A decentralized code resource sharing model for grid computing.

Grid computing is concerned with developing a conceptual infrastructure for resource sharing among geographically distributed virtual organizations. One important type of resource for Grid application developers is code resource, typically accessed through code repositories that store reusable software components. Current code resource sharing mechanisms use the client/server model, which does not support distributed code repositories. In this thesis, we approach the problem of distributed code resource sharing in Grid environment by proposing a new model that provides a decentralized, dynamic, scalable and heterogeneous solution. In our model, we use Peer-to-Peer (P2P) technology to support code resource sharing in Grid context. Within our prototype software system, every computer is a Grid servent node, which acts as both server and client by providing and requesting for reusable software components. Thus, a distributed code resource sharing community is established indeed. In this thesis we report on the design and implementation of a prototype code resource sharing software system. This system provides an effective way to aid Grid software developers to obtain access to distributed code resources in a decentralized way, featuring good economy and high autonomy within Grid networks. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .W35. Source: Masters Abstracts International, Volume: 43-01, page: 0246. Adviser: Robert Kent. Thesis (M.Sc.)--University of Windsor (Canada), 2004

The implementation of a GC/MS data system using DISNET: a Distributed Instrument System NETwork

The primary goal of a computer network is to achieve resource sharing between several computers. Resource sharing is most easily performed at the application program level, with lower layers of software providing communications services. Application programs which make local data, peripherals, or processes available for shared use are defined as ’resource providers’. Application programs which require such resources from the network are defined as ’resource consumers’. This distinction helps the system designer identify the qualities of resource providers and consumers necessary to address data communication problems in a straightforward manner, while ensuring the effort invested will provide satisfactory solutions. We have developed this resource sharing protocol for the Distributed Instrument System NETwork (DISNET) to provide an environment suitable for the development and growth of a distributed system for real-time instrument control, data acquisition, and computation in a laboratory environment

Resource dedication problem in a multi-project environment

Resource dedication problem (RDP) in a multi-project environment is defined as the optimal dedication of resource capacities to dierent projects within the overall limits of the resources with the objective of minimizing the sum of the weighted tardinesses of all projects. The projects involved are in general multi-mode resource constrained project scheduling problems (MRCPSP) with nish to start zero time lag and nonpreemtive activities. In general, approaches to multi-project scheduling consider the resources as a pool shared by all projects. When projects are distributed geographically or sharing resources between projects is too costly, then the resource sharing policy may not be appropriate and hence the resources are dedicated to individual projects throughout project durations. To the best of our knowledge, this point of view for resources is not considered in multi-project literature. In the following, we propose a solution methodology for RDP with a new local improvement heuristic by determining the resource dedications to individual projects and solving scheduling problems with the given resource limits

Multi-mode resource constrained multi-project scheduling and resource portfolio problem

This paper introduces a multi-project problem environment which involves multiple projects with assigned due dates; with activities that have alternative resource usage modes; a resource dedication policy that does not allow sharing of resources among projects throughout the planning horizon; and a total budget. There are three issues to face when investigating this multiproject environment. First, the total budget should be distributed among different resource types to determine the general resource capacities which correspond to the total amount for each renewable resource to be dedicated to the projects. With the general resource capacities at hand, the next issue is to determine the amounts of resources to be dedicated to the individual projects. With the dedication of resources accomplished, the scheduling of the projects' activities reduces to the multi-mode resource constrained project scheduling problem (MRCPSP) for each individual project. Finally the last issue is the effcient solution of the resulting MRCPSPs. In this paper, this multi-project environment is modeled in an integrated fashion and designated as the Resource Portfolio Problem. A two-phase and a monolithic genetic algorithm are proposed as two solution approaches each of which employs a new improvement move designated as the combinatorial auction for resource portfolio and the combinatorial auction for resource dedication. Computational study using test problems demonstrated the effectiveness of the solution approach proposed