机会网络路由策略及拥塞控制研究

发布时间：2018-05-25 02:33

本文选题：机会网络 + 数据转发　；参考：《新疆大学》2016年硕士论文

【摘要】：机会网络是一种新型的移动自组织网络,具有节点间链路频繁断开的特点,整个网络通常处于不连通的状态,这就导致传统无线网络中的路由协议无法正常运行,所以机会网络中节点通常采用“存储-携带-转发”的方式。由于节点在运动过程中需要携带消息,因此选择合适的节点进行数据的转发就成了重要的研究问题。近年来路由技术的研究发现,网络中20%的重要节点完成了几乎80%的数据转发任务,这就容易引起节点的缓存拥塞,从而影响整个网络的性能,因此机会网络的路由技术以及拥塞控制成为了研究的重点内容。本文结合了社会网络的特点,以及存储的特性开展拥塞控制算法研究,主要工作如下:(1)提出了一种基于节点身份转换的机会网络拥塞控制策略。算法通过设置不同拥塞阈值,将节点分为轻度拥塞、中度拥塞以及重度拥塞。针对不同的拥塞等级,节点选择仅接收、仅转发以及接收并转发身份参与到路由协议中进行数据的转发。为了防止节点盲目的丢弃消息,提出了一种消息处理方法。首先对消息按照其自身价值进行排序,当节点缓存空间已被占满,根据节点拥塞等级不同,选择直接丢弃或者迁移消息。最后在Epidemic算法的基础上进行了改进,提出了EpidemicCC(Epidemic Congestion Control)拥塞控制策略。(2)提出了一种基于社会感知的机会网络拥塞控制算法。算法在选择合适的中继转发节点时,通过计算节点间的直接社会关系、间接社会关系以及节点的接收能力作为转发效用值,接收能力即节点的可用缓存空间大小。综合考虑节点的效用值,避免将消息转发给重要但已经拥塞的节点。为了防止节点盲目的删除消息,提出了一种基于社会感知的消息管理策略,当接收节点拥塞时,根据自身缓存消息的社会效用值,将效用值低的消息删除。为了验证算法的有效性,本文使用机会网络仿真软件ONE对提出的拥塞控制算法进行仿真,仿真结果表明,所设计的拥塞控制算法能够有效的降低网络的拥塞程度,减少网络中消息的副本数量,提高了消息交付率。
[Abstract]:Opportunity network is a new type of mobile ad hoc network, which has the characteristics of frequent disconnection between nodes, and the whole network is usually disconnected, which leads to the routing protocol in the traditional wireless network can not run normally. Therefore, the node in the opportunity network usually adopts the way of "store-carry-forward". Because the nodes need to carry messages in the process of motion, it is an important research problem to select the appropriate nodes to transmit the data. In recent years, the research of routing technology found that 20% of the important nodes in the network have completed almost 80% of the tasks of data forwarding, which can easily lead to the buffer congestion of the nodes, thus affecting the performance of the entire network. Therefore, the routing technology and congestion control of opportunistic networks have become the focus of research. This paper combines the characteristics of social networks and the characteristics of storage to develop congestion control algorithms. The main work is as follows: 1) A congestion control strategy based on node identity conversion in opportunistic networks is proposed. By setting different congestion thresholds, the algorithm divides nodes into mild congestion, moderate congestion and heavy congestion. For different congestion levels, nodes choose only receive, forward only and receive and forward identity to participate in data forwarding in routing protocols. In order to prevent nodes from dropping messages blindly, a message processing method is proposed. Firstly, the messages are sorted according to their own value. When the buffer space is filled, the message is discarded or migrated directly according to the different congestion level of the node. Finally, based on the improvement of Epidemic algorithm, a new congestion control algorithm based on social perception for opportunistic networks is proposed, which is called EpidemicCC(Epidemic Congestion Control congestion Control Strategy. When selecting the appropriate relay forwarding node, the algorithm calculates the direct social relationship between the nodes, indirect social relations and the receiving ability of the node as the forwarding utility value, the receiving ability is the size of the available cache space of the node. Considering the utility value of nodes, we avoid forwarding messages to important but congested nodes. In order to prevent nodes from blindly deleting messages, a message management strategy based on social perception is proposed. When the receiving node is congested, the message with low utility value is deleted according to the social utility value of its own cached message. In order to verify the effectiveness of the proposed algorithm, this paper uses the opportunistic network simulation software ONE to simulate the proposed congestion control algorithm. The simulation results show that the designed congestion control algorithm can effectively reduce the congestion degree of the network. Reduce the number of copies of messages in the network, improve the message delivery rate.
【学位授予单位】：新疆大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TN929.5

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