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The random walk algorithm using gradient descent [160] is applied to guide the mobile node to a focus of interest The algorithm proceeds as follows: 1 Record the current sense value reading from the sensor P (i) 2 Move along a straight line for a constant distance 3 Record again the current sensor intensity reading from the sensor P (i + 1) 4 If the difference P (i + 1) P (i) > 0, move along the same direction 5 If the goal is reached then stop 6 If the goal is not reached then rotate by a random angle and go back to step 1 3557 Network repairing algorithm As described before, the use of mobile nodes makes it possible to repair the network connectivity of a sensor network [162] The use of mobile nodes could be important to increase the fault tolerance in a WSN.

Eqs. 7.1, 7.101

Varian, writing in The New York Times, provides some context for the development of the field research leading up to Nash s work He notes that the eminent mathematician, John von Neumann, laid much of the ground work for modern game theory as he sought to understand the basic logic behind strategic interactions Later, teaming with economist Oscar Morgenstern, von Neumann began to develop mathematic formulations that could represent these situations in which two or more parties or players had opposing interests Such scenarios, often referred to as zero-sum games could be fanciful in nature, such as sporting events or forms of gambling Their name derives from the simple proposition that for one player to win, every other player must lose They could also, however, be deadly earnest, like wars and international economic disputes.

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Assuming that a manual or automatic network deployment is executed, the connectivity repair algorithm could consist of two phases: The mobile node measures the connection topology of the deployed network and compares it to the desired topology If they match, no deployment is done This phase can be run at any time, with the objective detecting the potential failure of sensor nodes and ensuring sustained connectivity Otherwise, the measured connectivity graph is used to compute new deployment locations that will repair the desired topology These deployment locations can be represented as a set of waypoints In a real-life implementation [162], a simpli ed version of this procedure has been applied The algorithm computes deployment locations whose connectivity graph is one connected component Therefore, the task of the connectivity repair algorithm is to determine the number of connected components in the deployed network.

channel (E-DPCCH), and the DPCCH. The power ratios are called beta factors . The suggested beta factor is de ned as an average over multipath channels. Beta factors are summarized in Table 8.2. Here the values have been rounded to the signalling values available, and for FRC3 the value given corresponds to SF4 codes. SF2 code powers are p derived from this by multiplying by 2. These beta factors are designed for antenna diversity reception while 3 dB should be added for single-antenna reception. In the following the single-link performance of FRC2, 5, and 6 are presented under the assumptions listed in Table 8.3. FRC5 represents a rst-phase HSUPA UE, whereas FRC2 and FRC6 represent future release UEs. Note that power control is o in these simulations. The performance requirements are de ned for all FRCs with diversity reception, and all FRCs except 2 and 3 for single-antenna reception. Figure 8.1 shows the data rate without power control as a function of received Ec =N0 per base station antenna. The performance of FRC2 with a 2-ms TTI and FRC6 with a 10-ms TTI are fairly similar. FRC2 can provide higher peak data rates when Ec =N0 is

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