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This paper presents and analyzes user behavior and network performance in a public-area wireless network using a workload captured at a well-attended ACM conference. The goals of our study are: (1) to extend our understanding of wireless user behavior and wireless network performance; (2) to characterize wireless users in terms of a parameterized model for use with analytic and simulation studies involving wireless LAN traffic; and (3) to apply our workload analysis results to issues in wireless network deployment, such as capacity planning, and potential network optimizations, such as algorithms for load balancing across multiple access points (APs) in a wireless network.

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Multimedia storage servers provide access to multimedia objects including text, images, audio, and video. The design of such servers fundamentally di ers from conventional servers due to: 1 the real-time storage and retrieval requirements, as well as 2 the large storage space and data transfer rate requirements of digital multimedia. In this paper, we present an overview of the architectures and algorithms required for designing digital multimedia storage servers.

Future advances in networking coupled with the rapid advances in storage technologies will make it feasible to build a HDTV-on-demand server (that provides services similar to those of a neighborhood videotape rental store) on a metropolitan-area network. In this paper, we present a quantitative study of designing a multiuser HDTV server, and present efficient techniques for (1) storing multiple HDTV videos on disk, and (2) servicing multiple subscriber requests simultaneously, both under the constraint of guaranteeing HDTV playback rates. We develop a model that relates disk and device characteristics to the HDTV playback rate, and derive a storage pattern for HDTV video streams that guarantees their real-time retrieval. Given multiple HDTV streams, we develop mechanisms for merging their individual storage patterns together. We propose an off-line merging algorithm that can be applied a priori, and an on-line algorithm suitable for merging a new HDTV stream into a set of already stored HDTV streams, both of which yield a large improvement in space utilization over storing each of the streams independently. We study various policies, such as, round robin and quality proportional for servicing multiple subscribers simultaneously. The quality proportional algorithm retrieves video frames at a rate proportional on an average to the HDTV playback rates of subscribers, but uses a staggered toggling technique in which successive numbers of retrieved frames are fine tuned individually to achieve the servicing of an optimal number of subscribers simultaneously. The algorithm is powerful enough to accommodate bounded availability of HDTV display buffers, and permits dynamic additions and deletions of subscriber requests in a transparent manner (i.e., without causing discontinuity in the retrieval of any of the existing subscribers). In summary, our studies provide a quantitative demonstration of the technological feasibility and economic viability of HDTV-on-demand servers on metropolitan area networks.