An optimal mobile agent moving policy for a mobile agent network where a single mobile agent moves and collects management information, is studied. The network has one management station that maintains many network el...
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ISBN:
(纸本)9780889867048
An optimal mobile agent moving policy for a mobile agent network where a single mobile agent moves and collects management information, is studied. The network has one management station that maintains many network elements each of which generates the management information (e.g., the updated state of the element). We formulate this network model as a semi-Markov decision process (SMDP) and compute an optimal policy with a policy iteration algorithm. It is shown that an optimal mobile agent moving policy achieved by the policy iteration algorithm has a cost reduction effect for the network in comparison to a heuristic policy.
parallel algorithm of time-independent Monte Carlo transport problem is successful because particles are typically independent and easily distributed to multiple processors. However, for time-dependent Monte Carlo tra...
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ISBN:
(纸本)0889865701
parallel algorithm of time-independent Monte Carlo transport problem is successful because particles are typically independent and easily distributed to multiple processors. However, for time-dependent Monte Carlo transport problem, due to the communication of each time-step about scattering source attribute and meshes, it reduces the parallel efficiency and limits enlarge of parallel scale. We research two algorithms. Where adaptive processor assignment and the optimized processor choice are obtained. We propose a scheme that is based upon Monte Carlo stratified sampling technique for treatment of scattering source communication. It greatly reduces the communication cost. The parallel scalability is obviously improved. The larger speedup over the basic algorithm is obtained.
A computational grid is a widespread computing environment that provides huge computational power for large-scale distributed applications. One of the most important issues in such an environment is resource managemen...
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ISBN:
(纸本)0889865701
A computational grid is a widespread computing environment that provides huge computational power for large-scale distributed applications. One of the most important issues in such an environment is resource management for which agent-based approaches are appropriate. Load balancing as a part of resource management, has a considerable effect on performance. Ant colony is a metaheuristic that can be instrumental for grid load balancing. This paper presents an echo system of intelligent, autonomous and cooperative ants. The ants in this environment can procreate and also may commit suicide depending on existing conditions. A new concept called Ant level load balancing is presented for improving the performance of the mechanism. A performance evaluation model is derived. Theoretical analyses and simulation results indicate that this new mechanism surpasses its predecessor.
This paper presents a top-down Quality-of-Service (QoS) approach to design realtime Ethernet networks for automation systems based upon tree topologies. Therefore, the parallelism of switched unicast communication is ...
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ISBN:
(纸本)088986568X
This paper presents a top-down Quality-of-Service (QoS) approach to design realtime Ethernet networks for automation systems based upon tree topologies. Therefore, the parallelism of switched unicast communication is utilized by generating an off-line schedule, which considers each port of a switch as an exclusive networking resource. We point out that the schedule can be generated independently for each switch. Starting from a given network infrastructure and QoS-requests, we present a method consisting of attribution to identify routes, specification of conflicts inside the switches, and building of a conflict-multigraph for each switch. The schedule is realized using greedy edge-coloring of the graph together with optional edge pre-sorting and re-coloring after execution of the greedy-algorithm. The method is shown for a class of special cases with unitary packet-sizes and transmission of every request in each cycle-period. Finally, some first results of this method are presented.
The experimental researches of efficiency of coarse-grain parallel method of artificial neural networks training with static mapping onto processors of parallel computer are presented in this paper. The features of pa...
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The experimental researches of efficiency of coarse-grain parallel method of artificial neural networks training with static mapping onto processors of parallel computer are presented in this paper. The features of parallel algorithm implementation using C language and MPI library are described. The research of parallel method is carried out using analysis of its speed-up and efficiency.
In this paper we present a scalable parallel refinement algorithm for tetrahedral meshes which is based on a regular refinement strategy with closure tetrahedra. This algorithm works efficiently on distributed-memory ...
