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Research On The Key Issue Of Data Fusion Based On Network Coding

Posted on:2014-02-21Degree:MasterType:Thesis
Country:ChinaCandidate:Y LiuFull Text:PDF
GTID:2248330395483952Subject:Signal and Information Processing
Abstract/Summary:PDF Full Text Request
International Telecommunication Union (ITU) formally proposed the concept of the Internet of Things (IOT) in the’ITU Internet Report2005:Internet of Things’in WSIS. The information among IOT has the characteristics of multi-source, multi-granularity, multi-dimensional, massive and heterogeneous. As the end of the IOT, wireless sensor network (WSN) is a bridge of communication between virtual world and the real physical world, besides, it has been research on information transmission and processing at home and abroad. However, the coverage of IOT is beyond the scope of WSN. Therefore, new technology for IOT to process and transmit massive information timely is the key factor for practical use.Network coding (NC) is an important breakthrough in the field of communication networks and the advantage of NC is to improve network throughput and transmission reliability. Furthermore, the information from the sensor nodes in the WSN has a strong correlation. Based on NC, this paper makes efforts to improve the aggregation and delivery efficiency for multiple transmission data packets in the WSN. The main contributions of this paper are described as follows:(1) Based on Distributed Source Coding using Syndromes, this paper proposes an adaptive transmission algorithm with target of minimum energy consumption for the whole network based on joint DISCUS and NC scheme. First, we improve DISCUS for broader application. Besides, on the basis of Inter-flow Network Coding, this paper proposes an adaptive transmission algorithm for typical butterfly network and its deformation. The simulation results show that this proposed scheme not only further improves the efficiency of network transmission and enhances the throughput of the network, but also reduces the energy consumption of sensor nodes and extends the network life cycle.(2) This paper combines sequence entropy of Shannon information theory with opportunistic network coding, and then proposes an adaptive compression coding strategy based on network coding. Firstly, we define sequence similarity. Secondly, for wireless multicast multi-hop network, we propose an adaptive compression coding scheme to upgrade transmitted efficiency based on characteristics of the WSN. Theoretical computer simulation results show that this proposed scheme achieves significant performance gains over the previous scheme which just employing network coding. (3) On the basis of multi-path intra-flow network coding and sequence entropy of Shannon information theory, this paper proposes an improved network coding scheme based on redundancy compression for multipath network. For general wireless network, this paper studies on compressing data redundancy further in the WSN and proposes a compression coding scheme based on multi-path network coding. Theoretical analysis and computer simulation results illustrate that our proposed strategy not only reduces the redundant data and further improves the efficiency of network transmission, but also has a wide range of applications.
Keywords/Search Tags:Intra-flow network coding, Inter-flow network coding, Wireless sensor network, IOT, Distributed source coding, Opportunistic network coding, Sequence similarity, Redundancycompression
PDF Full Text Request
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