Tree-based systems rely on real-time dissemination trees to deliver information to nodes. In order to offer good services, two fundamental aspects should guide the real-time growth process: low node degree and short distances to the server. In this paper, we propose a growth process to construct trees and make a detailed study on modeling and performance analysis of these tree-based systems. Our generative mechanism is based on the preferential attachment principle, where preference is given in terms of node quality. The proposed growth mechanism has a single parameter to weigh the relative importance of node degree and node distance on assessing node quality. We aim at understanding this mechanism when considering the local aspect of the node's degree and the global aspect of the distance to a source. With this goal, we investigate our model through simulations and compare it to other growth processes. Our results indicate that the proposed model is capable of self-organizing nodes into good trees under six metrics of interest.INDEX TERMS Preferential attachment, Real-time growth process, Tree-based systems, Node quality, Recursive tree, Random tree, Random recursive tree, Power of two choices.
Many applications in Wireless Sensor Networks (WSNs) consider remote and large scale monitoring. For those scenarios, the whole network is difficultly fully connected all the time. A possible vision is the union of WSNs and Disruptive Tolerant Network(DTNs) concepts, where mobile nodes make collect data in sparse networks and deliver them to a base station. This work presents a buffer management strategy, which is a basic principle in DTN networks. The proposed solution considers the global coverage to choose which messages are dropped, therefore, minimizing the impact on monitoring application. Such solutions are important for WSNs applications with limited resources. We show through simulation that the proposed Coverage-Based Drop-Policy in Wireless Sensor Network with Disruptive Connections (CBDP) improves the network coverage compared to traditional DTN drop policies like Drop Last Packet (DL) and Drop First Packet (DF).
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