Using content-addressable networks for load balancing in desktop grids

Kim, Jik-Soo; Keleher, Peter J.; Marsh, Michael; Bhattacharjee, Bobby; Sussman, Alan

doi:10.1145/1272366.1272391

Cited by 38 publications

(52 citation statements)

References 21 publications

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“…The performance results obtained from the working prototype system shows the feasibility and effectiveness of service level agreementbased resource provisioning in cloud systems. Kim et al (2007) it is proposed a decentralized algorithm for maintaining approximate global load information and a job pushing mechanism that uses the global information to push jobs towards underutilized portions of the system. The system effectively balances load and improves overall system throughput.…”

Section: Methodsmentioning

confidence: 99%

Performance Improvement in Cloud Computing Using Resource Clustering

Malathy¹

2013

Journal of Computer Science

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Cloud computing is a computing paradigm in which the various tasks are assigned to a combination of connections, software and services that can be accessed over the network. The computing resources and services can be efficiently delivered and utilized, making the vision of computing utility realizable. In various applications, execution of services with more number of tasks has to perform with minimum intertask communication. The applications are more likely to exhibit different patterns and levels and the distributed resources organize into various topologies for information and query dissemination. In a distributed system the resource discovery is a significant process for finding appropriate nodes. The earlier resource discovery mechanism in cloud system relies on the recent observations. In this study, resource usage distribution for a group of nodes with identical resource usages patterns are identified and kept as a cluster and is named as resource clustering approach. The resource clustering approach is modeled using CloudSim, a toolkit for modeling and simulating cloud computing environments and the evaluation improves the performance of the system in the usage of the resources. Results show that resource clusters are able to provide high accuracy for resource discovery.

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Section: Methodsmentioning

confidence: 99%

Performance Improvement in Cloud Computing Using Resource Clustering

Malathy¹

2013

Journal of Computer Science

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“…This probabilistic approach can balance load effectively, but also minimizes over-provisioning. More details on this work for initial job placement can be found in Kim et al [10].…”

Section: Matchmaking Proceduresmentioning

confidence: 99%

Decentralized Preemptive Scheduling Across Heterogeneous Multi-core Grid Resources

Balasubramanian

Sussman

Sadeh

2014

Job Scheduling Strategies for Parallel Processing

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The recent advent of multi-core computing environments increases the heterogeneity of grid resources and the complexity of managing them, making efficient load balancing challenging. In an environment where jobs are submitted regularly into a grid which is already executing several jobs, it becomes important to provide low job turn-around times and high throughput for the users. Typically, the grids employ a First Come First Serve (FCFS) method of executing the jobs in the queue which results in poor average job turnaround times and wait times for most jobs. Hence a conventional FCFS (First come first serve) scheduling strategy does not suffice to reduce the average wait times across all jobs. In this paper, we propose new decentralized preemptive scheduling strategies that backfill jobs locally and dynamically migrate waiting jobs across nodes to leverage residual resources, while guaranteeing bounded turn-around and waiting times for all jobs. The methods attempt to maximize total throughput while balancing load across available grid resources. Experimental results for intra-node scheduling via simlulation show that our scheduling scheme performs considerably better than the conventional FCFS approach of a distributed or a centralized scheduler.

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“…A recent work by Jik-Soo et al [12] that advocates Content Addressable Network [16], DHT based dynamic propagation and load-balancing in desktop Grids, suffer from performance uncertainty and unreliability due to lack of context awareness in scheduling.…”

Section: Dependable Schedulingmentioning

confidence: 99%

“…Uncertainty and unreliability are facts in federated environments, which are triggered by multiple factors, including: (i) software and hardware failures as the system and application scale that lead to severe performance degradation and critical information loss; (ii) dynamism (unexpected failure) that occurs due to temporal behaviours, which should be detected and resolved at runtime to cope with changing conditions; and (iii) lack of complete global knowledge that hampers efficient decision making as regards to composition and deployment of the application elements. The existing Grid scheduling approaches and application composition techniques [12], [17] are inadequate to handle all of these uncertainties caused by the dynamic behaviours related to resources and applications in federated environments.…”

Section: Introductionmentioning

confidence: 99%

Dependable workflow scheduling in global Grids

Rahman

Ranjan

Buyya

2009

2009 10th IEEE/ACM International Conference on Grid Computing

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In this paper, a reputation-based Grid workflow scheduling algorithm is proposed to counter the effect of inherent unreliability and temporal characteristics of computing resources in large scale, decentralized Grid overlays. The proposed approach builds upon structured peer-to-peer indexing and overlay networking techniques to create a scalable wide-area networking of Grid sites for supporting dependable scheduling of applications. The scheduling algorithm considers reliability of a Grid resource as a statistical property, which is globally computed in the decentralized Grid overlay based on dynamic feedbacks or reputation scores assigned by individual service consumers (Grid Resource Brokers). The proposed algorithm can dynamically adapt to changing resource conditions and offer significant performance gains as compared to traditional approaches in the event of unsuccessful job execution or resource failure. We evaluate and demonstrate the feasibility of our approach through an extensive trace driven simulation. The results show that our scheduling technique can reduce the makespan up to 50% and successfully isolate the failure-prone resources from the system.

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Using content-addressable networks for load balancing in desktop grids

Cited by 38 publications

References 21 publications

Performance Improvement in Cloud Computing Using Resource Clustering

Performance Improvement in Cloud Computing Using Resource Clustering

Decentralized Preemptive Scheduling Across Heterogeneous Multi-core Grid Resources

Dependable workflow scheduling in global Grids

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