About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
PODC 1988
Conference paper
The power of multimedia: Combining point-to-point and multiaccess networks
Abstract
In this paper we introduce a new network model called a multimedia network. It combines the point-to-point message passing network and the multiaccess channel. To benefit from the combination we design algorithms which consist of two stages: a local stage which utilizes the parallelism of the point-to-point network and a global stage which utilizes the broadcast capability of the multiaccess channel. As a reasonable approach, one wishes to balance the complexities of the two stages by obtaining an efficient partition of the network into O(√n) connected components each of radius O(√n). To this end we present efficient deterministic and randomized partitioning algorithms. The deterministic algorithm runs in O(√n log∗ n) time and O(m + n log n log∗ n) messages, where n and m are the number of nodes and number of point-to-point links in the network. The randomized algorithm runs in the same time, but sends only O(m+ n log∗ n) messages. The partitioning algorithms are then used to obtain: (1) O(√n log n log∗ n) time deterministic and O(√n log∗ n) time randomized algorithms for computing global sensitive functions, and (2) O(√n log n) time deterministic algorithm for computing a minimum spanning tree. An Ω(n) time lower bounds for computing global sensitive functions in both point-topoint and multiaccess networks, are given, thus showing that the multimedia network is more powerful than both its separate components. Furthermore, we prove an Ω(√n) time lower bound for multimedia networks, thus leaving a small gap between our upper and lower bounds.