Efficient Distributed Workload (Re-)Embedding

Efficient Distributed Workload (Re-)Embedding

Abstract

Modern networked systems are increasingly reconfigurable, enabling demand-aware infrastructures whose resources can be adjusted according to the workload they currently serve. Such dynamic adjustments can be exploited to improve network utilization and hence performance, by moving frequently interacting communication partners closer, e.g., collocating them in the same server or datacenter. However, dynamically changing the embedding of workloads is algorithmically challenging: communication patterns are often not known ahead of time, but must be learned. During the learning process, overheads related to unnecessary moves (i.e., re-embeddings) should be minimized. This paper studies a fundamental model which captures the tradeoff between the benefits and costs of dynamically collocating communication partners on ℓ servers, in an online manner. Our main contribution is a distributed online algorithm which is asymptotically almost optimal, i.e., almost matches the lower bound (also derived in this paper) on the competitive ratio of any (distributed or centralized) online algorithm. As an application, we show that our algorithm can be used to solve a distributed union find problem in which the sets are stored across multiple servers.

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Authors
  • Henzinger, Monika
  • Neumann, Stefan
  • Schmid, Stefan
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Supplemental Material
Shortfacts
Category
Paper in Conference Proceedings or in Workshop Proceedings (Paper)
Event Title
ACM SIGMETRICS / IFIP Performance 2019
Divisions
Communication Technologies
Theory and Applications of Algorithms
Subjects
Informatik Allgemeines
Event Location
Phoenix, Arizona, USA
Event Type
Conference
Event Dates
June 2019
Date
June 2019
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