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ACM Transactions on Database Systems (TODS)
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STOC '90 Proceedings of the twenty-second annual ACM symposium on Theory of computing
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ACM Transactions on Database Systems (TODS)
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IEEE Transactions on Software Engineering
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A Competitive Dynamic Data Replication Algorithm
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OOPSLA '03 Companion of the 18th annual ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
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IBM Systems Journal
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ACM SIGCOMM Computer Communication Review
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The VLDB Journal — The International Journal on Very Large Data Bases
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Engineering Applications of Artificial Intelligence
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Engineering Applications of Artificial Intelligence
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ACM Transactions on Embedded Computing Systems (TECS)
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As component-based development matures, more and more applications are built by integrating multiple distributed components. We suggest providing components with multiple implementations, each optimized for a particular workload, and augmenting the component run-time environment with a mechanism for switching between implementations. This mechanism monitors the types of requests the component is receiving, and adaptively switches implementations for optimal application performance. Achieving this optimal performance depends on making good choices as to when and how to switch implementations, a problem we refer to as the adaptive component problem. We first formalize the generic problem and then provide an algorithm, named Delta, for switching implementations in the special case when the component has exactly two implementations. We show that this algorithm is (3 + )-competitive with respect to the optimal algorithm, where is a small fraction. We establish a 3-competitive lower bound for the problem, which implies that Delta is close to optimal. We describe the application of these results to the distributed pub/sub problem, and the data structure selection problem.