution in order to compute a set of diversified non-dominated networks, thus removing the need for the designer to rank or weight...
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