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In Network Processing and Data Aggregation in

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wild animals are monitored <strong>in</strong>side a park of several thous<strong>and</strong>s of sq. meters the placementof nodes is totally different from the case of a factory that supervises items <strong>in</strong> awarehouse.• Particular Traffic patternsA typical communication scenario is as follows: A physical phenomenon occurs neara field of sensors. A big number of sensors events are triggered result<strong>in</strong>g <strong>in</strong> the massproduction of messages (conta<strong>in</strong><strong>in</strong>g values, IDs etc.). These messages have to be routed<strong>in</strong> a multi-hop fashion to a s<strong>in</strong>gle po<strong>in</strong>t, the s<strong>in</strong>k. The rout<strong>in</strong>g pattern looks like a reversedmulticast tree where the dest<strong>in</strong>ation of all the packets is a s<strong>in</strong>gle node <strong>and</strong> there aremultiple senders (many-to-one). Figure 7 demonstrates this pattern. This, however, doesnot prevent the flow of data to be <strong>in</strong> other forms (e.g., multicast or peer to peer). Additionally,s<strong>in</strong>ce the data be<strong>in</strong>g collected by multiple sensors is based on common phenomena, redundantdata will surely be propagated <strong>in</strong>side the network.A B CEFDGSINKFigure 7. Reverse multicast tree• Robustness to network DynamicsThe nodes <strong>in</strong>side the area of deployment may change locations (mobile nodes). Thisleads to frequent alternations of the “neighborhood” of a sensor. Moreover, several nodesmay run out of battery or face hardware failures <strong>and</strong> become dead. The network has toma<strong>in</strong>ta<strong>in</strong> its connectivity no matter how many or how frequent are the topology changes.• Scalability (Us<strong>in</strong>g localized & distributed algorithm)

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