The Stealth distributed scheduler

Krueger, P.; Chawla, R.

doi:10.1109/icdcs.1991.148686

Cited by 68 publications

(22 citation statements)

References 9 publications

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“…Where both load-sharing and load-balancing approach tends to maximize the rate at which distribution systems work, when required resources are available, load-balancing additionally attempts to equalize the loads on the available nodes [23]. Additionally, load distribution algorithms can be categorized as: Sender-Initiated Algorithms [10], Receiver-Initiated Algorithms [10], Symmetrically Initiated Algorithms [20] and Adaptive Algorithm [21]. As the name suggests, in Sender-Initiated Algorithms, load-distribution is initiated by an overloaded sender that tends to send a task to an under-loaded receiver.…”

Section: Basics Of Load Balancing In a Distributed Environmentmentioning

confidence: 99%

A Distributed Multimedia Data Management over the Grid

Chatterjee

Sadjadi

Chen

2010

Multimedia Services in Intelligent Environments

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In this chapter, we propose a distributed multimedia data management architecture, which can efficiently store and retrieve multimedia data across several nodes of a Grid environment. The main components of the proposed system comprises of a distributed multidimensional index structure, a distributed query manager handling content-based information retrievals and a load balancing technology. The proposed distributed query manager embeds the high-level semantic relationships among the multimedia data objects into the k-NN based similarity search, thus bridging the semantic gap and increasing the relevance of query results manifold. This research has two major usabilities. First, it models a web environment where each node of the Grid can be considered as the nodes or sources of data in the world-wide-web. This should help to investigate and understand the challenges and requirements of future search paradigms based on content of multimedia data rather than on text annotations, as used currently. Second, it provides the foundation to develop content-based information retrievals as a possible Grid service. Extensive experiments were conducted with varied data sizes and different number of distribution nodes. Encouraging results are obtained that makes this endeavor a potential architecture to manage complex multimedia data over a distributed environment.

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Section: Basics Of Load Balancing In a Distributed Environmentmentioning

confidence: 99%

A Distributed Multimedia Data Management over the Grid

Chatterjee

Sadjadi

Chen

2010

Multimedia Services in Intelligent Environments

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“…In fact, many studies show that typical desktop workloads leave the vast majority of the resources idle most of the time. For example, reports regarding average system idle time range from 75% [509] to 91% [417]. On desktop machines, which are often networked together, the spare cycles on one machine may be used by applications initiated on another.…”

Section: Desktop and Worktation Workloadsmentioning

confidence: 99%

Workload Modeling for Computer Systems Performance Evaluation

Feitelson

2015

186

131

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Reliable performance evaluations require the use of representative workloads. This is no easy task since modern computer systems and their workloads are complex, with many interrelated attributes and complicated structures. Experts often use sophisticated mathematics to analyze and describe workload models, making these models difficult for practitioners to grasp. This book aims to close this gap by emphasizing the intuition and the reasoning behind the definitions and derivations related to the workload models. It provides numerous examples from real production systems, with hundreds of graphs. Using this book, readers will be able to analyze collected workload data and clean it if necessary, derive statistical models that include skewed marginal distributions and correlations, and consider the need for generative models and feedback from the system. The descriptive statistics techniques covered are also useful for other domains.

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“…The Linger-Longer approach permits slightly more disruption of the user, but tries to limit the delay to an acceptable level. One system that used non-idle workstations was the Stealth distributed scheduler [11]. It implemented a priority-based approach to running guest processes.…”

Section: Related Workmentioning

confidence: 99%