research-article

Modeling and performance analysis of DMAC for wireless sensor networks

Authors:

Sridhar Radhakrishnan,

Venkatesh SaranganAuthors Info & Claims

MSWiM '11: Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems

Pages 119 - 128

https://doi.org/10.1145/2068897.2068920

Published: 31 October 2011 Publication History

Abstract

DMAC is a popular data gathering MAC protocol for wireless sensor networks. It employs staggered sleep-awake schedules to enable continuous data forwarding along a data gathering tree, resulting in reduced end-to-end delays and energy consumption. In this paper we present a generalized model for the DMAC protocol and for this generalized model we have analyzed end-to-end delay and energy consumption with respect to the source node for both constant bit rate traffic and stochastic traffic following a Poisson process. The stochastic traffic scenario is modeled as a discrete time Markov chain and expressions for state transition probabilities, average delay and average energy consumption are developed and it is shown that these can be evaluated numerically. Simulations are carried out with various parameters and the results are in line with the analytical results. Both analysis and simulations indicate that DMAC is more suitable for constant bit rate traffic than stochastic traffic.

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Cited By

Singh RRai BBose S(2019)Modeling and Performance Analysis for Pipelined-Forwarding MAC Protocols for Linear Wireless Sensor NetworksIEEE Sensors Journal10.1109/JSEN.2019.291020919:15(6539-6552)Online publication date: 1-Aug-2019
https://doi.org/10.1109/JSEN.2019.2910209
Tong FHe SPan J(2019)Modeling and Analysis for Data Collection in Duty-Cycled Linear Sensor Networks With Pipelined-Forwarding FeatureIEEE Internet of Things Journal10.1109/JIOT.2019.29293086:6(9489-9502)Online publication date: Dec-2019
https://doi.org/10.1109/JIOT.2019.2929308
Lasla NDoudou MDjenouri DOuadjaout AZizoua C(2019)Wireless energy efficient occupancy-monitoring system for smart buildingsPervasive and Mobile Computing10.1016/j.pmcj.2019.101037(101037)Online publication date: Jun-2019
https://doi.org/10.1016/j.pmcj.2019.101037
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Index Terms

Modeling and performance analysis of DMAC for wireless sensor networks
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis
      1. Modeling methodologies

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Published In

cover image ACM Conferences

MSWiM '11: Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems

October 2011

462 pages

ISBN:9781450308984

DOI:10.1145/2068897

General Chair:
Ahmed Helmy
University of Florida, USA
,
Program Chairs:
Bjorn Landfeldt
University of Sydney, Australia
,
Luciano Bononi
University of Bologna, Italy

Copyright © 2011 ACM.

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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SIGSIM: ACM Special Interest Group on Simulation and Modeling

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 31 October 2011

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MSWiM '11

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MSWiM '11: The 14th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

October 31 - November 4, 2011

Florida, Miami, USA

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Overall Acceptance Rate 398 of 1,577 submissions, 25%

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Cited By

Singh RRai BBose S(2019)Modeling and Performance Analysis for Pipelined-Forwarding MAC Protocols for Linear Wireless Sensor NetworksIEEE Sensors Journal10.1109/JSEN.2019.291020919:15(6539-6552)Online publication date: 1-Aug-2019
https://doi.org/10.1109/JSEN.2019.2910209
Tong FHe SPan J(2019)Modeling and Analysis for Data Collection in Duty-Cycled Linear Sensor Networks With Pipelined-Forwarding FeatureIEEE Internet of Things Journal10.1109/JIOT.2019.29293086:6(9489-9502)Online publication date: Dec-2019
https://doi.org/10.1109/JIOT.2019.2929308
Lasla NDoudou MDjenouri DOuadjaout AZizoua C(2019)Wireless energy efficient occupancy-monitoring system for smart buildingsPervasive and Mobile Computing10.1016/j.pmcj.2019.101037(101037)Online publication date: Jun-2019
https://doi.org/10.1016/j.pmcj.2019.101037
Tong FHe SPan J(2017)Distance Distribution-Based Modeling and Analysis for Pipelined-Forwarding Sensor NetworksGLOBECOM 2017 - 2017 IEEE Global Communications Conference10.1109/GLOCOM.2017.8254508(1-6)Online publication date: Dec-2017
https://doi.org/10.1109/GLOCOM.2017.8254508
Doudou MBarcelo-Ordinas JDjenouri DGarcia-Vidal JBouabdallah ABadache N(2016)Game Theory Framework for MAC Parameter Optimization in Energy-Delay Constrained Sensor NetworksACM Transactions on Sensor Networks10.1145/288361512:2(1-35)Online publication date: 3-May-2016
https://dl.acm.org/doi/10.1145/2883615
Tong FZheng LAhmadi MNi MPan J(2016)Modeling and Analyzing Duty-Cycling Pipelined-Scheduling MAC for Linear Sensor NetworksIEEE Transactions on Vehicular Technology10.1109/TVT.2015.242670865:4(2608-2620)Online publication date: Apr-2016
https://doi.org/10.1109/TVT.2015.2426708
(2016)Impact of redundant sensor deployment over data gathering performanceJournal of Network and Computer Applications10.1016/j.jnca.2016.03.01267:C(26-42)Online publication date: 1-May-2016
https://dl.acm.org/doi/10.1016/j.jnca.2016.03.012
Doudou MBarcelo‐Ordinas JDjenouri DBadache NGarcia‐Vidal J(2016)Performance optimization of duty‐cycled MAC in delay‐energy constrained sensor network under uniform and nonuniform traffic generationInternational Journal of Communication Systems10.1002/dac.318530:9Online publication date: 13-Oct-2016
https://doi.org/10.1002/dac.3185
Bernstein MLittle GMiller RHartmann BAckerman MKarger DCrowell DPanovich K(2015)SoylentCommunications of the ACM10.1145/279128558:8(85-94)Online publication date: 23-Jul-2015
https://dl.acm.org/doi/10.1145/2791285
Soh LShell DIngraham ERamsay SMoore B(2015)Learning through computational creativityCommunications of the ACM10.1145/269939158:8(33-35)Online publication date: 23-Jul-2015
https://dl.acm.org/doi/10.1145/2699391
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