移动机会网络中数据传输优化研究

发布时间：2018-10-24 06:20

【摘要】：移动机会网络(MONs)是一种面向缺乏持续端到端连接的网络新模式,其部分概念源自延迟容忍网络(DTN)的研究。由于网络中节点的移动性,导致连接中断和网络分割现象,而且节点自身还受能耗与存储容量限制,这些特征使得数据传输面临极大挑战。传统的路由方案不考虑数据的大小,当需要传输大体量文件时,如传输多媒体广告或分享视频文件,中继节点的存储空间将成为实现更高性能的瓶颈。在移动机会网络中多播路由是一项重要研究课题,传统的多播路由是传输消息给预先确定的多个目的节点。然而,当目的节点不明确时,基于移动机会网络的多播传输将非常具有挑战性。本文围绕移动机会网络中的多媒体数据传输以及多播路由问题进行研究。首先,关于多媒体数据传输问题分别针对多媒体文件单播与多媒体广告广播两种应用场景进行算法研究。其次,针对移动机会网络中的多播路由分别提出K-Anycast问题以及M×N多源多播问题,并通过研究提出相应的解决方案。本文的主要内容如下:(1)针对移动机会网络中多媒体数据量较大而存储容量有限的情况,提出基于多背包问题的解决方案。其通过分布式的方式,将算法结合信道容量并获得优化组合,以实现局部最优解。(2)提出了针对机会式车载网中基于出租车的多媒体广告分发策略TaxiCast。首先它应用基于信号强度的编码和解码以获得周围车辆的广告需求度,然后结合信道容量和多媒体广告文件大小,将广告选择过程建模为背包问题。(3)提出了针对K-Anycast问题的多播转发策略。首先利用二分匹配将其作为资源分配问题来解决。然后根据路由线索建立基于活跃度的分层结构。最后基于这种网络结构,介绍了两种算法(K-Cast和K-Epidemic)。(4)根据移动机会网络中的M×N多源多播问题,提出了M×N搜索路由方案。首先提出一种主动模式下的分层结构,消息将沿着结构向上层方向传输。然后将基于单拷贝模式的转发策略进行扩展,提出多拷贝委托转发方案来进一步减少传输延迟。
[Abstract]:Mobile opportunity Network (MONs) is a new network model for the lack of continuous end-to-end connection. Some of its concepts are derived from the research of delay tolerance Network (DTN). Because of the mobility of nodes in the network, which leads to the phenomenon of connection interruption and network segmentation, and the nodes themselves are limited by energy consumption and storage capacity, these characteristics make data transmission face great challenges. Traditional routing schemes do not consider the size of data. When large volume files need to be transferred such as multimedia advertising or sharing video files the storage space of relay nodes will become the bottleneck to achieve higher performance. Multicast routing is an important research topic in mobile opportunity networks. The traditional multicast routing is to transmit messages to a predetermined number of destination nodes. However, when the destination node is not clear, the multicast transmission based on the mobile opportunity network will be very challenging. This paper focuses on multimedia data transmission and multicast routing in mobile opportunity networks. Firstly, the algorithms of multimedia file unicast and multimedia advertisement broadcasting are studied. Secondly, K-Anycast problem and M 脳 N multi-source multicast problem are proposed for multicast routing in mobile opportunity networks, and the corresponding solutions are put forward through research. The main contents of this paper are as follows: (1) in view of the large amount of multimedia data and limited storage capacity in mobile opportunity networks, a solution based on multi-knapsack problem is proposed. In order to achieve the local optimal solution, the algorithm is combined with the channel capacity and optimized by distributed method. (2) the multimedia advertisement distribution strategy TaxiCast. based on taxi in the opportunistic vehicular network is proposed. It first applies signal-strength based coding and decoding to obtain the advertising requirements of the surrounding vehicle, and then combines channel capacity and multimedia advertising file size. The advertising selection process is modeled as knapsack problem. (3) Multicast forwarding strategy for K-Anycast problem is proposed. First, we use dichotomy to solve the problem of resource allocation. Then, based on the routing clues, a hierarchical structure based on activity is established. Finally, based on this network structure, two algorithms (K-Cast and K-Epidemic). (4) are introduced. According to the M 脳 N multi-source multicast problem in mobile opportunity networks, a M 脳 N search routing scheme is proposed. Firstly, a hierarchical structure in active mode is proposed, along which messages are transmitted along the upper layer. Then the forwarding strategy based on single copy mode is extended and a multi-copy delegation forwarding scheme is proposed to further reduce the transmission delay.
【学位授予单位】：杭州电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN929.5

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