Elements of information theory
Elements of information theory
On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
On the relevance of long-range dependence in network traffic
IEEE/ACM Transactions on Networking (TON)
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Spatio-temporal correlation: theory and applications for wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: In memroy of Olga Casals
Fractal-Based Point Processes
Event-Based Motion Control for Mobile-Sensor Networks
IEEE Pervasive Computing
Supervisory control of mobile sensor networks: math formulation, simulation, and implementation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Networked Slepian-Wolf: theory, algorithms, and scaling laws
IEEE Transactions on Information Theory
Ubiquitous sensor networks traffic models for telemetry applications
NEW2AN'11/ruSMART'11 Proceedings of the 11th international conference and 4th international conference on Smart spaces and next generation wired/wireless networking
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Recently there has been a great deal of research on using mobility in wireless sensor networks to facilitate surveillance and reconnaissance in a wide deployment area. Besides providing an extended sensing coverage, the node mobility along with the spatial correlation of the monitored phenomenon introduces new dynamics to the network traffic. These dynamics could lead to long range dependent (LRD) traffic, which necessitates network protocols fundamentally different from what we have employed in the traditional (Markovian) traffic. Therefore, characterizing the effects of mobility and spatial correlation on the dynamic behavior of the network traffic is particularly important in the effective design of network protocols. In this paper, a novel traffic modeling scheme for capturing these dynamics is proposed that takes into account the statistical patterns of human mobility and spatial correlation. The contributions made in this paper are twofold: first, it is shown that the mobility variability and the spatial correlation can lead to the pseudo-LRD traffic, whose autocorrelation function follows a power law form with the Hurst parameter up to a certain cutoff time lag. Second, it is shown that the degree of traffic burstiness, which is characterized by the Hurst parameter, has an intimate connection with the mobility variability and the degree of spatial correlation. Furthermore, we show that this connection can be utilized to design the mobility-aware traffic smoothing schemes, which point out a new direction for traffic control protocols. Finally, simulation results reveal a close agreement between the traffic pattern predicted by our theoretical model and the simulated transmissions from multiple independent sources, under specific bounds of the observation intervals.