Wireless sensor networks have been widely used for surveillance in harsh environments. In many such applications, the environmental data are continuously sensed, and data collection by a server is only performed occas...
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Wireless sensor networks have been widely used for surveillance in harsh environments. In many such applications, the environmental data are continuously sensed, and data collection by a server is only performed occasionally. Hence, the sensor nodes have to temporarily store the data, and provide easy and on-hand access for the most updated data when the server approaches. Given the expensive server-to-sensor communications, the large amount of sensors and the limited storage space at each tiny sensor, continuous data collection becomes a challenging problem. In this article, we present partial network coding (PNC) as a generic tool for these applications. PNC generalizes the existing network coding (NC) paradigm, an elegant solution for ubiquitous data distribution and collection. Yet PNC allows efficient storage replacement for continuous data, which is a deficiency of the conventional NC. We prove that the performance of PNC is quite close to NC, except for a sub-linear overhead on storage and communications. We then address a set of practical concerns toward PNC-based continuous data collection in sensor networks. Its feasibility and superiority are further demonstrated through simulation results.
We study the gains to be had by using random linear coding (RLC) for simultaneously disseminating k distinct messages in a network of n nodes in a decentralized and distributed manner for arbitrary k and n. The goal i...
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ISBN:
(纸本)0780391500
We study the gains to be had by using random linear coding (RLC) for simultaneously disseminating k distinct messages in a network of n nodes in a decentralized and distributed manner for arbitrary k and n. The goal is to rapidly disseminate all the messages among all the nodes. Any node can communicate with any of the other nodes but only one at a time, nodes only have knowledge about their own contents, and the bandwidth for every transmission between two nodes is limited (does not scale with k or n). An efficient and well-studied protocol for message dissemination in such a frameowork is randomized gossip based message dissemination. The problem has been studied extensively without using any coding for message dissemination. We show using analysis and simulation that, in the regime k >= (ln(n))(3), RLC based dissemination reduces the dissemination time (the time-steps to disseminate all the messages among an the nodes) by a factor of Theta(ln(n)) as compared to disseminating the messages sequentially (i.e., one after the other) as implicit in most non-coding based technique. In the regime k <= (ln(n))(2,) the dissemination time with RLC goes down by a factor of Omega(root k/ In k). More precisely, our results indicate that a RLC based protocol disseminates all the messages among all the nodes in time ck + O(root k ln(k)(ln(n)) for a suitable constant c > 0. Analytical results show that, c < 3.46 using pull based dissemination, and c < 5.96 using push based dissemination, but reported simulations suggest c < 2 might be a tighter bound.
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