Dynamic load distribution for parallel applications is one of the most important topics of research in the area of parallel and distributed systems. The German Science Foundation has been support- ing research in this area by funding SFB 342 "Methods and Tools for the efficient Use of Parallel Systems" and GK "Cooperation and Resource-Management in Distributed Systems" since 1990 and 1995 respectively. This manuscript is the result of research in both projects done jointly in the department for informatics and electrical ...
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Dynamic load distribution for parallel applications is one of the most important topics of research in the area of parallel and distributed systems. The German Science Foundation has been support- ing research in this area by funding SFB 342 "Methods and Tools for the efficient Use of Parallel Systems" and GK "Cooperation and Resource-Management in Distributed Systems" since 1990 and 1995 respectively. This manuscript is the result of research in both projects done jointly in the department for informatics and electrical engineering of Technische Universitlit Munchen as well as by the industrial partner Corporate Research of Siemens AG, Munich. First, surveys and classifications of existing models and implementations are given. Based on this comprehensive framework, several systems for checkpointing, a distributed thread kernel, load distribution in large workstation networks, and adaptive load distribution systems have been implemented and tested. The structure and results obtained with such systems are also covered. Finally a middleware -based architecture and three application areas are used to test the systems described beforehand. Understanding the needs of large distributed applications and the efficient use of heterogenous networked resources is most important to make good use of the distributed computing power as it is available worldwide in the internet and also on a private basis in intranets. This manuscript will help the reader to understand the questions and can serve as a basis for future research and development as well as in training for distributed applications.
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