ARMS: An Agent‐Based Resource Management System for Grid Computing

Cao, Junwei; Jarvis, Stephen A.; Saini, Subhash; Kerbyson, Darren J.; Nudd, G.R.

doi:10.1155/2002/910792

Cited by 119 publications

(91 citation statements)

References 16 publications

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“…It is not a new idea to apply workflow technologies to Grid platform. Actually, people try to integrate the workflow technologies under Grid platforms in many projects, such as Triana (Majithia et (Cao et al 2002(Cao et al , 2003, Askalon (Fahringer et al 2005), Karajan (http://www.cogkit.org), etc. These Grid workflows give a host of useful workflow composition tools with graph-based modeling or language-based modeling.…”

Section: The Application Limit Of Grid In Remote Sensingmentioning

confidence: 99%

Grid Workflow Modeling for Remote Sensing Retrieval Service with Tight Coupling

Xue

Jin

et al. 2009

Lecture Notes in Computer Science

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Abstract. Grid computing technology is a new way for remotely sensed data processing. Tight-coupling remote sensing algorithms can't be scheduled by grid platform directly. Therefore, we need a interactive graphical tool to present the executing relationships of algorithms and to generate automatically the corresponding submitted description files for grid platform. In this paper we mainly discusses some application cases based on Grid computing for Geosciences and the application limit of Grid in remote sensing, and gives the method of Grid Workflow modeling for remote sensing. Then based on the modeling, we design a concrete example.

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Section: The Application Limit Of Grid In Remote Sensingmentioning

confidence: 99%

Grid Workflow Modeling for Remote Sensing Retrieval Service with Tight Coupling

Xue

Jin

et al. 2009

Lecture Notes in Computer Science

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“…Multi-agent systems have been known to provide capabilities of autonomy, cooperation, heterogeneity, robustness and reactivity, scalability, and flexibility [5,16]. A number of initiatives to apply agents in computational Grids have appeared [2,7,11]. Most these agent-based Grid scheduling systems are centralised and static as scheduling is performed by a Grid highperformance scheduler (broker), and resource agents do not use any flexible negotiation to schedule the jobs.…”

Section: Introductionmentioning

confidence: 99%

A Multi-agent Infrastructure and a Service Level Agreement Negotiation Protocol for Robust Scheduling in Grid Computing

Ouelhadj

Garibaldi

MacLaren

et al. 2005

Advances in Grid Computing - EGC 2005

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Abstract. In this paper we propose a new infrastructure for efficient job scheduling on the Grid using multi-agent systems and a Service Level Agreement (SLA) negotiation protocol based on the Contract Net Protocol. The agent-based Grid scheduling system involves user agents, local scheduler agents, and super scheduler agents. User agents submit jobs to Grid compute resources. Local scheduler agents schedule jobs on compute resources. Super scheduler agents act as mediators between the local scheduler and the user agents to schedule the jobs at the global level of the Grid. The SLA negotiation protocol is a hierarchical bidding mechanism involving meta-SLA negotiation between the user agents and the super scheduler agents; and sub-SLA negotiation between the super scheduler agents and the local scheduler agents. In this protocol the agents exchange SLA-announcements, SLA-bids, and SLAawards to negotiate the schedule of jobs on Grid compute resources. In the presence of uncertainties a re-negotiation mechanism is proposed to renegotiate the SLAs in failure.

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“…The authors emphasizes the overlap in problems that GRID and MAS address but without sharing research progress in either area: an integrated Grid/agent approach will only be achieved via a more fine-grain intertwining of the two technologies. Using MAS principles to improve core GRID performances (e.g., directory services, scheduling, brokering services, task allocation, dynamic resource allocation and load balancing) is a very active topic in the MAS community, for example: (i) MAS-based GRID for resource management [23][24][25][26]; (ii) MAS-based GRID for VO management [27]. However, none of this work proposes a real integration of MAS and GRID.…”

Section: Integration Related Workmentioning

confidence: 99%

Service-Based Integration of Grid and Multi-Agent Systems Models

Jonquet

Dugénie

Cerri

Service-Oriented Computing: Agents, Semantics, and Engineering

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Abstract. This position paper addresses the question of integrating GRID and MAS (Multi-Agent Systems) models by means of a service oriented approach. Service Oriented Computing (SOC) tries to address many challenges in the world of computing with services. The concept of service is clearly at the intersection of GRID and MAS and their integration allows to address one of these key challenges: the implementation of dynamically generated services based on conversations. In our approach, services are exchanged (i.e., provided and used) by agents through GRID mechanisms and infrastructure. Integration goes beyond the simple interoperation of applications and standards, it has to be intrinsic to the underpinning model. We introduce here an (quite unique) integration model for GRID and MAS. This model is formalized and represented by a graphical description language called Agent-Grid Integration Language (AGIL). This integration is based on two main ideas: (i) the representation of agent capabilities as Grid services in service containers; (ii) the assimilation of the service instantiation mechanism (from GRID) with the creation of a new conversation context (from MAS). The integrated model may be seen as a formalization of agent interaction for service exchange.

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ARMS: An Agent‐Based Resource Management System for Grid Computing

Cited by 119 publications

References 16 publications

Grid Workflow Modeling for Remote Sensing Retrieval Service with Tight Coupling

Grid Workflow Modeling for Remote Sensing Retrieval Service with Tight Coupling

A Multi-agent Infrastructure and a Service Level Agreement Negotiation Protocol for Robust Scheduling in Grid Computing

Service-Based Integration of Grid and Multi-Agent Systems Models

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