Service-oriented Grid Architecture Research Articles

Authentication and authorisation in service-oriented grid architecture

Authentication and authorisation in service-oriented grid architecture

Authentication and authorisation in service-oriented grid architecture

Authentication and authorisation in service-oriented grid architecture

A Framework for Web service negotiation

In a survey on the theory and practice of agent system deployment, conducted by the AgentLink workgroup on networked agents, it was found that there are an increasing number of initiatives for the migration of agents research towards new Internet technologies such as the semantic web, Grid, and Web services. In fact, Grid computing and multi-agent systems research have similar objectives. They both aim to achieve “large-scale open distributed systems, capable of being able to effectively and dynamically deploy and redeploy computational (and other) resources as required, to solve computationally complex problems” [Foster and Kesselman 2003]. On the one hand, service-oriented Grid architectures need to support dynamic cooperation, negotiation, and adaptive interactions between Web services controlling Grid resources for efficient resource and task allocation and execution. On the other hand, the Grid can facilitate agent communication, life-cycle management, and access to resources for agents. Although the relevance of Grid for agent research and vice versa has been identified in several forums, actual collaborative applications are still in their infancy. In this article, we discuss our recent work on deploying multi-agent negotiation techniques to facilitate dynamic negotiation for Grid resources as a step closer to an adaptive and autonomous Grid. In particular, we describe a Web service development of the Contract Net Protocol for negotiation between insurance companies and repair companies. We evaluate our approach to show the added value of negotiable interactions between Web services as opposed to inflexible single-shot interactions that are currently the state of the art.

A Model of Grid Service Capacity

Computational grids (CGs) are large scale networks of geographically distributed aggregates of resource clusters that may be contributed by distinct organizations for the provision of computing services such as model simulation, compute cycle and data mining. Traditionally, the decision-making strategies underlying the grid management mechanisms rely on the physical view of the grid resource model. This entails the need for complex multi-dimensional search strategies and a considerable level of resource state information exchange between the grid management domains. In this paper we argue that with the adoption of service oriented grid architectures, a logical service-oriented view of the resource model provides a more appropriate level of abstraction to express the grid capacity to handle incoming service requests. In this respect, we propose a quantification model of the aggregated service capacity of the hosting environment that is updated based on the monitored state of the various environmental resources required by the hosted services. A comparative experimental validation of the model shows its performance towards enabling an adequate exploitation of provisioned services.

A Service Oriented Grid Architecture with End to End Quality of Service

Providing non-trivial QoS is one of the primary goals of the grid computing. Since extensive efforts have been made on the development of basic grid components such as execution framework and resource brokering system, there is still a great challenge to build up a QoS-enabled grid architecture for today's service grid. In this paper, a QoS-enabled service grid architecture (QESA) is proposed; the concept of differential guaranteed service is introduced to provide QoS guarantee at service layer; a QoS-aware service discovery and scheduling mechanism are designed to provide QoS guarantee for grid jobs. The performance of the QESA and related mechanisms has been evaluated by a grid application called AREM. The results show that QESA can provide QoS guarantee to grid jobs.

The Grid Economy

This work identifies challenges in managing resources in a Grid computing environment and proposes computational economy as a metaphor for effective management of resources and application scheduling. It identifies distributed resource management challenges and requirements of economy-based Grid systems, and discusses various representative economy-based systems, both historical and emerging, for cooperative and competitive trading of resources such as CPU cycles, storage, and network bandwidth. It presents an extensive, service-oriented Grid architecture driven by Grid economy and an approach for its realization by leveraging various existing Grid technologies. It also presents commodity and auction models for resource allocation. The use of commodity economy model for resource management and application scheduling in both computational and data grids is also presented.

JISGA: A Jini-Based Service-Oriented Grid Architecture

This paper describes how to extend a Jini system into an OGSA-compliant infrastructure for Grid computing by introducing Web service techniques into the Jini system. The Jini-based Service-oriented Grid Architecture (JISGA) is presented, the functionality of the system is described, and the main services and components of the system are discussed. The paper shows how to present a Jini service as a Web service, and how an application composed of interacting services can be described using the service workflow description language (SWFL). The conversion of a composite application specified in an SWFL document into an executable Java code, and its subsequent execution, are also discussed. This latter capability, enabled by the SWFL2Java tool, permits the blocking and non-blocking submission of jobs to the Grid, and their processing in both sequential and parallel execution modes.