Showing papers by "Peter F. Linington published in 2011"

Building Enterprise Systems with ODP: An Introduction to Open Distributed Processing

Abstract: The Reference Model of Open Distributed Processing (RM-ODP) is an international standard that provides a solid basis for describing and building widely distributed systems and applications in a systematic way. It stresses the need to build these systems with evolution in mind by identifying the concerns of major stakeholders and then expressing the design as a series of linked viewpoints. Although RM-ODP has been a standard for more than ten years, many practitioners are still unaware of it. Building Enterprise Systems with ODP: An Introduction to Open Distributed Processing offers a gentle pathway to the essential ideas that constitute ODP and shows how these ideas can be applied when designing and building challenging systems. It provides an accessible introduction to the design principles for software engineers and enterprise architects. The book also explains the benefits of using viewpoints to produce simpler and more flexible designs and how ODP can be applied to service engineering, open enterprise, and cloud computing. The authors include guidelines for using the Unified Modeling Language (UML) notation and for structuring and writing system specifications. They elucidate how this fits into the model-driven engineering tool chain via approaches, such as Model-Driven Architecture (MDA). They also demonstrate the power of RM-ODP for the design and organization of complex distributed IT systems in e-government, e-health, and energy and transportation industries. All concepts and ideas in the book are illustrated through a single running example that describes the IT support needed by a medium-sized company as it grows and develops. Complete UML models and more are available at http://theodpbook.lcc.uma.es/

A P2P Based Scheduler for Home Grids

Abstract: This work presents a P2P based grid scheduling system for highly dynamic and highly heterogeneous environments, such as home networks, where we can find a variety of devices (laptops, PCs, game consoles, etc.) and networks. Our solution is based on the distribution of the matchmaking task among providers, leaving the final allocation decision to a central scheduler that can be running on a limited device without a big loss in performance. We evaluate our solution by simulating different scenarios and configurations against the Opportunistic Load Balance (OLB) scheduling heuristic, which we found to be the best option for home grids from the existing solutions that we analyzed. The results have shown that our solution performs similar to or better than OLB.