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    • 2. 发明申请
    • PREDICTIVE NETWORK SYSTEM AND METHOD
    • 预测网络系统和方法
    • US20140113600A1
    • 2014-04-24
    • US13876781
    • 2011-09-28
    • Hesham El GamalAtilla EryilmazGiuseppe CaireFei ShaMargaret McLaughlin
    • Hesham El GamalAtilla EryilmazGiuseppe CaireFei ShaMargaret McLaughlin
    • H04L12/911H04W28/02
    • H04L47/823H04W28/02H04W28/16
    • A proactive networking system and method is disclosed. The network anticipates the user demands in advance and utilizes this predictive ability to reduce the peak to average ratio of the wireless traffic and yield significant savings in the required resources to guarantee certain Quality of Service (QoS) metrics. The system and method focuses on the existing cellular architecture and involves the design and analysis of learning algorithms, predictive resource allocation strategies, and incentive techniques to maximize the efficiency of proactive cellular networks. The system and method further involve proactive peer-to-peer (P2P) overlaying, which leverages the spatial and social structure of the network. Machine learning techniques are applied to find the optimal tradeoff between predictions that result in content being retrieved that the user ultimately never requests, and requests that are not anticipated in a timely manner.
    • 公开了主动联网系统和方法。 该网络提前预测用户需求,并利用这种预测能力来降低无线流量的平均峰值比,并显着节省所需资源以保证某些服务质量(QoS)指标。 该系统和方法着重于现有的蜂窝架构,涉及学习算法的设计和分析,预测资源分配策略和激励技术,以最大化主动蜂窝网络的效率。 该系统和方法还涉及主动对等(P2P)覆盖,利用网络的空间和社会结构。 应用机器学习技术来找到导致用户最终从未请求的内容被检索的预测之间的最佳权衡,以及及时预期的请求。