A resource broker with an efficient network information model on grid environments

Yang, Chao-Tung; Shih, Po-Chi; Lin, Cheng-Fang; Chen, Sung-Yi

doi:10.1007/s11227-006-0025-0

Cited by 13 publications

(10 citation statements)

References 10 publications

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“…The main tasks of the proposed Resource Broker are resource discovery, application modeling, information gathering, system selection, and job execution [12]. Information gathering refers to aggregating information required for resource brokering.…”

Section: Machine and Network Information Aggregatormentioning

confidence: 99%

Resource brokering using a multi‐site resource allocation strategy for computational grids

Yang

Leu

Chen

2010

Concurrency and Computation

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SUMMARYGrid computing employs heterogeneous resources which may be installed on different platforms, hardware/software, computer architectures, and perhaps using different computer languages to solve large-scale computational problems. As many more Grids are being developed worldwide, the number of multi-institutional collaborations is growing rapidly. However, to realize Grid computing's full potential, it is expected that Grid participants must be able to share one another's resources. This paper presents a resource broker that employs the multi-site resource allocation (MSRA) strategy and the dynamic domain-based network information model that we propose to allocate Grid resources to submitted jobs, where the Grid resources may be dispersed at different sites, and owned and governed by different organizations or institutes. The jobs and resources may also belong to different clusters/sites. Resource statuses collected by the Ganglia, and network bandwidths gathered by the Network Weather Service, are both considered in the proposed scheduling approach. A dynamic domain-based model for network information measurement is also proposed to choose the most appropriate resources that meet the jobs' execution requirements. Experimental results show that MSRA outperformed the other tested strategies.

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Section: Machine and Network Information Aggregatormentioning

confidence: 99%

Resource brokering using a multi‐site resource allocation strategy for computational grids

Yang

Leu

Chen

2010

Concurrency and Computation

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“…However, much of the research into economic grid resource allocation makes reference to some sort of broker ( [12][13][14][15][16][17][18][19][20][21] and others), suggesting that no matter what the future grid economy looks like, brokers will play a significant role. At least in the infancy of applications that consume grid resources, allocating its own resources will place unnecessary strain and complexity on the system, which could be much more easily handled by a dedicated broker.…”

Section: Grid Economicsmentioning

confidence: 99%

“…Coallocation strategies like the one presented in [21] may reduce the transmission times of the involved blocks. The network bandwidth should be factored in to efficient allocation as in [20] and should affect pricing.…”

Section: Conclusion/future Workmentioning

confidence: 99%

Efficient allocation and composition of distributed storage

2008

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In this paper, we investigate the composition of cheap network storage resources to meet specific availability and capacity requirements. We show that the problem of finding the optimal composition for availability and price requirements can be reduced to the knapsack problem, and propose three techniques for efficiently finding approximate solutions. The first algorithm uses a dynamic programming approach to find mirrored storage resources for high availability requirements, and runs in the pseudo-polynomial O(n 2 c) time where n is the number of sellers' resources to choose from and c is a capacity function of the requested and minimum availability. The second technique is a heuristic which finds resources to be agglomerated into a larger coherent resource, with complexity of O(n log n). The third technique finds a compromise between capacity and availability (which in our phrasing is a complex integer programming problem) using a genetic algorithm. The algorithms can be implemented on a broker that intermediates between buyers and sellers of storage resources. Finally, we show that a broker in an open storage market, using the combination of the three algorithms can more frequently meet user requests and lower the cost of requests that are met compared to a broker that simply matches single resources to requests.

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“…Many studies have identified important QoS features of SOA systems [1, 2], such as throughput, timeliness and security, which are directly affected by the limitation of system resources. It is noted that the system resource considered here is for large-scale aggregation of distributed computing resources working together over the Internet as a tremendous virtual computer [3][4][5]. For example, computing grids and clouds are vast resource pools for on-demand requests over the Internet.…”

Section: Introductionmentioning

confidence: 99%

Adaptive resource allocation for service-based systems

Yau

2009

Proceedings of the First Asia-Pacific Symposium on Internetware

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Due to its major advantages, service-oriented architecture (SOA) has been adopted in various distributed systems, such as web services, grid computing systems, utility computing systems and cloud computing systems. These systems are referred as service-based systems (SBS). In order to effectively use these systems in various applications, one major challenge which must be addressed is to manage the quality of services (QoS) to satisfy users' requirements. In SBS, multiple services are often hosted by the same server and compete for the limited system resources of the server, such as CPU-time, memory and network bandwidth. In addition, service compositions, resource status of servers, workflow priorities and QoS requirements are usually dynamically changing in runtime. Hence, it is necessary to have effective techniques to allocate the system resources to each service provided by a server in order to satisfy the QoS requirements of multiple workflows in SBS. In this paper, a resource allocation approach is presented to adaptively allocating the system resources of servers to their services in runtime in order to satisfy one of the most important QoS requirements, the throughput, of multiple workflows in SBS.

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A resource broker with an efficient network information model on grid environments

Cited by 13 publications

References 10 publications

Resource brokering using a multi‐site resource allocation strategy for computational grids

Resource brokering using a multi‐site resource allocation strategy for computational grids

Efficient allocation and composition of distributed storage

Adaptive resource allocation for service-based systems

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