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21.2 CLASSIFICATION OF ROUTING ALGORITHMS We shall now review the main characteristics of proposed routing algorithms in light of desired qualitative and quantitative properties [35] and a few additional characteristics. 21.2.1 Demand-Based Operation Routing algorithms can be classified as proactive or reactive. Proactive protocols maintain routing tables when nodes move, independently of traffic demand, and thus may have unacceptable overhead when data traffic is considerably lower than mobility rate. For instance, shortest- (weighted) path-based-solutions [3, 43, 45] are too sensitive to small changes in local topology and activity status (the later even does not involve node movement). The communication overhead involved in maintaining global information about the networks is not acceptable for networks whose bandwidth and battery power are severely limited. They are not elaborated on further in this chapter. Routes in reactive algorithms are established when they are needed, in order to minimize the communication overhead. They are adaptive to sleep period operation, since inactive nodes simply do not participate at the time the route is established. One of wellknown reactive algorithms is the source-initiated, on-demand routing strategy [5, 22, 41, 44, 45]. In this strategy, the source or intermediate node S issues destination search request if the route to destination D is not available. The destination search is performed by flooding a short search message, so that each node in the network is reached. Flooding algorithms that reduce the number of retransmissions are surveyed and discussed in [50]. The path to destination is memorized in the process [5, 22, 41, 44, 45]. A variant of this strategy is proposed in [53]. Several search tickets (each ticket is a short message con-

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10 60 s

10 4

her mobile device for nding people driving by and willing to share their car. Alice quickly inputs her current location, her destination, as well as other parameters such as her trust level on the car owner: a family member, acquaintances, or anyone having a car. The application indicates to her a list of possibilities. She is very happy when she realises that her friends Jane and Mary are driving together towards the city. A few minutes later her friend s car picks her up near to the repair shop and together they head to the city centre for some shopping. After all, the accident has a much more positive outcome than I could have expected! , Alice thinks.

where T e is the effective noise temperature measured in kelvins. Note that the kelvin temperature scale is based on absolute zero.

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(a) Classi cation Accuracy Advertisement Fixed Eigenspace Original IPCA Batch PCA Chunk IPCA (b) CPU Time Advertisement Fixed Eigenspace Original IPCA Batch PCA Chunk IPCA 13.7 18.1 3000 18.5 Isolet 1.8 6379 2146 265.9 MUSK 0.044 17.4 37.6 1.7 Spambase 0.003 27.4 3.1 0.9 Segmentation 0.0003 0.073 0.022 0.023 Vowel 0.001 0.109 0.05 0.058 89.7 93.2 94.2 93.4 Isolet 88.0 88.3 88.5 88.0 MUSK 95.0 95.1 94.8 94.9 Spambase 69.4 78.9 79.2 78.9 Segmentation 77.3 87.3 87.3 87.3 Vowel 54.8 57.7 58.6 57.2

This value of 0.280 lies at about the 40th percentile of the F1, n p 2 = F1, 72 distribution, giving us a p-value for this hypothesis test of 0.60. Therefore, the null hypothesis that weight should not be included in the model, given all the other variables, is not rejected, and the variable weight is thereby eliminated from the model.

1 = H 4

in style sheet; but even in a style sheet, you don t want to indicate the bullet type separately for each item in the list; this is better indicated in the list element

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