Citation
Carlo Fischione. "Reducing Energy Consumption in Wireless Sensor Networks". Talk or presentation, 11, December, 2007.

Abstract
Wireless Sensor Networks (WSNs) are ad hoc networks of tiny, autonomous devices equipped with wireless communication and sensing capabilities for networking, control and monitoring purposes. WSNs are characterized by limited resources in terms of communication, computation and energy supply. The need of achieving maximum efficiency from these systems motivates the challenge of a careful design that integrates functionalities traditionally considered to be separated, as communication, computation, and control. Indeed, despite major recent advances in each of these areas, several open questions have to be explored for the overall design of WSNs. In particular, the limited amount of processing resources of wireless nodes has a significant impact on many aspects of the system. It is expected that significant performance improvement can be achieved by exploiting the advantages offered by joint design of communication, control, and computation in WSNs, using the Platform Based Design approach. In this talk, we illustrate such a design methodology for the problem of energy consumption minimization of WSNs. Specifically, we present some relevant aspects of two coding schemes available in the literature: the Minimum Energy (ME) coding, and the Modified Minimum Energy (MME) coding. We start from a detailed and general model of the energy consumption of the nodes, which is a function of the hardware characteristics of the transceivers, the coding technique, the radio transmit powers, and the dynamics of the wireless channel. Then, we propose a new method to minimize the energy by optimizing all the variables of the model. In particular, we suggest an optimal way to design the detection thresholds of the receivers. Exploiting the limited feed-back of the channel state, and resorting to the theory of the contractive functions, a distributed radio power minimization algorithm is derived. The algorithm is shown to be stable and it requires low computational processing, making it amenable for implementation on limited hardware platforms. Next, an analysis of the bit error probability is addressed. Finally, the theoretical framework is applied to real WSNs to illustrate the tradeoffs between ME and MME coding.

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• HTML

  Carlo Fischione. <a
  href="http://chess.eecs.berkeley.edu/pubs/381.html"
  ><i>Reducing Energy Consumption in Wireless Sensor
  Networks</i></a>, Talk or presentation,  11,
  December, 2007.

• Plain text

  Carlo Fischione. "Reducing Energy Consumption in
  Wireless Sensor Networks". Talk or presentation,  11,
  December, 2007.

• BibTeX

  @presentation{Fischione07_ReducingEnergyConsumptionInWirelessSensorNetworks,
      author = {Carlo Fischione},
      title = {Reducing Energy Consumption in Wireless Sensor
                Networks},
      day = {11},
      month = {December},
      year = {2007},
      abstract = {Wireless Sensor Networks (WSNs) are ad hoc
                networks of tiny, autonomous devices equipped with
                wireless communication and sensing capabilities
                for networking, control and monitoring purposes.
                WSNs are characterized by limited resources in
                terms of communication, computation and energy
                supply. The need of achieving maximum efficiency
                from these systems motivates the challenge of a
                careful design that integrates functionalities
                traditionally considered to be separated, as
                communication, computation, and control. Indeed,
                despite major recent advances in each of these
                areas, several open questions have to be explored
                for the overall design of WSNs. In particular, the
                limited amount of processing resources of wireless
                nodes has a significant impact on many aspects of
                the system. It is expected that significant
                performance improvement can be achieved by
                exploiting the advantages offered by joint design
                of communication, control, and computation in
                WSNs, using the Platform Based Design approach. In
                this talk, we illustrate such a design methodology
                for the problem of energy consumption minimization
                of WSNs. Specifically, we present some relevant
                aspects of two coding schemes available in the
                literature: the Minimum Energy (ME) coding, and
                the Modified Minimum Energy (MME) coding. We start
                from a detailed and general model of the energy
                consumption of the nodes, which is a function of
                the hardware characteristics of the transceivers,
                the coding technique, the radio transmit powers,
                and the dynamics of the wireless channel. Then, we
                propose a new method to minimize the energy by
                optimizing all the variables of the model. In
                particular, we suggest an optimal way to design
                the detection thresholds of the receivers.
                Exploiting the limited feed-back of the channel
                state, and resorting to the theory of the
                contractive functions, a distributed radio power
                minimization algorithm is derived. The algorithm
                is shown to be stable and it requires low
                computational processing, making it amenable for
                implementation on limited hardware platforms.
                Next, an analysis of the bit error probability is
                addressed. Finally, the theoretical framework is
                applied to real WSNs to illustrate the tradeoffs
                between ME and MME coding.},
      URL = {http://chess.eecs.berkeley.edu/pubs/381.html}
  }
  

Posted by Douglas Densmore on 11 Dec 2007.
Groups: chess
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