Resource Discovery in a dynamical grid based on Re-routing Tables

Abstract

This paper studies the Resource Discovery problem in a dynamical grid based on a grid-router model. This model suggests that the grid can be seen as an environment comprised by routers and resources, where each router is in charge of its local resources. We address the Grid Resource Discovery problem as a problem of discovering the appropriate resource for a specific request within that environment. Attempting to solve the Grid Resource Discovery problem, several mechanisms have been proposed in the past. One of those mechanisms is the Routing Tables mechanism, which can guarantee finding the appropriate resource for a specific request within a static grid environment, where resources are permanently online, connected in the grid. This paper investigates the effectiveness of a Routing Tables mechanism, called Re-routing Tables which can guarantee finding the appropriate resource in a dynamical grid environment, where resources could disconnect from the grid, and therefore get in an offline state. Due to an offline resource situation, the resource request must be re-routed in order to be satisfied.

Introduction

The term “Grid” was introduced in early 1998 with the publication of the book “The Grid: Blueprint for a new computing infrastructure”. Until then researchers and scientists referred to “the computing resources transparently available to the user via a networked environment” with the terms metasystem or metacomputer [23], [24], [25]. The release of this book laid the groundwork of the field and provided definitions regarding that field. Since that time, many technological changes have occurred in computer science resulting to the evolution of the grid technology. Therefore, the need for clear definitions and descriptions about the grid technologies is now more than obvious, mainly because new aspects of the grid need to be included [1].

In [2], the authors extracted characteristics and definitions from main grid literature sources in order to provide a clear and complete grid definition. According to the list of characteristics extracted from literature, a grid can be defined as “a large-scale, geographically distributed, hardware and software infrastructure composed of heterogeneous networked resources owned and shared by multiple administrative organizations which are coordinated to provide transparent, dependable, pervasive and consistent computing support to a wide range of applications. These applications can perform distributed computing [26], [28], high throughput computing, on-demand computing [30], data-intensive computing [29], collaborative computing or multimedia computing”.

It is obvious, that the base of grid technology is the concept of resource sharing. The types of resources shared in a grid infrastructure could be desktop systems, clusters, storage devices and large data-sets. The question is what happens when a remote user requests access to a remote resource either to execute a job or to have access in the resource’s data? A mechanism provided by the grid infrastructure should be available to discover an appropriate resource for a request. Therefore, one of the main capabilities a grid infrastructure needs to support is a Resource Discovery mechanism [3].

Discovering a specific resource in traditional computing environments is relatively easy because the number of shared resources is small and all resources are under central control. In a grid environment, there are certain factors that make the resource discovery problem difficult to solve. These factors are: the huge number of resources, distributed ownership, heterogeneity of resources, resource failure, and resource evolution (upgrades changing a resource’s technical characteristics). An efficient Resource Discovery mechanism should take into consideration the above factors.

Another important aspect in a grid infrastructure is the dynamicity of such a system. Resources, shared in a grid, exist in two states: online and offline. Not all resources are permanently online in a grid. A resource’s state could change during time from online to offline and backwards. The main reason that this happens is the distributed ownership of grid resources. An owner may establish a policy on a workstation that states that a foreign job can be run on a machine only at certain periods of time. Another reason for a resource to exit the grid, therefore get in an offline state, is due to heavy local load. An owner may establish a policy on a workstation that states that a foreign job can be run on a machine when the local load is under a certain limit. When the local load reaches that limit, a resource must exit the grid and execute local jobs only. Finally, the huge number of resources in a grid increases the probabilities of resource failures. Resource failures are unpredictable and common due to hardware faults, software faults or power outages.

Taken into consideration the dynamicity that characterizes a grid system, we propose a new framework for resource discovery based on Routing Tables, called Re-routing Tables. Based on a large number of tests, we investigate the effectiveness of the Re-routing Tables mechanism which can guarantee finding the appropriate resource in a dynamical grid environment, where resources could disconnect from the grid, and therefore get in an offline state.

This paper is organized as follows: Section 2 presents related work on resource discovery in a grid environment. Section 3 describes the Resource Discovery mechanism based on Routing Tables. Section 4 describes our deployed framework of the Re-routing Tables mechanism. Section 5 presents experiments and testing of the mechanism.