Remote Opportunities: A Rethinking and Retooling

Abstract Introducing technology as a sustainable means of creating, connecting, and collaborating reveals the need to carefully consider subtle aspects of deployment strategies and support in remote regions. In order to comprehensively address both cultural and technical issues for educational infrastructure, we consider two elements to be key: (1) a staged deployment approach, involving both educators and community members, coupled with (2) uniquely designed collaborative Integrated Development Environments (IDEs) to aid constructivism. This paper presents our current experience with these elements in the context of a pilot project for aboriginal communities on the west coast of British Columbia. Currently, these local communities have been working alongside our group for a staged deployment of programs throughout southern Vancouver Island. In our next phase we will be extending this to more remote regions in the north island and coastal regions. By building on a philosophy of CommunityDriven Initiatives for Technology (C-DIT), we hope to secure community involvement in the development and testing of necessary tool support. These tools specifically target IDEs for the development of programming skills, and support our long term goal to help secondary and postsecondary level students appreciate both the process and the art of programming

Dynamic Resource Allocation in Computing Clouds using Distributed Multiple Criteria Decision Analysis.

Abstract-In computing clouds, it is desirable to avoid wasting resources as a result of under-utilization and to avoid lengthy response times as a result of over-utilization. In this paper, we propose a new approach for dynamic autonomous resource management in computing clouds. The main contribution of this work is two-fold. First, we adopt a distributed architecture where resource management is decomposed into independent tasks, each of which is performed by Autonomous Node Agents that are tightly coupled with the physical machines in a data center. Second, the Autonomous Node Agents carry out configurations in parallel through Multiple Criteria Decision Analysis using the PROMETHEE method. Simulation results show that the proposed approach is promising in terms of scalability, feasibility and flexibility