Robust Load Delegation in Service Grid Environments

Fölling, Alexander; Grimme, Christian; Lepping, Joachim; Papaspyrou, Alexander

doi:10.1109/tpds.2010.16

Cited by 12 publications

(14 citation statements)

References 24 publications

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“…Improved performance substantially, backup plan in case the system fails even partially, maintain the system stability, accommodate future modification in the system and avoid a situation where some nodes are heavily loaded while others are idle or doing little work. Most Resource matchmaking approaches are depend on the best grid resource selection from fault tolerance, shortest distance, low cost, high energy, load balanced techniques (Qiang et al, 2011;Ning and Shaohua, 2013;Folling et al, 2010). Existing systems have a Limited innovation for resource matchmaking process.…”

Section: Grid Balanced Resource Matchmakingmentioning

confidence: 99%

Inject an Elastic Grid Computing Techniques to Optimal Resource Management Technique Operations

Surendran¹,

Varthini²

2013

Journal of Computer Science

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Evaluation of sharing on the Internet well-developed from energetic technique of grid computing. Dynamic Grid Computing is Resource sharing in large level high performance computing networks at worldwide. Existing systems have a Limited innovation for resource management process. In proposed work, Grid Computing is an Internet based computing for Optimal Resource Management Technique Operations (ORMTO). ORMTO are Elastic scheduling algorithm, finding the Best Grid node for a task prediction, Fault tolerance resource selection, Perfect resource co-allocation, Grid balanced Resource matchmaking and Agent based grid service, wireless mobility resource access. Survey the various resource management techniques based on the performance measurement factors like time complexity, Space complexity and Energy complexity find the ORMTO with Grid computing. Objectives of ORMTO will provide an efficient Resource co-allocation automatically for a user who is submitting the job without grid knowledge, design a Grid service (portal) for selects the Best Fault tolerant Resource for a given task in a fast, secure and efficient manner and provide an Enhanced grid balancing system for multi-tasking via Hybrid topology based Grid Ranking. Best Quality of Service (QOS) parameters are important role in all RMT. Proposed system ORMTO use the greater number of QOS Parameters for better enhancement of existing RMT. In proposed system, follow the enhanced techniques and algorithms use to improve the Grid based ORMTO.

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Section: Grid Balanced Resource Matchmakingmentioning

confidence: 99%

Inject an Elastic Grid Computing Techniques to Optimal Resource Management Technique Operations

Surendran¹,

Varthini²

2013

Journal of Computer Science

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“…In [7], the authors use evolutionary fuzzy systems to solve job scheduling in decentralized computational grids where jobs between grid clusters are exchanged. The average response time per job is minimized but again the overhead of data transfers is not considered.…”

Section: International Journal Of Digital Multimedia Broadcastingmentioning

confidence: 99%

Multi-Objective Genetic Algorithm for Task Assignment on Heterogeneous Nodes

Notario

Baert

D’Hondt

2012

International Journal of Digital Multimedia Broadcasting

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Task assignment in grid computing, where both processing and bandwidth constraints at multiple heterogeneous devices need to be considered, is a challenging problem. Moreover, targeting the optimization of multiple objectives makes it even more challenging. This paper presents a task assignment strategy based on genetic algorithms in which multiple and conflicting objectives are simultaneously optimized. Specifically, we maximize task execution quality while minimizing energy and bandwidth consumption. Moreover, in our video processing scenario; we consider transcoding to lower spatial/temporal resolutions to tradeoff between video quality; processing, and bandwidth demands. The task execution quality is then determined by the number of successfully processed streams and the spatial-temporal resolution at which they are processed. The results show that the proposed algorithm offers a range of Pareto optimal solutions that outperforms all other reference strategies.

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“…Other fuzzy‐based grid scheduling algorithms20–22 make use of a Takagi–Sugeno–Kang (TSK)29 controller. Instead of using site‐specific metrics which cover a large number of system states, only two different state values are allowed.…”

Section: Knowledge Representation Schemesmentioning

confidence: 99%