Resource Management for Ad-Hoc Wireless Networks with Cluster Organization

  • Authors:
  • Ionut Cardei;Srivatsan Varadarajan;Allalaghatta Pavan;Lee Graba;Mihaela Cardei;Manki Min

  • Affiliations:
  • Honeywell Labs, 3660 Technology Dr., Minneapolis, MN 55418, USA;Honeywell Labs, 3660 Technology Dr., Minneapolis, MN 55418, USA;Honeywell Labs, 3660 Technology Dr., Minneapolis, MN 55418, USA;Honeywell Labs, 3660 Technology Dr., Minneapolis, MN 55418, USA;University of Minnesota, 200 Union St. SE, Minneapolis, MN 55455, USA;University of Minnesota, 200 Union St. SE, Minneapolis, MN 55455, USA

  • Venue:
  • Cluster Computing
  • Year:
  • 2004

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Abstract

Boosted by technology advancements, government and commercial interest, ad-hoc wireless networks are emerging as a serious platform for distributed mission-critical applications. Guaranteeing QoS in this environment is a hard problem because several applications may share the same resources in the network, and mobile ad-hoc wireless networks (MANETs) typically exhibit high variability in network topology and communication quality. In this paper we introduce DYNAMIQUE, a resource management infrastructure for MANETs. We present a resource model for multi-application admission control that optimizes the application admission utility, defined as a combination of the QoS satisfaction ratio. A method based on external adaptation (shrinking QoS for existing applications and later QoS expansion) is introduced as a way to reduce computation complexity by reducing the search space. We designed an application admission protocol that uses a greedy heuristic to improve application utility. For this, the admission control considers network topology information from the routing layer. Specifically, the admission protocol takes benefit from a cluster network organization, as defined by ad-hoc routing protocols such as CBRP and LANMAR. Information on cluster membership and cluster head elections allows the admission protocol to minimize control signaling and to improve application quality by localizing task mapping.