Antonio Fernández Anta ; Miguel Mosteiro ; Christopher Thraves Caro - Deterministic Recurrent Communication and Synchronization in Restricted Sensor Network

dmtcs:528 - Discrete Mathematics & Theoretical Computer Science, April 22, 2011, Vol. 13 no. 1 -
Deterministic Recurrent Communication and Synchronization in Restricted Sensor NetworkArticle

Authors: Antonio Fernández Anta 1; Miguel Mosteiro 2,3; Christopher Thraves Caro

Monitoring physical phenomena in Sensor Networks requires guaranteeing permanent communication between nodes. Moreover, in an effective implementation of such infrastructure, the delay between any two consecutive communications should be minimized. The problem is challenging because, in a restricted Sensor Network, the communication is carried out through a single and shared radio channel without collision detection. Dealing with collisions is crucial to ensure effective communication between nodes. Additionally, minimizing them yields energy consumption minimization, given that sensing and computational costs in terms of energy are negligible with respect to radio communication. In this work, we present a deterministic recurrent-communication protocol for Sensor Networks. After an initial negotiation phase of the access pattern to the channel, each node running this protocol reaches a steady state, which is asymptotically optimal in terms of energy and time efficiency. As a by-product, a protocol for the synchronization of a Sensor Network is also proposed. Furthermore, the protocols are resilient to an arbitrary node power-up schedule and a general node failure model.

Volume: Vol. 13 no. 1
Section: Distributed Computing and Networking
Published on: April 22, 2011
Accepted on: June 9, 2015
Submitted on: September 24, 2010
Keywords: [INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM]
    Source : OpenAIRE Graph
  • Adversarial Models in Sensor Networks; Funder: European Commission; Code: 210021
  • HECURA: Colaborative: Multidimensional and String Indexes for Streaming Data; Funder: National Science Foundation; Code: 0937829

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