In this paper we put forward a distributed model for accessing heterogeneous database systems. The processing of database operations requested by the user are processed in a distributed manner that takes advantage of ...
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ISBN:
(纸本)0780342291
In this paper we put forward a distributed model for accessing heterogeneous database systems. The processing of database operations requested by the user are processed in a distributed manner that takes advantage of the inherent parallelism of distributed systems, minimises network traffic and uses almost any general purpose computer on the network. processing is not confined to DBMS sites but is provided as a distributed service. The design is modular and provides the mechanisms that may be arranged in a variety of ways providing a range of integration paradigms from loosely coupled integrations to more tightly coupled integrations.
The computing resources offered by a collection of workstations can be enormous. To locate and utilize idle workstations efficiently has been a problem requiring much study. A process migration facility is one such me...
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ISBN:
(纸本)0818675578
The computing resources offered by a collection of workstations can be enormous. To locate and utilize idle workstations efficiently has been a problem requiring much study. A process migration facility is one such method aimed at better utilization of the vast computing potential that allows the user of a workstation to off-load programs onto idle workstations, thereby providing the user with access to computational resources far beyond that provided by his or her personal workstation. PMDOS: Process Migration on a network of DOS workstations -A distributedprocessing system comprising a checkpoint/restart mechanism and a process migration mechanism at user level was designed and implemented on a network of DOS machines (PC's) to create an environment wherein: temporarily unused workstations can be accessed by other users on the network to perform distributed or parallel computations or execute background or non-interactive jobs. An owner of a workstation need not be aware that the machine is being used during idle times;the machine is immediately returned when the owner begins to work again. The system gives good throughput, fault tolerance and efficiency for parallel and distributedapplications.
StarRules is a high-level programming language based on Event Calculus principles that was developed for processing large volumes of data. It is an integral part of a comprehensive platform that has been used for many...
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We propose a new consistency protocol named Pilgrim for distributed shared memory (DSM) where different shared objects are replicated at each site. This protocol provides both reliable consistency and guaranteed perfo...
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ISBN:
(纸本)0780342291
We propose a new consistency protocol named Pilgrim for distributed shared memory (DSM) where different shared objects are replicated at each site. This protocol provides both reliable consistency and guaranteed performance. This protocol is discussed and proved with a finite state automaton, and we demonstrate its qualities.
Many embedded and distributedapplications are based on processing nodes that perform parallelprocessing tasks. Unfortunately, it is difficult to evaluate the overall behaviour of this kind of applications because th...
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A distributed Computing System (DCS) contributes in proper partitioning of the tasks into modules and allocating them to various nodes so as to enable parallel execution of their modules by individual different proces...
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A distributed Computing System (DCS) contributes in proper partitioning of the tasks into modules and allocating them to various nodes so as to enable parallel execution of their modules by individual different processing nodes of the system. The scheduling of various modules on particular processing nodes may be preceded by appropriate allocation of modules of the different tasks to various processing nodes and then only the appropriate execution characteristic can be obtained. A number of algorithms have been proposed for allocation of tasks in a DCS. Most of the solutions proposed had simplifying assumptions. The very first assumption has been: consideration of a single task with their corresponding modules only;second, no consideration of the status of processing nodes in terms of the previously allocated modules of various tasks and third, the capacity and capability of the processing nodes. This work proposes algorithms for a realistic situation wherein multiple tasks with their modules compete for execution on a DCS dynamically considering their architectural capability. In this work, we propose two algorithms based on the two well-known A* and CA for the task allocation models. The paper explains the algorithms elaborately by illustrated examples and presents a comparative performance study among our algorithms and the algorithms for task allocation proposed in the various literatures. The results demonstrate that our CA based task allocation algorithm achieves better performance compared with the other algorithms.
Scheduling applications on multi-processor is an effective core technology in using distributed systems. Task scheduling is to map applications to parallel system in order to minimize the makespan. Task scheduling is ...
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ISBN:
(纸本)9781509063529
Scheduling applications on multi-processor is an effective core technology in using distributed systems. Task scheduling is to map applications to parallel system in order to minimize the makespan. Task scheduling is classified into static scheduling and dynamic scheduling. Most task scheduling is NP-complete problem. The authors come up with a new scheduling algorithm: Chunking Splicing Algorithm for a special type of DAG like the processing of PDSCH (Physical Downlink Shared Channel) in LTE. When mapping that special type of DAG (like signal processing of PDSCH), its performance is quite good comparing with traditional list scheduling algorithms: HLFET, ISH, ETF, DLS algorithm. Also the authors use some random DAGs to test the performance of our new algorithm.
An automated facilities management system is described which can help reduce high energy costs. In addition, the system can improve building security and help achieve maximum equipment life expectancy. distributed pro...
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An automated facilities management system is described which can help reduce high energy costs. In addition, the system can improve building security and help achieve maximum equipment life expectancy. distributedprocessing techniques make the system especially suitable for large multibuilding installations.
The proceedings contain 62 papers. The topics discussed include: adaptive routing for a bus-based multiprocessor;multi-node broadcasting in hypercubes and star graphs;calculating optimal flit size and upper limit on t...
ISBN:
(纸本)0780342291
The proceedings contain 62 papers. The topics discussed include: adaptive routing for a bus-based multiprocessor;multi-node broadcasting in hypercubes and star graphs;calculating optimal flit size and upper limit on the performance of wormhole routing;prioritized physical channel scheduling in wormhole networks;an object-oriented data cache architecture for programmable parallel digital signal processors;a systolic architecture for sorting an arbitrary number of elements;virtual parallel processors;parallel information retrieval on a distributed memory multiprocessor system;modeling and evaluation of a new cluster-based system for commercial applications;a simulator construction methodology for the shiva multiprocessor system;and Dycos - a customizable kernel architecture supporting distributed operating environments.
In many application areas, data that is being generated and processed goes beyond the petabyte scale. Analyzing such an increasing massive volume of data faces computational, as well as, statistical challenges. In ord...
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ISBN:
(纸本)9781450346177
In many application areas, data that is being generated and processed goes beyond the petabyte scale. Analyzing such an increasing massive volume of data faces computational, as well as, statistical challenges. In order to solve these challenges, distributed and parallelprocessing frameworks have been used for implementing scalable data analysis algorithms. Nevertheless, processing the whole big data set at one time may exceed the available computing resources and the time requirements for some applications. Thus, approximate approaches can be used to achieve asymptotic analysis results, especially when data analysis algorithms are amenable to an approximate result rather than an exact one. However, most approximation approaches require taking a random sample of the data which is a nontrivial task when working with big data sets. In this paper, we employ ensemble learning as an approach for asymptotic analysis using randomly selected subsets (i.e. data blocks) of a big data set. We propose an asymptotic ensemble learning framework which depends on block-based sampling rather than record-based sampling. In order to demonstrate the feasibility and performance of this framework, we present an empirical analysis on real data sets. In addition to the scalability advantage, the experimental results show that several blocks of a data set are enough to get approximately the same results as those from using the whole data set.
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