Optimal allocation of resources in distributed information networks
ACM Transactions on Database Systems (TODS) - Special issue: papers from the international conference on very large data bases: September 22–24, 1975, Framingham, MA
Open, Closed, and Mixed Networks of Queues with Different Classes of Customers
Journal of the ACM (JACM)
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Journal of the ACM (JACM)
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Journal of the ACM (JACM)
Database Location in Computer Networks
Journal of the ACM (JACM)
The Operational Analysis of Queueing Network Models
ACM Computing Surveys (CSUR)
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Communications of the ACM
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Communications of the ACM
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Communications of the ACM
Some Extensions to Multiclass Queueing Network Analysis
Proceedings of the Third International Symposium on Modelling and Performance Evaluation of Computer Systems: Performance of Computer Systems
File allocation in distributed systems
SIGMETRICS '76 Proceedings of the 1976 ACM SIGMETRICS conference on Computer performance modeling measurement and evaluation
Optimal branching probabilities and their relationship to computer network file distribution.
Optimal branching probabilities and their relationship to computer network file distribution.
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IEEE Transactions on Computers
Optimal Assignments in Broadcast Networks
IEEE Transactions on Computers
Simulation of a distributed database system incorporating a routing optimizer
ANSS '85 Proceedings of the 18th annual symposium on Simulation
Modeling reentrant and nonreentrant software
SIGMETRICS '82 Proceedings of the 1982 ACM SIGMETRICS conference on Measurement and modeling of computer systems
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Given a collection of distributed programs and the modules they use, the module allocation problem is to determine an assignment of modules to processors that minimizes the total execution cost of the programs. Standard approaches to this problem are based on solving either a network flow problem or a constrained 0-1 integer programming problem. In this paper we discuss an alternative approach to the module allocation problem where a closed, multiclass queueing network is solved to determine the cost of a particular module allocation. The advantage of this approach is that the execution cost can be expressed in terms of performance measures of the system such as response time. An interchange heuristic is proposed as a method of searching for a good module allocation using this model and empirical evidence for the success of the heuristic is given. The heuristic normally finds module allocations with costs within 10 percent of the optimal module allocation. Fast, approximate queueing network solution techniques based on mean-value-analysis allow each heuristic search to be completed in a few seconds of CPU time. The computational complexity of each search is O (M K (K + N) C) where M is the number of modules, K is the number of sites in the network, N is the number of communications processors, and C is the number of distributed program types. It appears that substantial problems of this type could be solved using the methods we describe.