MARO - MinDrift affinity routing for resource management in heterogeneous computing systems

This paper deals with designing effective resource management strategies for systems of heterogeneous computers. Each computer is represented as an abstract server, capable of serving different task demands at different rates. We consider a system with I types of independent Poisson task demand arrival streams and J parallel servers with independent non-identical processing time distributions for each arrival type. The decision of routing each type i task immediately upon arrival to a server j is made by comparing the state information of a subset of the J servers. We show that choosing the subset according to a linear programming (LP) problem which maximizes the system capacity can not only significantly reduce the amount of state information required in making the routing decision, but also yield shorter total mean queue length (and hence mean time in system) compared with the policies requiring global state information. In addition, we explore means of limiting flexibility to further reduce the required state information.

[1]  Francine Berman,et al.  Heuristics for scheduling parameter sweep applications in grid environments , 2000, Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556).

[2]  Michael Mitzenmacher,et al.  How Useful Is Old Information? , 2000, IEEE Trans. Parallel Distributed Syst..

[3]  Ian T. Foster,et al.  The Anatomy of the Grid: Enabling Scalable Virtual Organizations , 2001, Int. J. High Perform. Comput. Appl..

[4]  Ali Sharifnia,et al.  Instability of the Join-the-Shortest-Queue and FCFS Policies in Queueing Systems and Their Stabilization , 1997, Oper. Res..

[5]  Anthony A. Maciejewski,et al.  Dynamically mapping tasks with priorities and multiple deadlines in a heterogeneous environment , 2007, J. Parallel Distributed Comput..

[6]  R. F. Freund,et al.  Scheduling resources in multi-user, heterogeneous, computing environments with SmartNet , 1998, Proceedings Seventh Heterogeneous Computing Workshop (HCW'98).

[7]  Michael Mitzenmacher,et al.  The Power of Two Choices in Randomized Load Balancing , 2001, IEEE Trans. Parallel Distributed Syst..

[8]  Alexander L. Stolyar,et al.  OPTIMAL ROUTING IN OUTPUT-QUEUED FLEXIBLE SERVER SYSTEMS , 2005, Probability in the Engineering and Informational Sciences.

[9]  Douglas G. Down,et al.  Linear Programming Based Affinity Scheduling for Heterogeneous Computing Systems , 2007, PDPTA.

[10]  Richard Wolski,et al.  Fault-aware scheduling for Bag-of-Tasks applications on Desktop Grids , 2006, 2006 7th IEEE/ACM International Conference on Grid Computing.

[11]  Sigrún Andradóttir,et al.  Dynamic Server Allocation for Queueing Networks with Flexible Servers , 2003, Oper. Res..

[12]  Rajkumar Buyya,et al.  A taxonomy and survey of grid resource management systems for distributed computing , 2002, Softw. Pract. Exp..

[13]  William Gropp,et al.  Beowulf Cluster Computing with Linux , 2003 .

[14]  R. F. Freund,et al.  Dynamic matching and scheduling of a class of independent tasks onto heterogeneous computing systems , 1999, Proceedings. Eighth Heterogeneous Computing Workshop (HCW'99).