User Aggregation Models for a Video-on-Demand (VoD) System

Subrato Mondal, Goutam Sen
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Abstract

We consider the scalability issues in the static data segment location problem in information networks and provide integer linear programming (ILP) formulations for user aggregation. We explore three approaches based on k-means clustering, locality-of-reference and biased locality of reference. The second and third approaches are innovatively modeled as discrete optimization problems. The models are tested in IBM ILOG CPLEX Optimization Studio platform and the computational results are discussed in this paper.
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视频点播(VoD)系统的用户聚合模型
考虑了信息网络中静态数据段定位问题中的可扩展性问题,给出了用户聚合的整数线性规划(ILP)公式。我们探索了基于k-means聚类、参考位置和参考偏置位置的三种方法。第二和第三种方法创新地建模为离散优化问题。在IBM ILOG CPLEX Optimization Studio平台上对模型进行了测试,并对计算结果进行了讨论。
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