Near-Optimal Scheduling of Distributed Algorithms

This paper studies the question of how to run many distributed algorithms, solving independent problems, together as fast as possible. Suppose that we want to run distributed algorithms A1, A2 . . . , Ak in the CONGEST model, each taking at most dilation rounds, and where for each network edge, at most congestion messages need to go through it, in total over all these algorithms. A celebrated work of Leighton, Maggs, and Rao [22] shows that in the special case where each of these algorithms is simply a packet routing—that is, sending a message from a source to a destination along a given path—there is an O(congestion + dilation) round schedule. Note that this bound is trivially optimal. Generalizing the framework of LMR [22], we study scheduling general distributed algorithms and present two results: (a) an existential schedule-length lower bound of Ω(congestion +dilation· log n log log n ) rounds, (b) a distributed algorithm that produces a near-optimal O(congestion+dilation·...

• Type: Journal
• Year: 2015
• Where: PODC
• Authors: Mohsen Ghaffari
• Keywords: Distributed And Parallel Computing, PODC 2015