107 resultados para load balancing

em Deakin Research Online - Australia


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Load balance is a critical issue in distributed systems, such as server grids. In this paper, we propose a Balanced Load Queue (BLQ) model, which combines the queuing theory and hydro-dynamic theory, to model load balance in server grids. Base on the BLQ model, we claim that if the system is in the state of global fairness, then the performance of the whole system is the best. We propose a load balanced algorithm based on the model: the algorithm tries its best to keep the system in the global fairness status using job deviation. We present three strategies: best node, best neighbour, and random selection, for job deviation. A number of experiments are conducted for the comparison of the three strategies, and the results show that the best neighbour strategy is the best among the proposed strategies. Furthermore, the proposed algorithm with best neighbour strategy is better than the traditional round robin algorithm in term of processing delay, and the proposed algorithm needs very limited system information and is robust.

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This report describes an implementation of MPI-1 on the GENESIS cluster operating system and compares this implementation to a UNIX based MPI implementation. The changes that were made to the implementation are compared between the two, and the advantages of porting to GENESIS are detailed. This report demonstrates how GENESIS load balancing supported by process migration improves the execution performance of an MPI application. The significance of this report is in demonstrating how these services can enhance parallel programming tools to improve performance and how future parallel programming tool design could take advantage of these services.

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Dedicated clusters are becoming commonly used for high performance parallel processing. Computers of a non-dedicated cluster are often idle or lightly loaded. These under utilised computers can be employed to execute parallel applications. Thus, they have to be shared by parallel and sequential applications, which could lead to the improvement of their execution performance. There is a lack of experimental study showing the behaviour and performance of executing parallel and sequential applications concurrently on a non-dedicated cluster. We present the result of an experimental study into load balancing of a mixture of parallel and sequential applications on a non-dedicated cluster.

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Increasingly, replicated anycast servers are being used to deliver network applications and service ever increasing user requests. Therefore, the strategies used to guarantee network bandwidth prerequisites and perform load balancing across the nodes of an anycast group are critical to the performance of online applications. In this paper, we model user requests, network congestion and latency, and server load using a combination of hydro-dynamics and queuing theory to develop an efficient job distribution strategy. Current, anycast research does not explicitly consider the system load of nodes within an anycast groups when distributing requests. Therefore, the performance of a heavily loaded anycast system can quickly become congested and uneven as jobs are routed to closely linked nodes which are already saturated with requests. In comparison, the nodes of further away systems remain relatively unused because of other issues such as network bandwidth and latency during these times. Our system redirects requests from busy systems to the idle, remotely linked nodes, to process requests faster in spite of slower network access. Using an empirical study, we show this technique can improve request performance, and throughput with minimal network probing overhead.

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Studies have shown that most of the computers in a non-dedicated cluster are often idle or lightly loaded. The underutilized computers in a non-dedicated cluster can be employed to execute parallel applications. The aim of this study is to learn how concurrent execution of a computation-bound and sequential applications influence their execution performance and cluster utilization. The result of the study has demonstrated that a computation-bound parallel application benefits from load balancing, and at the same time sequential applications suffer only an insignificant slowdown of execution. Overall, the utilization of a non-dedicated cluster is improved.

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Computers of a non-dedicated cluster are often idle (users attend meetings, have lunch or coffee breaks) or lightly loaded (users carry out simple computations). These underutilized computers can be employed to execute parallel applications not only during weekends and at nights but also during office hours. Thus, they have to be shared by parallel and sequential applications which could lead to the improvement of their execution performance. However, there is a lack of experimental study showing the behavior and performance of parallel and sequential applications executing concurrently on clusters. We present here the result of an experimental study into load balancing based scheduling of a mixture of parallel and sequential applications on a non-dedicated cluster.

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Although individual PCs of a cluster are used by their owners to run sequential applications (local jobs), the cluster as a whole or its subset can also be employed to run parallel applications (cluster jobs) even during working hours. This implies that these computers have to be shared by parallel and sequential applications, which could lead to the improvement of the execution performance and resource utilization. However, there is a lack of experimental study showing the behavior and performance of executing parallel and sequential applications concurrently on a non-dedicated cluster. The result of such research would be beneficial for the development of new global scheduling algorithms. We present the result of an experimental study into scheduling of a mixture of parallel and sequential applications on a non-dedicated cluster. The aim of this study is to learn how the concurrent execution of a communication intensive parallel application and sequential applications influences their execution performance and utilization of the cluster.

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Wireless sensor networks (WSN) are attractive for information gathering in large-scale data rich environments. In order to fully exploit the data gathering and dissemination capabilities of these networks, energy-efficient and scalable solutions for data storage and information discovery are essential. In this paper, we formulate the information discovery problem as a load-balancing problem, with the combined aim being to maximize network lifetime and minimize query processing delay resulting in QoS improvements. We propose a novel information storage and distribution mechanism that takes into account the residual energy levels in individual sensors. Further, we propose a hybrid push-pull strategy that enables fast response to information discovery queries.

