@inproceedings{3a6fe82e71bf45f7ae79254a32c7f2b6,

title = "Revisiting randomized parallel load balancing algorithms",

abstract = "We deal with the well studied allocation problem of assigning n balls to n bins so that the maximum number of balls assigned to the same bin is minimized. We focus on randomized, constant-round, distributed, asynchronous algorithms for this problem. Adler et al. [1] presented lower bounds and upper bounds for this problem. A similar lower bound appears in Berenbrink et al. [2]. The lower bound is based on a topological assumption. Our first contribution is the observation that the topological assumption does not hold for two algorithms presented by Adler et al. [1]. We amend this situation by presenting direct proofs of the lower bound for these two algorithms. We present an algorithm in which a ball that was not allocated in the first round retries with a new choice in the second round. We present tight bounds on the maximum load obtained by our algorithm. The analysis is based on analyzing the expectation and transforming it to a bound with high probability using martingale tail inequalities. Finally, we present a 3-round heuristic with a single synchronization point. We conducted experiments that demonstrate its advantage over parallel algorithms for 106 ≤ n ≤ 108 balls and bins. In fact, the obtained maximum load meets the best results for sequential algorithms.",

keywords = "Balls and bins, Load balancing, Martingales, Static randomized parallel allocation",

author = "Guy Even and Moti Medina",

year = "2010",

doi = "10.1007/978-3-642-11476-2_17",

language = "אנגלית",

isbn = "364211475X",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "209--221",

booktitle = "Structural Information and Communication Complexity - 16th International Colloquium, SIROCCO 2009, Revised Selected Papers",

note = "null ; Conference date: 25-05-2009 Through 27-05-2009",

}