Adaptive Data Broadcast in Hybrid Networks.

摘要

Hybrid networks combine multiple communication modes and are fast emerging as the most viable solution for the ever increasing demand for bandwidth and data services. Taking advantage of this new technology, we are proposing a hybrid scheme which effectively combines broadcast for massive data dissemination and unicast for individual data delivery. The goal is to build highly scalable systems with small response time. In this paper, we describe a technique that continuously adapts the broadcast content to match the hot-spot of the workload. We show that the hot-spot can be accurately obtained by monitoring the 'broadcast misses' observed through direct requests. This is a major departure from all other broadcast optimization schemes which are handicapped by their total reliance on complete knowledge of both 'hits' and 'misses'. We also show that the proposed adaptive scheme performs effectively even under very dynamic and rapidly changing workloads. Extensive simulation results demonstrate both the scalability and versatility of the technique. Another basic result obtained in this paper is that the overall system's throughput depends only on the size of the hot-spot and not on the volume of the workload. This has far reaching implications for very large scale and high volume wide area information systems.