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Kinetically stable task assignment for networks of microservers

Published: 19 April 2006 Publication History

Abstract

This paper studies task assignment in a network of resource constrained computing platforms (called microservers). A task is an abstraction of a computational agent or data that is hosted by the microservers. For example, in an object tracking scenario, a task represents a mobile tracking agent, such as a vehicle location update computation, that runs on microservers, which can receive sensor data pertaining to the object of interest. Due to object motion, the microservers that can observe a particular object change over time and there is overhead involved in migrating tasks among microservers. Furthermore, communication, processing, or memory constraints, allow a microserver to only serve a limited number of objects at the same time. Our overall goal is to assign tasks to microservers so as to minimize the number of migrations, and thus be kinetically stable, while guaranteeing that as many tasks as possible are monitored at all times. When the task trajectories are known in advance, we show that this problem is NP-complete (even over just two time steps), has an integrality gap of at least 2, and can be solved optimally in polynomial time if we allow tasks to be assigned fractionally. When only probabilistic information about future movement of the tasks is known, we propose two algorithms: a multi-commodity flow based algorithm and a maximum matching algorithm. We use simulations to compare the performance of these algorithms against the optimum task allocation strategy.

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Cited By

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  • (2012)Efficient Allocation of Agent Groups for Complex Tasks in Real Cost EnvironmentsProceedings of the 2012 IEEE International Conference on Software Science, Technology and Engineering10.1109/SWSTE.2012.14(54-62)Online publication date: 12-Jun-2012
  • (2010)Enabling rich mobile applicationsACM SIGMOBILE Mobile Computing and Communications Review10.1145/1710130.171013313:3(14-25)Online publication date: 21-Jan-2010
  • (2008)Distributed Operator Placement and Data Caching in Large-Scale Sensor NetworksIEEE INFOCOM 2008 - The 27th Conference on Computer Communications10.1109/INFOCOM.2008.151(977-985)Online publication date: Apr-2008
  • Show More Cited By

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cover image ACM Conferences
IPSN '06: Proceedings of the 5th international conference on Information processing in sensor networks
April 2006
514 pages
ISBN:1595933344
DOI:10.1145/1127777
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 19 April 2006

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Author Tags

  1. matchings
  2. stochastic processes

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Overall Acceptance Rate 143 of 593 submissions, 24%

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Cited By

View all
  • (2012)Efficient Allocation of Agent Groups for Complex Tasks in Real Cost EnvironmentsProceedings of the 2012 IEEE International Conference on Software Science, Technology and Engineering10.1109/SWSTE.2012.14(54-62)Online publication date: 12-Jun-2012
  • (2010)Enabling rich mobile applicationsACM SIGMOBILE Mobile Computing and Communications Review10.1145/1710130.171013313:3(14-25)Online publication date: 21-Jan-2010
  • (2008)Distributed Operator Placement and Data Caching in Large-Scale Sensor NetworksIEEE INFOCOM 2008 - The 27th Conference on Computer Communications10.1109/INFOCOM.2008.151(977-985)Online publication date: Apr-2008
  • (2007)Joint Computation and Communication Scheduling to Enable Rich Mobile ApplicationsIEEE GLOBECOM 2007-2007 IEEE Global Telecommunications Conference10.1109/GLOCOM.2007.405(2117-2122)Online publication date: Nov-2007

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