A Fair Comparison of Pull and Push Strategies in Large Distributed Networks

In this paper, we compare the performance of the pull and push strategies in a large homogeneous distributed system. When a pull strategy is in use, lightly loaded nodes attempt to steal jobs from more highly loaded nodes, while under the push strategy, more highly loaded nodes look for lightly loaded nodes to process some of their jobs. Given the maximum allowed overall probe rate R and arrival rate λ, we provide closed-form solutions for the mean response time of a job for the push and pull strategy under the infinite system model. More specifically, we show that the push strategy outperforms the pull strategy for any probe rate % > 0 when λ <; φ-1, where φ = (1 +√5)/2 ≈ 1.6180 is the golden ratio. More generally, we show that the push strategy prevails if and only if 2λ <; √(R+1)2 + 4(R+1) √ (R+1). We also show that under the infinite system model, a hybrid pull-and-push strategy is always inferior to the pure pull or push strategy. The relation between the finite and infinite system model is discussed, and simulation results that validate the infinite system model are provided.

[1]  J. A. Walker,et al.  Dynamical Systems and Evolution Equations , 1980 .

[2]  M. Benaïm,et al.  A class of mean field interaction models for computer and communication systems , 2008, 2008 6th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks and Workshops.

[3]  Edward D. Lazowska,et al.  A Comparison of Receiver-Initiated and Sender-Initiated Adaptive Load Sharing , 1986, Perform. Evaluation.

[4]  James R. Larus,et al.  Join-Idle-Queue: A novel load balancing algorithm for dynamically scalable web services , 2011, Perform. Evaluation.

[5]  J. Norris Appendix: probability and measure , 1997 .

[6]  Jean-Yves Le Boudec,et al.  A class of mean field interaction models for computer and communication systems , 2008, WiOpt.

[7]  Donald F. Towsley,et al.  Analysis of the Effects of Delays on Load Sharing , 1989, IEEE Trans. Computers.

[8]  Bruno Gaujal,et al.  A mean field model of work stealing in large-scale systems , 2010, SIGMETRICS '10.

[9]  Benny Van Houdt,et al.  Performance Comparison of Aggressive Push and Traditional Pull Strategies in Large Distributed Systems , 2011, QEST.

[10]  Donald F. Towsley,et al.  Adaptive Load Sharing in Heterogeneous Distributed Systems , 1990, J. Parallel Distributed Comput..

[11]  T. K. Caughey,et al.  Dynamical Systems and Evolution Equations: Theory and Applications , 1980 .

[12]  T. Kurtz Approximation of Population Processes , 1987 .

[13]  Jean-Yves Le Boudec,et al.  On Mean Field Convergence and Stationary Regime , 2011, ArXiv.

[14]  Moshe Shaked,et al.  Stochastic orders and their applications , 1994 .

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

[16]  Michael Mitzenmacher,et al.  Analyses of Load Stealing Models Based on Families of Differential Equations , 2000, Theory of Computing Systems.

[17]  Edward D. Lazowska,et al.  Adaptive load sharing in homogeneous distributed systems , 1986, IEEE Transactions on Software Engineering.

[18]  Mark S. Squillante,et al.  Analysis of task migration in shared-memory multiprocessor scheduling , 1991, SIGMETRICS '91.

[19]  K. Deimling Ordinary differential equations in Banach spaces , 1977 .

[20]  R. L. Dobrushin,et al.  Queueing system with selection of the shortest of two queues: an assymptotic approach , 1996 .