Ontology for Contract Negotiations in an Agent-based Grid Resource Management System

Drozdowicz, Michal; Wasielewska, Katarzyna; Ganzha, Maria; Paprzycki, Marcin; Attaoui, Naoual; Lirkov, Ivan; Olejnik, Richard; Petcu, Dana; Bǎdicǎ, Costin

doi:10.4203/csets.27.15

Cited by 14 publications

(15 citation statements)

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“…One of the main assumptions of the AiG is to use ontologies and semantic data processing to represent all knowledge in the system, as well as the content of messages exchanged by system components. Therefore, we have developed an ontology of the grid combined with ontologies needed for contract negotiations (for details, see [16]). This ontology modifies and extends the ontology developed during the CoreGrid project.…”

Section: Agents In Grid Projectmentioning

confidence: 99%

Combining AiG Agents with Unicore Grid for Improvement of User Support

Lysik

Wasielewska

Paprzycki

et al. 2013

2013 First International Symposium on Computing and Networking

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Abstract-Grid computing has, in recent history, become an invaluable tool for scientific research. As grid middleware has matured, considerations have extended beyond the core functionality, towards greater usability. The aim of this paper is to consider how resources that are available to the users across the Queensgate Grid (QGG) at the University of Huddersfield (UoH), could be accessed with the help of an ontology-driven interface. The interface is a part of the Agent in Grid (AiG) project under development at the Systems Research Institute Polish Academy of Sciences (SRIPAS). It is to be customized and integrated with the UoH computing environment. The overarching goal is to help users of the grid infrastructure. The secondary goals are: (i) to improve the performance of the system, and (ii) to equalize the distribution of work among resources. Results presented in this paper include the new ontology that is being developed for the grid at the UoH, and the description of issues encountered during the development of a scenario when user searches for an appropriate resource within the Unicore grid middleware and submits job to be executed on such resource.

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Section: Agents In Grid Projectmentioning

confidence: 99%

Combining AiG Agents with Unicore Grid for Improvement of User Support

Lysik

Wasielewska

Paprzycki

et al. 2013

2013 First International Symposium on Computing and Networking

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“…The CGO was extended (adding 88 entities) and modified to match the needs of the AiG project (see, [5,9]). During this process, features identified as most problematic, from the point of view of the AiG project, have been modified.…”

Section: Aig Ontology Reengineeringmentioning

confidence: 99%

“…The AiG project combines software agents and semantic data processing. Specifically, all knowledge in the system is stored in / represented as an ontology, while communication protocols utilize messages with ontological content ( [5]). During the development of the system, three ontologies were designed to provide concepts necessary for: (i) resource and Grid structure description, (ii) contract and requirements specification, and (iii) content of messages exchanged in the system.…”

Section: Introductionmentioning

confidence: 99%

Reengineering and Extending the Agents in Grid Ontology

Szmeja

Wasielewska

Ganzha

et al. 2014

Large-Scale Scientific Computing

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Abstract. Ontology engineering, despite considerable progress, is still relatively new and dynamically evolving discipline. As a result, the universal standards for creating and/or editing an ontology, have not been established. This leads to problems with reusing and updating existing ontologies. It also makes writing an ontology from scratch seem like a good idea. The aim of this paper is two-fold. First, to discuss key issues encountered during re-engineering of an existing ontology. Second, to show how the good practices of ontology development were applied to model the area of computational linear algebra. Here, special attention is paid to the application of this ontology in the user support system.

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“…However, some modifications and extensions had to be brought to this solution, especially so that it would include concepts related to the SLA. The complete description of the resulting ontology can be found in [21,22]. Here, let us briefly outline its main features.…”

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confidence: 99%

“…In an example given in [23] simple job execution negotiations involved simultaneous evaluation of price, job start time and job end time. Currently, after the AiG ontology was fully developed (see, [22] for more details), truly multi-criterial negotiations can be used. Note that in both negotiation scenarios introduced above, the negotiation strategy is constrained by the following conditions: (1) no information about the preferences of the other participant(s) in the negotiation, and (2) the agreement reached should be optimal to both negotiating parties.…”

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confidence: 99%

Multiple equivalent simultaneous offers strategy in an agent-based grid resource brokering system - initial considerations

Attaoui¹,

Ganzha²,

Paprzycki³

et al. 2013

SCPE

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Abstract. The Agent in Grid (AiG) project attempts to integrate the concept of the Grid and an agent-based system to facilitate efficient resource management in the Grid. In this paper, we present preliminary considerations concerning multiple equivalent simultaneous offers strategy that can be used in the Service Level Agreement (SLA) negotiations. These negotiations are the key part of the main use case scenarios within the AiG project. In this context, first, we describe the AiG system. Second, we introduce the simultaneous offer strategy, as a mechanism known from economy, and suggest an approach for using it in the AiG negotiations.Key words: Grid computing, multiple equivalent simultaneous offers, AiG, agent-based negotiations, SLA, multi-attribute negotiations 1. Introduction. The context for the presented work is provided by the Agents in Grid project (AiG; [16,17,23]) that aims at creating a management system for the Grid computing resources. The system utilizes the concept of software agents that can act flexibly in a dynamic and uncertain environment, where resources can appear and disappear at any time. Furthermore, the AiG project integrates business principles, by allowing users to earn money by offering resources, or to pay for the use of available resources. The key part of the realization of this economic model is the negotiation process that should lead to contracts beneficial to the engaged parties. In the AiG project, negotiations materialize in the two main scenarios: (i) when the user would like to execute her job and is searching for resources that satisfy her needs, (ii) when a resource owner is seeking a team to join, to earn money. Here, we are confronted with one of the key assumptions behind the AiG project. Based on the analysis of working conditions of volunteer systems (e.g. seti@home; [32]), and taking into account progress in the development of agent systems (their capability for autonomously reaching an agreement [33]) it was stipulated that agents that offer their resources to earn money should work in teams. In this way, teams should be able to deliver results even if some members disappear without warning (for more details, see [16]).Observe that negotiations taking place in the AiG project have to take into account multiple attributes. In an example given in [23] simple job execution negotiations involved simultaneous evaluation of price, job start time and job end time. Currently, after the AiG ontology was fully developed (see, [22] for more details), truly multi-criterial negotiations can be used. Note that in both negotiation scenarios introduced above, the negotiation strategy is constrained by the following conditions: (1) no information about the preferences of the other participant(s) in the negotiation, and (2) the agreement reached should be optimal to both negotiating parties.Let us observe that recent studies in social psychology and economics [1,2] have shown that using a strategy based on multiple offers is more profitable than a strategy based on a single offe...

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Ontology for Contract Negotiations in an Agent-based Grid Resource Management System

Cited by 14 publications

References 0 publications

Combining AiG Agents with Unicore Grid for Improvement of User Support

Combining AiG Agents with Unicore Grid for Improvement of User Support

Reengineering and Extending the Agents in Grid Ontology

Multiple equivalent simultaneous offers strategy in an agent-based grid resource brokering system - initial considerations

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