A scalability analysis of grid allocation mechanisms

This article examines the broker's behavior with regard to a varying number of participating nodes and shows that incremental losses have to be accepted in central resource allocation when introducing new nodes. --Grid Computing

Automated Federation Of Virtual Organization In Grid Using Select, Match, Negotiate And Expand (SMNE) Protocol [QA76.9.C58 C518 2008 f rb].

Sekelompok sumber perkomputeran yang teragih dan berlainan jenis dalam persekitaran grid akan membentuk organisasi maya dan berkongsi sumber komputer. A group of distributed and heterogeneous resources in a grid environment may form a Virtual Organization (VO) to enable resource sharing

Automated Bidding in Computing Service Markets. Strategies, Architectures, Protocols

This dissertation contributes to the research on Computational Mechanism Design by providing novel theoretical and software models - a novel bidding strategy called Q-Strategy, which automates bidding processes in imperfect information markets, a software framework for realizing agents and bidding strategies called BidGenerator and a communication protocol called MX/CS, for expressing and exchanging economic and technical information in a market-based scheduling system

Performance Evaluation - Annual Report Year 3

This report describes the work done and results obtained in third year of the CATNETS project. Experiments carried out with the different configurations of the prototype are reported and simulation results are evaluated with the CATNETS metrics framework. The applicability of the Catallactic approach as market model for service and resource allocation in application layer networks is assessed based on the results and experience gained both from the prototype development and simulations. --Grid Computing

Using Semantic Web Technology to Design Agent-to-Agent Argumentation Mechanism in an E-Marketplace

In existing e-marketplaces, buyers can use search engines to find products that exactly match their demands, but some products those are potentially interesting to them cannot be found out. This research aims to design a multi-agent e-marketplace in which buyers and sellers can delegate their agents to argue over product attributes via an agent-to-agent argumentation mechanism. A seller agent is able to persuade a buyer agent to believe the seller’s product is interesting to the buyer. To make this idea possible, this research adopts the Semantic Web technology to express agents’ ontologies and uses an abstract argumentation framework with dialectical game approach to support defeasible reasoning. This research hopes the proposed architecture and approach can help buyers to find out potential interesting products and help sellers to increase revenue through their agents and help existing and initiative e-marketplaces to design their argumentation mechanisms

Rational bidding using reinforcement learning: an application in automated resource allocation

The application of autonomous agents by the provisioning and usage of computational resources is an attractive research field. Various methods and technologies in the area of artificial intelligence, statistics and economics are playing together to achieve i) autonomic resource provisioning and usage of computational resources, to invent ii) competitive bidding strategies for widely used market mechanisms and to iii) incentivize consumers and providers to use such market-based systems. The contributions of the paper are threefold. First, we present a framework for supporting consumers and providers in technical and economic preference elicitation and the generation of bids. Secondly, we introduce a consumer-side reinforcement learning bidding strategy which enables rational behavior by the generation and selection of bids. Thirdly, we evaluate and compare this bidding strategy against a truth-telling bidding strategy for two kinds of market mechanisms – one centralized and one decentralized

Analysis Of Aircraft Arrival Delay And Airport On-time Performance

While existing grid environments cater to specific needs of a particular user community, we need to go beyond them and consider general-purpose large-scale distributed systems consisting of large collections of heterogeneous computers and communication systems shared by a large user population with very diverse requirements. Coordination, matchmaking, and resource allocation are among the essential functions of large-scale distributed systems. Although deterministic approaches for coordination, matchmaking, and resource allocation have been well studied, they are not suitable for large-scale distributed systems due to the large-scale, the autonomy, and the dynamics of the systems. We have to seek for nondeterministic solutions for large-scale distributed systems. In this dissertation we describe our work on a coordination service, a matchmaking service, and a macro-economic resource allocation model for large-scale distributed systems. The coordination service coordinates the execution of complex tasks in a dynamic environment, the matchmaking service supports finding the appropriate resources for users, and the macro-economic resource allocation model allows a broker to mediate resource providers who want to maximize their revenues and resource consumers who want to get the best resources at the lowest possible price, with some global objectives, e.g., to maximize the resource utilization of the system