Adaptive load sharing in homogeneous distributed systems
IEEE Transactions on Software Engineering
Caching Hints in Distributed Systems
IEEE Transactions on Software Engineering - Special issue on distributed systems
A Trace-Driven Simulation Study of Dynamic Load Balancing
IEEE Transactions on Software Engineering
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Proceedings of the International Workshop on Experiences with Distributed Systems
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IEEE Transactions on Software Engineering
Semi-Distributed Load Balancing for Massively Parallel Multicomputer Systems
IEEE Transactions on Software Engineering
The Influence of Scale on Distributed File System Design
IEEE Transactions on Software Engineering
Multitasking in high-speed interconnection systems
Computer Networks and ISDN Systems - Special issue on high speed networks
Scalable, Adaptive Load Sharing for Distributed Systems
IEEE Parallel & Distributed Technology: Systems & Technology
Methodical Analysis of Adaptive Load Sharing Algorithms
IEEE Transactions on Parallel and Distributed Systems
Scalability in distributed systems, parallel systems and supercomputers
HPCN Europe '95 Proceedings of the International Conference and Exhibition on High-Performance Computing and Networking
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Abstract: Powerful processors and high-bandwidth communications which are available provide a very large amount of cycles at supercomputer speeds. This can serve emerging data-intensive applications which require extremely high data rates. Workstations equipped with such processors are often utilized for a fraction of the time and sit idle otherwise. It may become possible to sell and buy computational power over the network in the same way that electrical power is sold and bought by utilities over the power grid today. Potential buyers are users in need of more cycles than those provided by their own workstations. A request made by a potential buyer can be directed to any of the sellers and a best match of buyer and seller (trading) has to be made. For scalability, traders use an extended version of the adaptive partitioning algorithm which may be applicable whenever mutual interest is clearly defined, i.e. a seller is interested in finding a buyer and vice versa. It is shown that server or client selection for buying or selling computation power over the network using adaptive partitioning is simple and efficient.