The Hector distributed run-time environment

Russ, Samuel H.; Robinson, J.; Flachs, B.; Heckel, B.

doi:10.1109/71.735957

Cited by 18 publications

(9 citation statements)

References 17 publications

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“…There have been several e orts to make theories practical and to compare these protocols 4,10,11,15,17,18,20]. The previous works employed some subset of recovery protocols, and evaluated their performance using applications running on small datasets.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Consistent Recovery Protocols Using MPICH-GF

Woo

Jung

Shin

et al. 2005

Dependable Computing - EDCC 5

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Abstract. This paper presents an implementation of several consistent recovery protocols at the abstract device level and their performance comparison. We h a ve performed experiments using three NAS Parallel Benchmark applications with class C datasets on state of the art equipment. The interesting result is that causal message logging protocol has the most expensive recovery cost with communication intensive applications since it su ers from concentrated overload of simultaneous message replaying. Receiver-based optimistic message logging has the least recovery cost with drawback of extensive disk access overhead in failure-free executions. Coordinated checkpointing seems the most practical choice among them.

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Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Consistent Recovery Protocols Using MPICH-GF

Woo

Jung

Shin

et al. 2005

Dependable Computing - EDCC 5

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“…At present, research is on-going to develop intelligent agents to perform task allocation for a heterogeneous computing environment [10]. Implementation of many of the functions of the human immune system described in this paper are being demonstrated in an H-cell implementation based on a hierarchical ART architecture [11].…”

Section: H-cells and S-cells As Intelligent Agents For Task Allocationmentioning

confidence: 99%

“…An intelligent control agent (ICA) based on the H-cell is being implemented to replace the slave agent used in the HECTOR system that helps globally manage the heterogeneous system [10]. The artificial immune based scheduling system is designed around the decentralized decision-making of the ICAs.…”

Section: Implementation In the Hector Environmentmentioning

confidence: 99%

The biological basis of the immune system as a model for intelligent agents

King¹,

Lambert²,

Russ³

et al. 1999

Lecture Notes in Computer Science

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Abstract. This paper describes the human immune system and its functionalities from a computational viewpoint. The objective of this paper is to provide the biological basis for an artificial immune system. This paper will also serve to illustrate how a biological system can be studied and how inferences can be drawn from its operation that can be exploited in intelligent agents. Functionalities of the biological immune system (e.g., content addressable memory, adaptation, etc.) are identified for use in intelligent agents. Specifically, in this paper, an intelligent agent will be described for task allocation in a heterogeneous computing environment. This research is not intended to develop an explicit model of the human immune system, but to exploit some of its functionalities in designing agent-based parallel and distributed control systems.

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“…Thus, it cannot manage hardware failures. Hector [16] performs a coordinated checkpointing using hierarchical process managers which create and migrate application processes. Before the checkpointing, every process closes its channel connections to ensure that there is no in-transit messages left in the network.…”

Section: Related Workmentioning

confidence: 99%