On the Assignment Problem of Arbitrary Process Systems to Heterogeneous Distributed Computer Systems

The authors propose and evaluate an efficient hierarchical clustering and allocation algorithm that drastically reduces the interprocess communications cost while observing lower and upper bounds of utilization for the individual processors. They compare the algorithm with branch-and-bound-type algorithms that can produce allocations with minimal communication cost, and show a very encouraging time complexity/suboptimality tradeoff in favor of the algorithm, at least for a class of process clusters and their random combinations which it is believed occur naturally in distributed applications. The heuristic allocation is well suited for a changing environment, where processors may fail or be added to the system and where the workload patterns may change unpredictably and/or periodically. >

[1]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[2]  Donald F. Ferguson,et al.  Relocating Processes in Distributed Computer Systems , 1986, Symposium on Reliability in Distributed Software and Database Systems.

[3]  Andrew S. Tanenbaum,et al.  Distributed operating systems , 2009, CSUR.

[4]  Wesley W. Chu,et al.  Estimation of Intermodule Communication (IMC) and Its Applications in Distributed Processing Systems , 1984, IEEE Transactions on Computers.

[5]  Robin Liggett,et al.  The Quadratic Assignment Problem: An Experimental Evaluation of Solution Strategies , 1981 .

[6]  Andrew B. Whinston,et al.  On Optimal Allocation in a Distributed Processing Environment , 1982 .

[7]  Amnon Barak,et al.  A distributed load‐balancing policy for a multicomputer , 1985, Softw. Pract. Exp..

[8]  Lawrence J. Watters Letter to the Editor - Reduction of Integer Polynomial Programming Problems to Zero-One Linear Programming Problems , 1967, Oper. Res..

[9]  Harold S. Stone,et al.  Assignment of Tasks in a Distributed Processor System with Limited Memory , 1979, IEEE Transactions on Computers.

[10]  Philip S. Yu,et al.  Analysis of Affinity Based Routing in Multi-System Data Sharing , 1987, Perform. Evaluation.

[11]  Harold S. Stone,et al.  Multiprocessor Scheduling with the Aid of Network Flow Algorithms , 1977, IEEE Transactions on Software Engineering.

[12]  Miron Livny,et al.  Load balancing in homogeneous broadcast distributed systems , 1982, SIGMETRICS 1982.

[13]  Boontee Kruatrachue,et al.  Grain size determination for parallel processing , 1988, IEEE Software.

[14]  Keshab K. Parhi,et al.  Static Rate-Optimal Scheduling of Iterative Data-Flow Programs via Optimum Unfolding , 1991, IEEE Trans. Computers.

[15]  Raphael A. Finkel,et al.  A Stable Distributed Scheduling Algorithm , 1981, IEEE International Conference on Distributed Computing Systems.

[16]  Jacob Hagouel,et al.  Issues in routing for large and dynamic networks , 1983 .

[17]  Ten-Hwang Lai,et al.  Mapping Pyramid Algorithms into Hypercubes , 1990, J. Parallel Distributed Comput..

[18]  Shahid H. Bokhari,et al.  On the Mapping Problem , 1981, IEEE Transactions on Computers.

[19]  Edward D. Lazowska,et al.  Dynamic load sharing in homogenous distributed systems , 1985 .

[20]  Rami G. Melhem,et al.  Embedding Rectangular Grids into Square Grids with Dilation Two , 1990, IEEE Trans. Computers.

[21]  Kemal Efe,et al.  Heuristic Models of Task Assignment Scheduling in Distributed Systems , 1982, Computer.