Simulations results prove the proposed method(s) of information discovery offer significant QoS benefits for global as well as individual queries in comparison to previous approaches.

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Computers of a non-dedicated cluster are often idle (users attend meetings, have lunch or coffee breaks) or lightly loaded (users carry out simple computations to support problem solving activities). These underutilised computers can be employed to execute parallel applications. Thus, these computers can be shared by parallel and sequential applications, which could lead to the improvement of their execution performance. However, there is a lack of experimental study showing the applications’ performance and the system utilization of executing parallel and sequential applications concurrently and concurrent execution of multiple parallel applications on a non-dedicated cluster. Here we present the result of an experimental study into load balancing based scheduling of mixtures of NAS Parallel Benchmarks and BYTE sequential applications on a very low cost non-dedicated cluster. This study showed that the proposed sharing provided performance boost as compared to the execution of the parallel load in isolation on a reduced number of computers and better cluster utilization. The results of this research were used not only to validate other researchers’ result generated by simulation but also to support our research mission of widening the use of non-dedicated clusters. Our promising results obtained could promote further research studies to convince universities, business and industry, which require a large amount of computing resources, to run parallel applications on their already owned non-dedicated clusters.

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Wireless sensor networks (WSN) are attractive for information gathering in large-scale data rich environments. Emerging WSN applications require dissemination of information to interested clients within the network requiring support for differing traffic patterns. Further, in-network query processing capabilities are required for autonomic information discovery. In this paper, we formulate the information discovery problem as a load-balancing problem, with the combined aim being to maximize network lifetime and minimize query processing delay. We propose novel methods for data dissemination, information discovery and data aggregation that are designed to provide significant QoS benefits. We make use of affinity propagation to group "similar" sensors and have developed efficient mechanisms that can resolve both ALL-type and ANY-type queries in-network with improved energy-efficiency and query resolution time. Simulation results prove the proposed method(s) of information discovery offer significant QoS benefits for ALL-type and ANY-type queries in comparison to previous approaches.

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The future of computing lies with distributed systems, i.e. a network of workstations controlled by a modern distributed operating system. By supporting load balancing and parallel execution, the overall performance of a distributed system can be improved dramatically. Process migration, the act of moving a running process from a highly loaded machine to a lightly loaded machine, could be used to support load balancing, parallel execution, reliability etc. This thesis identifies the problems past process migration facilities have had and determines the possible differing strategies that can be used to resolve these problems. The result of this analysis has led to a new design philosophy. This philosophy requires the design of a process migration facility and the design of an operating system to be conducted in parallel. Modern distributed operating systems follow the microkernel and client/server paradigms. Applying these design paradigms, in conjunction with the requirements of both process migration and a distributed operating system, results in a system where each resource is controlled by a separate server process. However, a process is a complex resource composed of simple resources such as data structures, an address space and communication state. For this reason, a process migration facility does not directly migrate the resources of a process. Instead, it requests the appropriate servers to transfer the resources. This novel solution yields a modular, high performance facility that is easy to create, debug and maintain. Furthermore, the design easily incorporates providing multiple migration strategies. In order to verify the validity of this design, a process migration facility was developed and tested within RHODOS (ResearcH Oriented Distributed Operating System). RHODOS is a modern microkernel and client/server based distributed operating system. In RHODOS, a process is composed of at least three separate resources: process state - maintained by a process manager, address space - maintained by a memory manager and communication state - maintained by an InterProcess Communication Manager (IPCM). The RHODOS multiple strategy migration manager utilises the services of the process, memory and IPC Managers to migrate the resources of a process. Performance testing of this facility indicates that this design is as fast or better than existing systems which use faster hardware. Furthermore, by studying the results of the performance test ing, the conditions under which a particular strategy should be employed have been identified. This thesis also addresses heterogeneous process migration. The current trend is to have islands of homogeneous workstations amid a sea of heterogeneity. From this situation and the current literature on the topic, heterogeneous process migration can be seen as too inefficient for general use. Instead, only homogeneous workstations should be used for process migration. This implies a need to locate homogeneous workstations. Entities called traders, which store and disseminate knowledge about the resources of several workstations, should be used to provide resource discovery. Resource discovery will enable the detection of homogeneous workstations to which processes can be migrated.

