DAG Based Multipath Routing Algorithm for Load Balancing in Machine-to-Machine Networks
DAG Based Multipath Routing Algorithm for Load Balancing in Machine-to-Machine Networks
复制标题
基于 DAG 的机器对机器网络负载均衡多路径路由算法
DOI：
10.1155/2014/457962
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发表时间：
2013-12
影响因子：
2.3
通讯作者：
Zhang, Jun
中科院分区：
文献类型：
--
作者：
Liu, Liang;Zhang, Tao;Zhang, Jun
在M2M网络中，大多数节点由电池供电，因此过度使用的节点很容易断电，这导致网络寿命的减少。为了解决这个问题，将网络负载均衡到更多的节点和链路上，有助于减少网络拥塞。多路径路由是一种有效的工具，以减少拥塞，因为数据流可以分散到多个路径。然而，以往的多路径路由算法大多是基于路径不相交约束的，这导致路由路径的缺乏，无法将数据流分散到更多的链路。提出了一种基于有向无环图的拥塞最小化多路径路由算法（DAGMR），该算法将不同的路由路径限制在一个有向无环图中，并满足时延约束。此外，数据流分配是通过部分容量网络，以获得最小的多径路由拥塞因子。仿真结果表明，与路径不相交约束的算法相比，该算法可以获得更低的拥塞因子，并生成更多节点和链路的多路径路由图。此外，我们的算法是一个多项式时间复杂度的算法与节点和链接的整个网络的数量。
In M2M networks, most nodes are powered by battery; hence the overused nodes may easily be out of power, which causes the reduction of network lifetime. To solve this problem, it is helpful to balance network load into more nodes and links, so as to reduce network congestion. Multipath routing is a useful tool to reduce congestion, since data flow can be dispersed into multiple paths. However, most of the previous multipath routing algorithm is based on the path disjoint constraint, which leads to the lack of routing paths and the failure to disperse data flow into more links. In this paper, a directed acyclic graph based multipath routing algorithm for congestion minimization (DAGMR) is proposed, where different routing paths are confined in a directed acyclic graph (DAG) under time delay constraint. Furthermore, the data flow distribution is accomplished through partial capacity network to obtain the minimal multipath routing congestion factor. Simulation indicates that our algorithm can obtain lower congestion factor and formulates multipath routing graph with more nodes and links than algorithm with path disjoint constraint. In addition, our algorithm is a polynomial time complexity algorithm with nodes and links number of the entire network.
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DOI：
--
发表时间：
2011
期刊：
--
影响因子：
--
作者：
Wenjing Yang;Xinyu Yang;Guozheng Liu;C. Dong
通讯作者：
Wenjing Yang;Xinyu Yang;Guozheng Liu;C. Dong
影响因子：
1.1
作者：
Kyriaki Ioannidou;Stavros D. Nikolopoulos
通讯作者：
Kyriaki Ioannidou;Stavros D. Nikolopoulos
影响因子：
3.6
作者：
David K. Smith
通讯作者：
David K. Smith
影响因子：
7.2
作者：
Shio Kumar Singh;M. P. Singh;Asst. Professor;D. K. Singh
通讯作者：
Shio Kumar Singh;M. P. Singh;Asst. Professor;D. K. Singh
DOI：
10.1109/iciss.2010.5657149
发表时间：
2010-12
期刊：
2010 International Conference on Intelligent Computing and Integrated Systems
影响因子：
--
作者：
Wenchao Jiang;Qingyun Dai;Yanhong Zhou;Rong-zhen Liu
通讯作者：
Wenchao Jiang;Qingyun Dai;Yanhong Zhou;Rong-zhen Liu