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Here 0 1, is the asymptotic mean of vn when n approaches infinity, and xn is an independent, uncorrelated, and stationary Gaussian process with zero mean The Gauss Markov model represents a wide range of mobility patterns, including the constant velocity fluid flow models (when = 1) and the random walk model (when = 0 and = 0) Normal Walk Model In [41], the authors have proposed a multiscale, straight-oriented mobility model referred to as normal walk They assume that a mobile station moves in unit steps on a Euclidean plane The ith move, Yi, is obtained by rotating the (i 1)th move, Yi 1, counterclockwise for i degrees: Yi = R( i)Yi 1 Here i is normally distributed with zero mean Since the normal distribution with zero mean is chosen, the probability density increases as the rotation angle approaches zero.

Therefore, a mobile station has a very high probability of preserving the previous direction Shortest Path Model In [3], the authors have introduced the shortest path model for the mobility of a vehicular mobile station The network topology used to illustrate the model is of the mesh configuration They assume that, within the location area, a mobile station will follow the shortest path measured in the number of cells traversed, from source to destination At each intersection, the mobile station makes a decision to proceed to any of the neighboring cells such that the shortest distance assumption is maintained That means that a mobile station can only go straight or make a left or right turn at an intersection Furthermore, a mobile station cannot make two consecutive left turns or right turns.

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Tsiatsis, S Ganeriwal, and M Srivastava Optimizing sensor networks in the energy-latency-density design space IEEE Transactions on Mobile Computing, 1(1):70 80, January 2002 39 Y Yu, B Krishnamachari, and V K Prasanna Energy-latency tradeoffs for data gathering in wireless sensor networks In Proceedings of INFOCOM 2004, Hong Kong, March 2004 40 D Slepian and J K Wolf Noiseless encoding of correlated information sources IEEE Transactions on Information Theory, IT-19:471 480, July 1973 41 E Duarte-Melo, M Liu, and A Misra A computational approach to the joint design of distributed data compression and data dissemination in a data-gathering wireless sensor network In Proceedings of the 34th Allerton Conference on Communications Control, Monticello, Illinois, October 2003 42 P Gupta and P R Kumar The capacity of wireless networks IEEE Transactions on Information Theory, 46(2):388 404, 2000 43 D Petrovic, R C Shah, K Ramchandran, and J Rabaey.

Activity-Based Model Instead of using a set of random variables to model the mobility pattern, an actual activitybased mobility model has been developed at the University of Waterloo [38, 39] The model is based on the trip survey conducted by the Regional Municipality of Waterloo in 1987 It is assumed that a trip is undertaken for taking part in an activity such as shopping at the destination Once the location for the next activity is selected, the route from the current location to the activity location will be determined in terms of cells crossed The.

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Data funneling: Routing with aggregation and compression for wireless sensor networks In Proceedings of the 1st IEEE International Workshop on Sensor Network Protocols and Applications (SNPA), pages 156 162, Anchorage, Alaska, May 2003..

These voice recording capabilities are provided by the Windows CE voice recorder control. The control contains a Play button, and optional Stop, Record, OK, and Close buttons. There is no voice recording API. Instead, the voice recorder control responds to a set of messages that control recording and playback.

The General panel includes settings that don t fit anywhere else, including Place Scroll Arrows for controlling whether your scroll arrows appear at one end or both ends of the scroll bar, Expos Window Hiding to enable the miniaturized Desktop mode of Expos (see Figure 7-3), and Display Of Sheets to make sheets (like save and open panels) roll out faster, if you re that impatient.

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