title: Minimal Increase Network Coding for Dynamic Networks.
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.
authors: College of Computer Science and Technology, Harbin Engineering University, Harbin, Heilongjiang, P. R. China.
authors: Guoyin
authors: G
authors: Zhang
authors: College of Computer Science and Technology, Harbin Engineering University, Harbin, Heilongjiang, P. R. China.
authors: Xu
authors: X
authors: Fan
authors: College of Computer Science and Technology, Harbin Engineering University, Harbin, Heilongjiang, P. R. China.
authors: Yanxia
authors: Y
authors: Wu
mesh_terms: D000465:Algorithms; D059019:Clinical Coding; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D003201:Computers; D006801:Humans; D015233:Models, Statistical; D011336:Probability; D011381:Programming Languages