Adaptive load sharing in heterogeneous distributed systems
Journal of Parallel and Distributed Computing
Economic models for allocating resources in computer systems
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Principles of distributed database systems (2nd ed.)
Principles of distributed database systems (2nd ed.)
SIAM Journal on Computing
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The VLDB Journal — The International Journal on Very Large Data Bases
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WWW '03 Proceedings of the 12th international conference on World Wide Web
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ICDE '99 Proceedings of the 15th International Conference on Data Engineering
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ICPP '00 Proceedings of the 2000 International Workshop on Parallel Processing
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CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
The power of two choices in randomized load balancing
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ODBASE'06/OTM'06 Proceedings of the 2006 Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, DOA, GADA, and ODBASE - Volume Part I
SQLB: a query allocation framework for autonomous consumers and providers
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
A self-adaptable query allocation framework for distributed information systems
The VLDB Journal — The International Journal on Very Large Data Bases
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In large-scale distributed information systems, providers are typically autonomous, i.e. free to leave the system at will or to perform certain requests. In this context, request allocation is critical for the efficient system's operation. However, most methods used in distributed information systems aim at maximizing overall system performance (throughput and response times) by allocating requests to the most efficient providers, without considering providers' autonomy. In this paper, we propose a balanced request allocation method, KnBest, which considers providers' autonomy in addition to load balancing. Our method is general and simple, so that it can be easily incorporated in existing distributed information systems. We describe the implementation of KnBest in different scenarios. Finally, we give an experimental evaluation which shows that KnBest significantly outperforms traditional request allocation methods.