移動機會網(wǎng)絡中數(shù)據(jù)傳輸優(yōu)化研究
發(fā)布時間：2018-10-24 06:20
【摘要】：移動機會網(wǎng)絡(MONs)是一種面向缺乏持續(xù)端到端連接的網(wǎng)絡新模式,其部分概念源自延遲容忍網(wǎng)絡(DTN)的研究。由于網(wǎng)絡中節(jié)點的移動性,導致連接中斷和網(wǎng)絡分割現(xiàn)象,而且節(jié)點自身還受能耗與存儲容量限制,這些特征使得數(shù)據(jù)傳輸面臨極大挑戰(zhàn)。傳統(tǒng)的路由方案不考慮數(shù)據(jù)的大小,當需要傳輸大體量文件時,如傳輸多媒體廣告或分享視頻文件,中繼節(jié)點的存儲空間將成為實現(xiàn)更高性能的瓶頸。在移動機會網(wǎng)絡中多播路由是一項重要研究課題,傳統(tǒng)的多播路由是傳輸消息給預先確定的多個目的節(jié)點。然而,當目的節(jié)點不明確時,基于移動機會網(wǎng)絡的多播傳輸將非常具有挑戰(zhàn)性。本文圍繞移動機會網(wǎng)絡中的多媒體數(shù)據(jù)傳輸以及多播路由問題進行研究。首先,關于多媒體數(shù)據(jù)傳輸問題分別針對多媒體文件單播與多媒體廣告廣播兩種應用場景進行算法研究。其次,針對移動機會網(wǎng)絡中的多播路由分別提出K-Anycast問題以及M×N多源多播問題,并通過研究提出相應的解決方案。本文的主要內(nèi)容如下:(1)針對移動機會網(wǎng)絡中多媒體數(shù)據(jù)量較大而存儲容量有限的情況,提出基于多背包問題的解決方案。其通過分布式的方式,將算法結合信道容量并獲得優(yōu)化組合,以實現(xiàn)局部最優(yōu)解。(2)提出了針對機會式車載網(wǎng)中基于出租車的多媒體廣告分發(fā)策略TaxiCast。首先它應用基于信號強度的編碼和解碼以獲得周圍車輛的廣告需求度,然后結合信道容量和多媒體廣告文件大小,將廣告選擇過程建模為背包問題。(3)提出了針對K-Anycast問題的多播轉發(fā)策略。首先利用二分匹配將其作為資源分配問題來解決。然后根據(jù)路由線索建立基于活躍度的分層結構。最后基于這種網(wǎng)絡結構,介紹了兩種算法(K-Cast和K-Epidemic)。(4)根據(jù)移動機會網(wǎng)絡中的M×N多源多播問題,提出了M×N搜索路由方案。首先提出一種主動模式下的分層結構,消息將沿著結構向上層方向傳輸。然后將基于單拷貝模式的轉發(fā)策略進行擴展,提出多拷貝委托轉發(fā)方案來進一步減少傳輸延遲。
[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.
【學位授予單位】：杭州電子科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN929.5
本文編號：2290565
[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.
【學位授予單位】：杭州電子科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN929.5
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