Pervasive Grids: Challenges and Opportunities

Pervasive Grids: Challenges and Opportunities

Manish Parashar (Rutgers - The State University of New Jersey, USA) and Jean-Marc Pierson (Paul Sabatier University, France)
Copyright: © 2010 |Pages: 17
DOI: 10.4018/978-1-60566-661-7.ch002
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Abstract

Pervasive Grid is motivated by the advances in Grid technologies and the proliferation of pervasive systems, and is leading to the emergence of a new generation of applications that use pervasive and ambient information as an integral part to manage, control, adapt and optimize. However, the inherent scale and complexity of Pervasive Grid systems fundamentally impact how applications are formulated, deployed and managed, and presents significant challenges that permeate all aspects of systems software stack. In this chapter, the authors present some use-cases of Pervasive Grids and highlight their opportunities and challenges. They then present why semantic knowledge and autonomic mechanisms are seen as foundations for conceptual and implementation solutions that can address these challenges.
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Introduction

Grid computing has emerged as the dominant paradigm for wide-area distributed computing (Parashar & Lee, 2005). The goal of the original Grid concept is to combine resources spanning many organizations into virtual organizations that can more effectively solve important scientific, engineering, business and government problems. Over the last decade, significant resources and research efforts have been devoted towards making this vision a reality and have lead to the development and deployment of a number of Grid infrastructures targeting a variety of applications.

However, recent technical advances in computing and communication technologies and associated cost dynamics are rapidly enabling a ubiquitous and pervasive world - one in which the everyday objects surrounding us have embedded computing and communication capabilities and form a seamless Grid of information and interactions. As these technologies weave themselves into the fabrics of everyday life (Weiser, 1991), they have the potential of fundamentally redefining the nature of applications and how they interact with and use information.

This leads to a new revolution in the original Grid concept and the realization of a Pervasive Grid vision. The Pervasive Grid vision is driven by the advances in Grid technologies and the proliferation of pervasive systems, and seamlessly integrates sensing/actuating instruments and devices together with classical high performance systems as part of a common framework that offers the best immersion of users and applications in the global environment. This is, in turn, leading to the emergence of a new generation of applications using pervasive and ambient information as an integral part to manage, control, adapt and optimize (Pierson, 2006; Matossian et al., 2005; Bangerth, Matossian, Parashar, Klie, &Wheeler, 2005; Parashar et al., 2006). These applications include a range of application areas including crisis management, homeland security, personal healthcare, predicting and managing natural phenomenon, monitoring and managing engineering systems, optimizing business processes, etc (Baldridge et al., 2006).

Note that it is reasonable to argue that in concept, the vision of Pervasive Grids was inherent in the visions of “computing as a utility” originally by Corbat et al (Corbat & Vyssotsky, 1965) and later by Foster et al (Foster, Kesselman, & Tuecke, 2001). In this sense, Pervasive Grids are the next significant step towards realizing the metaphor of the power grid. Furthermore, while, Foster et al., defined a computational Grid in (Foster & Kesselman, 1999) as “... a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities”, the term pervasive in this definition refers to the transparent access to resources rather than the nature of the resources themselves. Pervasive Grids focus on the latter and essentially address an extreme generalization of Grid concept where the resources are pervasive and include devices, services, information, etc.

The aim of this chapter is to introduce the vision of Pervasive Grid computing and to highlight its opportunities and challenges. In this paper we first described the nature of applications in a Pervasive Grid and outline their requirements. We then describe key research challenges, and motivate semantic knowledge and autonomic mechanisms as the foundations for conceptual and implementation solutions that can address these challenges.

Key Terms in this Chapter

Autonomic Computing: Accounts for a system that does not need human intervention to work, repair, adapt and optimize. Autonomous entities must adapt to their usage context to find the best fit for their execution.

Grid: The goal of the original Grid concept is to combine resources spanning many organizations into virtual organizations that can more effectively solve important scientific, engineering, business and government problems.

Pervasive: A term that covers the ubiquity of the system. A pervasive system is transparent to its users that use it without noticing it. It is often linked with mobility since it helps to cover the anywhere/anytime resources access for nomadic users.

Quality of Service: Designs the achievable performances that a system, an application or a service is expected to deliver to its consumers.

Pervasive Grid: A pervasive grid mixes a grid resource sharing with an anywhere/anytime access to these resources, either data or computing resources.

Semantic Knowledge: Designs the enriched value of the information. Raw information coming from sensors or monitored by the system is not enough to achieve ubiquitous access to resources. Only higher level abstractions allow for handling seamlessly the system.

Uncertainty: The dubiety that can be put on the system, the application or the information in a pervasive grid. Information cannot be accepted without doubt and double checking, redundancy, is often the rule.

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