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Ant-Inspired Mini-Community-Based Solution for Video-On-Demand Services in Wireless Mobile Networks

机译:基于蚂蚁启发的基于小型社区的无线移动网络视频点播服务解决方案

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摘要

Highly efficient distribution and management of media resources and fast content discovery are key determinants for mobile peer-to-peer video-on-demand solutions, especially in wireless mobile networks. Virtual communities making use of users' common characteristics such as interest and interaction to describe the boundary of sharing content and objects are a promising avenue for high-efficiency resource sharing. In this paper, we propose a novel ant-inspired mini-community-based video sharing solution for on-demand streaming services in wireless mobile networks (AMCV). AMCV relies on a newly designed two layer architecture and on an algorithm inspired from the indirect communication between ants via pheromone trails which enables them to discover and use shortest paths. The architecture is composed of a mini-community network layer and a community member layer. The ant-inspired algorithm enables finding the common interest of users in video content within large amounts of pseudo disorderly interactive behavior data. AMCV proposes an ant colony optimization-based community communication strategy that dynamically bridges communities to support fast search for resources. AMCV achieves high scalability by making use of a designed community maintenance mechanism to uniformly distribute the maintenance cost of members and resources in the community, according to various member roles. Simulation-based testing shows how AMCV outperforms another state-of- the-art solution in terms of a wide set of performance metrics.
机译:媒体资源的高效分发和管理以及快速的内容发现是移动点对点视频点播解决方案的关键决定因素,尤其是在无线移动网络中。虚拟社区利用用户的共同特征(例如兴趣和互动)来描述共享内容和对象的边界,这是高效资源共享的有希望的途径。在本文中,我们为无线移动网络(AMCV)中的点播流服务提出了一种新颖的基于蚂蚁启发的基于小型社区的视频共享解决方案。 AMCV依赖于新设计的两层体系结构以及受信息素路径之间蚂蚁之间的间接通信启发的算法,该算法使蚂蚁能够发现和使用最短路径。该体系结构由一个小型社区网络层和一个社区成员层组成。蚂蚁启发算法可以在大量伪无序互动行为数据中找到用户对视频内容的共同兴趣。 AMCV提出了一种基于蚁群优化的社区交流策略,该策略可动态地桥接社区以支持快速搜索资源。 AMCV通过使用设计的社区维护机制来实现高可伸缩性,以根据各种成员角色来均匀分配社区中成员和资源的维护成本。基于仿真的测试显示了AMCV在广泛的性能指标方面如何胜过其他最新解决方案。

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