SPATIOTEMPORAL CORRELATION THEORY FOR WIRELESS SENSOR NETWORKS in .NET framework

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SPATIOTEMPORAL CORRELATION THEORY FOR WIRELESS SENSOR NETWORKS
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Figure 5.3. Spatial re-usage in sensor networks [18].
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In a recent work [18], a correlation-based MAC protocol has been proposed which exploits the spatial correlation between closely located sensor nodes that regulate medium access and prevent redundant transmissions from closely located sensors. Based on the spatial correlation among sensor nodes, the MAC protocol collaboratively regulates medium access so that redundant transmissions from correlation neighbors are suppressed. In addition, necessary mechanisms for the ef cient transmission of the information from the sensor nodes to the sink have also been incorporated into the proposed correlation-based MAC solution. The experimental results in reference 18 reveal that signi cant performance gains and energy savings are obtained by exploiting spatial correlation in sensor networks. 5.4.2 Spatiotemporal Correlation and Reliable Event Communication In order to realize the potential gains of the WSN, it is imperative that desired event features are reliably communicated to the sink. Unlike traditional communication networks, the sensor network paradigm necessitates that the event features are estimated within a certain distortion bound (i.e., required reliability level) at the sink as discussed in Section 5.2. Reliable event detection at the sink is based on collective information provided by source nodes and not on any individual report. Hence, conventional endto-end reliability de nitions and solutions are inapplicable in the WSN regime and would only lead to overutilization of scarce sensor resources. On the other hand, the absence of reliable transport altogether can seriously impair event detection, which is the main objective of WSN deployment. Hence, the WSN paradigm necessitates a collective event-to-sink reliability notion rather than the traditional end-to-end notion [19]. Such event-to-sink reliable transport notion based on collective identi cation of spatially and temporally correlated data ows from the event to the sink is illustrated in Figure 5.4 and depends on the following de nitions:
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COROLLARIES AND EXPLOITING CORRELATION IN WIRELESS SENSOR NETWORKS
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Figure 5.4. Typical sensor network topology with event and sink. The sink is only interested in collective information of sensor nodes within the event radius and not in their individual data.
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De nition 1. The observed event distortion Di is the distortion achieved [i.e., as in (5.23)] when the sink performs estimation of the signal S being tracked in decision interval i. De nition 2. The desired event distortion D is the maximum distortion allowed to assure reliable event detection in the estimation performed by the sink. This upper bound for the distortion level is determined by the application and based on the physical characteristics of the signal S being tracked. Based on the packets generated by the sensor nodes in the event area, the sink estimates the event features to determine the necessary action and observes Di at each decision interval i. Note that a distortion level D for the estimation of event features from the sensor observations corresponds to the reliability level of the eventto-sink communication in the WSN. If observed event distortion is less than the distortion bound, i.e., Di < D , then the event is deemed to be reliably detected. Else, appropriate action needs to be taken to assure the desired reliability level in the event-to-sink communication. The main rationale behind such event-to-sink reliability notion is that the data generated by the sensors are temporally correlated, which tolerates individual packets to be lost to the extent where the desired event distortion D is not exceeded. Let f be the reporting frequency of a sensor node de ned as the number of samples taken and hence packets sent out per unit time by that node for a sensed phenomenon. This reporting frequency can be attributed to increase in sampling rate as in Section 5.3.2. Hence, the reporting frequency f controls the amount of traf c injected to the sensor eld while regulating the number of temporally correlated samples taken from the phenomenon. This, in turn, affects the observed event distortion that is, event detection reliability. Thus, the reliable event transport problem in WSN is to determine the reporting rate (f ) of source nodes so that the maximum event estimation distortion bound D is not exceeded; that is, required event detection reliability is achieved at the sink, with minimum resource utilization.
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