Making many people happy: Greedy solutions for content distribution
The increase in multimedia content makes providing good quality of service in wireless networks a challenging problem. Consider a set of users, with different content interests, connected to the same base station. The base station can only broadcast a limited amount of content, but wishes to satisfy the largest number of users. We approach this problem by considering each user as a point in a 2-D space, and each type of broadcast content as a circle. A point that is covered by a circle will be satisfied, and the closer the point is to the center of the circle, the higher the satisfaction. In this paper, we first formulate this problem as an optimal content distribution problem and show that it is NP-hard. The optimal problem can also be extended into an m-dimensional (m-D) space, and distance measurements can be expressed in a general p-norm. We then introduce three local greedy algorithms and compare their complexity. The approximation ratio of our greedy algorithms to the optimization problem is also formally analyzed in this paper. We perform extensive simulations using various conditions to evaluate our greedy algorithms. The results demonstrate that our solutions perform well and reflect our analytical results.
|Keywords||Approximation ratio, Content distribution, Local greedy algorithm, Maximum coverage, Optimization|
|Conference||40th International Conference on Parallel Processing, ICPP 2011|
Wang, Y. (Yunsheng), Guo, Y, & Wu, J. (Jie). (2011). Making many people happy: Greedy solutions for content distribution. In Proceedings of the International Conference on Parallel Processing (pp. 693–702). doi:10.1109/ICPP.2011.31