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Current attempts to manage parallel applications on Clusters of Workstations (COWs) have either generally followed the parallel execution environment approach or been extensions to existing network operating systems, both of which do not provide complete or satisfactory solutions. The efficient and transparent management of parallelism within the COW environment requires enhanced methods of process instantiation, mapping of parallel process to workstations, maintenance of process relationships, process communication facilities, and process coordination mechanisms. The aim of this research is to synthesise, design, develop and experimentally study a system capable of efficiently and transparently managing SPMD parallelism on a COW. This system should both improve the performance of SPMD based parallel programs and relieve the programmer from the involvement into parallelism management in order to allow them to concentrate on application programming. It is also the aim of this research to show that such a system, to achieve these objectives, is best achieved by adding new special services and exploiting the existing services of a client/server and microkernel based distributed operating system. To achieve these goals the research methods of the experimental computer science should be employed. In order to specify the scope of this project, this work investigated the issues related to parallel processing on COWs and surveyed a number of relevant systems including PVM, NOW and MOSIX. It was shown that although the MOSIX system provide a number of good services related to parallelism management, none of the system forms a complete solution. The problems identified with these systems include: instantiation services that are not suited to parallel processing; duplication of services between the parallelism management environment and the operating system; and poor levels of transparency. A high performance and transparent system capable of managing the execution of SPMD parallel applications was synthesised and the specific services of process instantiation, process mapping and process interaction detailed. The process instantiation service designed here provides the capability to instantiate parallel processes using either creation or duplication methods and also supports multiple and group based instantiation which is specifically design for SPMD parallel processing. The process mapping service provides the combination of process allocation and dynamic load balancing to ensure the load of a COW remains balanced not only at the time a parallel program is initialised but also during the execution of the program. The process interaction service guarantees to maintain transparently process relationships, communications and coordination services between parallel processes regardless of their location within the COW. The combination of these services provides an original architecture and organisation of a system that is capable of fully managing the execution of SPMD parallel applications on a COW. A logical design of a parallelism management system was developed derived from the synthesised system and was shown that it should ideally be based on a distributed operating system employing the client server model. The client/server based distributed operating system provides the level of transparency, modularity and flexibility necessary for a complete parallelism management system. The services identified in the synthesised system have been mapped to a set of server processes including: Process Instantiation Server providing advanced multiple and group based process creation and duplication; Process Mapping Server combining load collection, process allocation and dynamic load balancing services; and Process Interaction Server providing transparent interprocess communication and coordination. A Process Migration Server was also identified as vital to support both the instantiation and mapping servers. The RHODOS client/server and microkernel based distributed operating system was selected to carry out research into the detailed design and to be used for the implementation this parallelism management system. RHODOS was enhanced to provide the required servers and resulted in the development of the REX Manager, Global Scheduler and Process Migration Manager to provide the services of process instantiation, mapping and migration, respectively. The process interaction services were already provided within RHODOS and only required some extensions to the existing Process Manager and IPC Managers. Through a variety of experiments it was shown that when this system was used to support the execution of SPMD parallel applications the overall execution times were improved, especially when multiple and group based instantiation services are employed. The RHODOS PMS was also shown to greatly reduce the programming burden experienced by users when writing SPMD parallel applications by providing a small set of powerful primitives specially designed to support parallel processing. The system was also shown to be applicable and has been used in a variety of other research areas such as Distributed Shared Memory, Parallelising Compilers and assisting the port of PVM to the RHODOS system. The RHODOS Parallelism Management System (PMS) provides a unique and creative solution to the problem of transparently and efficiently controlling the execution of SPMD parallel applications on COWs. Combining advanced services such as multiple and group based process creation and duplication; combined process allocation and dynamic load balancing; and complete COW wide transparency produces a totally new system that addresses many of the problems not addressed in other systems.

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Studies have shown that most of the computers in a non-dedicated cluster are often idle or lightly loaded. The underutilized computers in a non-dedicated cluster can be employed to execute parallel applications. The aim of this study is to learn how concurrent execution of a computation-bound and sequential applications influence their execution performance and cluster utilization. The result of the study has demonstrated that a computation-bound parallel application benefits from load balancing, and at the same time sequential applications suffer only an insignificant slowdown of execution. Overall, the utilization of a non-dedicated cluster is improved.

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We assert that companies can make more money and research institutions can improve their performance if inexpensive clusters and enterprise grids are exploited. In this paper, we have demonstrated that our claim is valid by showing the study of how programming environments, tools and middleware could be used for the execution of parallel and sequential applications, multiple parallel applications executing simultaneously on a non-dedicated cluster, and parallel applications on an enterprise grid and that the execution performance was improved. For this purpose an execution environment, and parallel and sequential benchmark applications selected for, and used in, the experiments were characterised.

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We investigate the resource-allocation problem in multicell networks targeting the max-min throughput of all cells. A joint optimization over power control, channel allocation, and user association is considered, and the problem is then formulated as a nonconvex mixed-integer nonlinear problem (MINLP). To solve this problem, we proposed an alternating-optimization-based algorithm, which applies branch-and-bound and simulated annealing in solving subproblems at each optimization step. We also demonstrate the convergence and efficiency of the proposed algorithms by thorough numerical experiments. The experimental results show that joint optimization over all resources outperforms the restricted optimization over individual resources significantly.