Generalized Fibonacci broadcasting: An efficient VOD scheme with user bandwidth limit

AbstractBroadcasting is attractive in delivering popular videos in video-on-demand service, because the server broadcast bandwidth is independent of the number of users. However, the required server bandwidth does depend on how much bandwidth each user can use, as well as on the user's initial waiting time. This paper addresses the issue of limiting the user bandwidth, and proposes a new broadcasting scheme, named Generalized Fibonacci Broadcasting (GFB). In terms of many performance graphs, we show that, for any given combination of the server bandwidth and user bandwidth, GFB can achieve the least waiting time among all the currently known fixed-delay broadcasting schemes. Furthermore, it is very easy to implement GFB. We also demonstrate that there is a trade-off between the user waiting time and the buffer requirement at the user

The pp-Center Problem in Tree Networks Revisited

We present two improved algorithms for weighted discrete $p$-center problem for tree networks with $n$ vertices. One of our proposed algorithms runs in $O(n \log n + p \log^2 n \log(n/p))$ time. For all values of $p$, our algorithm thus runs as fast as or faster than the most efficient $O(n\log^2 n)$ time algorithm obtained by applying Cole's speed-up technique [cole1987] to the algorithm due to Megiddo and Tamir [megiddo1983], which has remained unchallenged for nearly 30 years. Our other algorithm, which is more practical, runs in $O(n \log n + p^2 \log^2(n/p))$ time, and when $p=O(\sqrt{n})$ it is faster than Megiddo and Tamir's $O(n \log^2n \log\log n)$ time algorithm [megiddo1983]

An O(n^2 log^2 n) Time Algorithm for Minmax Regret Minsum Sink on Path Networks

We model evacuation in emergency situations by dynamic flow in a network. We want to minimize the aggregate evacuation time to an evacuation center (called a sink) on a path network with uniform edge capacities. The evacuees are initially located at the vertices, but their precise numbers are unknown, and are given by upper and lower bounds. Under this assumption, we compute a sink location that minimizes the maximum "regret." We present the first sub-cubic time algorithm in n to solve this problem, where n is the number of vertices. Although we cast our problem as evacuation, our result is accurate if the "evacuees" are fluid-like continuous material, but is a good approximation for discrete evacuees