Spatiotemporal Correlation Theory for Wireless Sensor Networks
5.5 CONCLUSION AND OPEN RESEARCH ISSUES
In addition to its collaborative nature, the existence of spatiotemporal correlation among the sensor observations is a significant and unique characteristic of the WSN.
In this chapter, a theoretical analysis of spatiotemporal correlation characteristics in WSN is presented. It has been shown via mathematical analysis, their results, case studies, and discussions that correlation in WSNs can be exploited to signifi-cantly improve the energy-efficiency in WSNs. Therefore, this theoretical framework provides tools for finding the feasible operating region in terms of spatial and temporal resolution for a specific distortion constraint considering spatiotemporal correlation, signal properties, and network variables in WSNs.
Although there exists a considerable amount of existing research and studies on the correlation characteristics of sensor networks, there are many open research is-sues and new directions on this topic. One important research direction would be to obtain real sensor data and capture the spatiotemporal correlation behavior observed in different practical sensor network applications in order to enhance the correla-tion models developed so far. This will improve the accuracy of the correlacorrela-tion and distortion analysis derived in the current literature.
On the other hand, the effects of the network parameters such as topology, node distribution, radio, and sensing ranges of sensor nodes, heterogeneity of events occur-ring in the network need to be carefully investigated in order to reveal other important characteristics of spatiotemporal correlation in WSNs.
The correlation in WSNs can be considered in developing new energy-efficient net-working protocols specifically tailored for the WSN paradigm. These protocols utiliz-ing the correlation to conserve energy resources may drastically enhance the overall network performance. Furthermore, spatiotemporal correlation could be a baseline for
cross-layer design of energy-efficient communication techniques for wireless sensor networks.
Moreover, the spatiotemporal correlation characteristics can also be exploited for efficient distributed source coding and information processing techniques. To this end, new spatiotemporal correlation modeling analysis can be developed for wireless multimedia sensor networks [20] that involve the communication of event data in the form of multimedia such as still image, video, and audio. Based on the spatiotem-poral correlation models that can capture the unique communication paradigm of multimedia over WSNs, energy-efficient multimedia processing and communication algorithms can be devised for wireless multimedia sensor networks as well.
5.6 EXERCISES
1. Explain different types of correlation observed in wireless sensor networks. Pro-vide a practical example for each case and discuss the main reasons for the ob-served correlation in the examples you provide.
2. What is the relation between the correlation and the distortion observed in the estimation of event features in a given sensor network? Propose another simple (yet practical) definition for distortion [as in (5.9)] which could be used as a reliability indicator in wireless sensor networks.
3. Derive the distortion function in (5.12) using the Spherical Covariance Model instead of the Power Exponential Model. Obtain the distortion as a function of number of nodesMthat send information to the sink and correlation coefficients and comment on the results comparing them with Figure 5.2.
4. In the analysis of temporal correlation in WSNs, it is assumed that the observed signals(t) is wide-sense stationary (WSS). What is the effect of this assumption?
How could this assumption be relaxed without losing the validity of the results of the analysis?
5. Note that the distortion analysis in this chapter does not explicitly incorporate the effects of channel and network capacity on the successful reception performance of the transmitted samples. Propose a modification to the model presented in Section 5.2 in order to include the effects of channel error rate and network congestion on the derived distortion functions.
6. Based on the spatiotemporal correlation characteristics and the distortion func-tions derived in this chapter, propose a new routing protocol for WSNs which can find the minimum energy and minimum distortion paths from the event field to the sink. Clearly state the assumptions you make and outline the algorithm you propose by explaining the rational behind your idea.
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