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UCF EEL 5937 - A Taxonomy of Wireless Micro-Sensor Network Models

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A Taxonomy of Wireless Micro-Sensor Network ModelsSameer TilakNael B. Abu-GhazalehWendi Heinzelman[email protected] [email protected] [email protected]Computer System Research Laboratory, Dept. of CS, Binghamton University, Binghamton, NYElectrical and Computer Engineering, University of Rochester, Rochester, NYIn future smart environments, wireless sensor networks will play a key role in sensing,collecting, and disseminating information about environmental phenomena. Sensing ap-plications represent a new paradigm for network operation, one that has different goalsfrom more traditional wireless networks. This paper examines this emerging field to clas-sify wireless micro-sensor networks according to different communication functions, datadelivery models, and network dynamics. This taxonomy will aid in defining appropriatecommunication infrastructures for different sensor network application sub-spaces, allow-ing network designers to choose the protocol architecture that best matches the goals oftheir application. In addition, this taxonomy will enable new sensor network models to bedefined for use in further research in this area.I. IntroductionAdvances in hardware and wireless network technolo-gies have placed us at the doorstep of a new era wheresmall wireless devices will provide access to informa-tion anytime, anywhere as well as actively participatein creating smart environments. One of the applica-tions of smart spaces is sensor networks, networks thatare formed when a set of small untethered sensor de-vices that are deployed in an ad hoc fashion cooperateon sensing a physical phenomenon. Sensor networkshold the promise of revolutionizing sensing in a widerange of application domains because of their reliabil-ity, accuracy, flexibility, cost-effectiveness, and easeof deployment.To motivate the challenges in designing sensor net-works, consider the following scenarios: sensors arerapidly deployed in a remote inhospitable area for asurveillance application; sensors are used to analyzethe motion of a tornado; sensors are deployed in a for-est for fire detection; sensors are attached to taxi cabsin a large metropolitan area to study the traffic con-ditions and plan routes effectively; and smart Kinder-garten [1] where sensor networks are deployed to cre-ate a developmental problem-solving environment forearly childhood education.Clearly, there is a wide range of applications forsensor networks with differing requirements. We be-lieve that a better understanding of micro-sensor net-work requirements as well as the underlying differ-ences between micro-sensor applications is needed toThis work was partially supported by NSF grant EIA-9911099.assist designers. To this end, in this paper we attemptto classify wireless micro-sensor networks. In partic-ular, we classify the aspects of wireless micro-sensornetworks that we believe are most relevant to commu-nication. We examine the characteristics and goals oftypical micro-sensor networks as well as the differenttypes of communication that are required to achievethese goals. We compare different data delivery mod-els and network dynamics to create a taxonomy ofwireless micro-sensor network communication. Webelieve that this taxonomy will aid network designersin making better decisions regarding the organizationof the network, the network protocol and informationdissemination models. Furthermore, it will aid in de-veloping realistic sensor network models and bench-marks for use in future sensor network research.The remainder of this paper is organized as fol-lows. Section II presents some basic definitions andan overview of the characteristics of sensor networks.Section III overviews performance metrics of interestfor sensor networks. In Section IV, we describe sensornetwork architectures. Section V classifies the com-munication models present in sensor networks andmakes the distinction between application and infras-tructure related communication. Section VI classifiesthe data delivery models. In Section VII, the networkorganization and dynamics are classified. Section VIIIpresents case studies of existing sensor network pro-tocols, showing how they fit into the taxonomy de-scribed in this paper. Finally, Section IX presents asummary and some concluding remarks.28Mobile Computing and Communications Review, Volume 6, Number 2II. Sensor Network CharacteristicsIn this paper, we use the following terminology:¯Sensor: The device that implements the phys-ical sensing of environmental phenomena andreporting of measurements (through wirelesscommunication). Typically, it consists of fivecomponents– sensing hardware, memory, bat-tery, embedded processor, and trans-receiver.¯Observer: The end user interested in obtaininginformation disseminated by the sensor networkabout the phenomenon. The observer may in-dicate interests (or queries) to the network andreceive responses to these queries. Multiple ob-servers may exist in a sensor network.¯Phenomenon: The entity of interest to the ob-server that is being sensed and potentially ana-lyzed/filtered by the sensor network. Multiplephenomena may be under observation concur-rently in the same network.In a sensing application, the observer is interestedin monitoring the behavior of the phenomenon undersome specified performance requirements (e.g., accu-racy or delay). In a typical sensor network, the in-dividual sensors sample local values (measurements)and disseminate information as needed to other sen-sors and eventually to the observer. The measure-ments taken by the sensors are discrete samples ofthe physical phenomenon subject to individual sensormeasurement accuracy as well as location with respectto the phenomenon.Sensor networks share many of the challenges oftraditional wireless networks, including limited en-ergy available to each node and bandwidth-limited,error-prone channels. However, communication insensor networks differs from communication in othertypes of networks in that it is typically not end-to-end [2]. More specifically, the function of the networkis to report information regarding the phenomenon tothe observer who is not necessarily aware of the sen-sor network infrastructure and the individual sensorsas an end-point of communication. Furthermore, en-ergy is typically more limited in sensor networks thanin other wireless networks because of the nature ofthe sensing devices and the difficulty in rechargingtheir batteries. Studies in


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