Literature DB >> 26867211

Minimal Increase Network Coding for Dynamic Networks.

Guoyin Zhang1, Xu Fan1, Yanxia Wu1.   

Abstract

Because of the mobility, computing power and changeable topology of dynamic networks, it is difficult for random linear network coding (RLNC) in static networks to satisfy the requirements of dynamic networks. To alleviate this problem, a minimal increase network coding (MINC) algorithm is proposed. By identifying the nonzero elements of an encoding vector, it selects blocks to be encoded on the basis of relationship between the nonzero elements that the controls changes in the degrees of the blocks; then, the encoding time is shortened in a dynamic network. The results of simulations show that, compared with existing encoding algorithms, the MINC algorithm provides reduced computational complexity of encoding and an increased probability of delivery.

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Year:  2016        PMID: 26867211      PMCID: PMC4750993          DOI: 10.1371/journal.pone.0148725

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  1 in total

1.  Exact and heuristic algorithms for Space Information Flow.

Authors:  Alfred Uwitonze; Jiaqing Huang; Yuanqing Ye; Wenqing Cheng; Zongpeng Li
Journal:  PLoS One       Date:  2018-03-27       Impact factor: 3.240

  1 in total

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