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In this paper we present a scalable parallel refinement algorithm for tetrahedral meshes which is based on a regular refinement strategy with closure tetrahedra. This algorithm works efficiently on distributed-memory machines. We focus on the parallel implementation of the boundary updates of each mesh partition. Additionally we show that it is sufficient to exchange only boundary edge information between neighboring mesh partitions to obtain a conforming distributed three-dimensional tetrahedral mesh. The algorithm is implemented using the padfem2 framework.
The past decade has witnessed a boost in the acceptance of Grid computing as an alternative to traditional supercomputing environments. The evolution of Computers, networks and the Internet has boosted the growth of G...
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ISBN:
(纸本)9780889867048
The past decade has witnessed a boost in the acceptance of Grid computing as an alternative to traditional supercomputing environments. The evolution of Computers, networks and the Internet has boosted the growth of Grid computing. However applications with fine grained jobs tend to be unfavorable for this environment. Further applications that possess jobs that are dependent upon each other need to be grouped together and represented in a coarse-grained manner to lower the overheads involved with fine grained jobs, and rescheduling of dependent jobs. Also, there is a need to impose ordering on resource selection based on their processing capabilities and dynamic bandwidth scenarios. Users with different priorities must be provided differentiated Network ToS to ensure high Success Rates of job completion. In this paper, we investigate a dependency based, Network Aware, dynamic job grouping scheduler, which provides Network ToS to Users based on their deadlines.
Grid computing can be defined as coordinated resource sharing and problem solving in dynamic, multi-institutional collaborations [1], As more Grids are deployed worldwide, the number of multi-institutional collaborati...
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ISBN:
(纸本)0889865701
Grid computing can be defined as coordinated resource sharing and problem solving in dynamic, multi-institutional collaborations [1], As more Grids are deployed worldwide, the number of multi-institutional collaborations is rapidly growing. However, for Grid computing to realize its full potential, it is expected that Grid participants are able to use one another resources. Resource negotiation (i.e. exchange or trading of resources between Grids) enables Grid participants to face an unstable request environment. The aim of this position paper is to present a survey of the current state and challenges of resource negotiation research, with a Machine Learning perspective. We support the view that negotiation and learning are intrinsically linked. In particular, we show the expected benefits of integrating Machine Learning techniques with resource negotiation.
Group mutual exclusion (GME) was first introduced by Joung [5] as a generalization of the n-process mutual exclusion problem, and subsequently modeled as the Congenial Talking Philosophers problem. GME allows processe...
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ISBN:
(纸本)9780889866386
Group mutual exclusion (GME) was first introduced by Joung [5] as a generalization of the n-process mutual exclusion problem, and subsequently modeled as the Congenial Talking Philosophers problem. GME allows processes requesting for the same resource to concurrently access the shared resource. However, a process requesting a resource that is different from the one currently being used will not be able to access the requested resource at the same time. Two solutions to the GME problem for a ring network exist. One by Wu and Joung had an unbounded message size problem [11, 12], the second one by Cantarell, et. al. provided a bound for message size, but could potentially generate an unbounded number of messages [2, 3]. This work presents a GME algorithm for a token-passing network that solves both problems by providing a bound both to the number of messages and to message size. Analysis results of time and message complexities and of correctness are presented. Performance is evaluated by simulation experiments, which further validate complexity analyses.
A distributor is a time-multiplexed switch that routes active input signals to output ports in the round-robin fashion. This paper presents the Merge-Distribute algorithm for the recursive construction of distributors...
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A distributor is a time-multiplexed switch that routes active input signals to output ports in the round-robin fashion. This paper presents the Merge-Distribute algorithm for the recursive construction of distributors in the form of paralleldistributed-control networks, as analogous to the recursive construction of sorting networks by the Mergesort algorithm. The Merge-Distribute algorithm achieves the best known depths for distribution networks of all sizes within the practical range. The rigorous algebraic formulation AMkeeps the algorithmic construction transparent and affords many variations in the construction so as to flexibly cope with ad hoc engineering constraints in implementation.
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