1916771
Performance Evaluation of Distributed Prefetching for Asynchronous Multicast in P2P Networks
We consider the problem of delivering real-time, near real-time and stored streaming media to a large number of asynchronous clients. This problem has been studied in the context of asynchronous multicast and peer-to-peer content distribution. In this paper we evaluate through extensive simulations the performance of the distributed prefetching protocol, dPAM [20], proposed for scalable, asynchronous multicast in P2P systems. We show that the prefetch-and-relay strategy of dPAM can reduce the server bandwidth requirement quite significantly, compared to the previously proposed cache-and-relay strategy, even when the group of clients downloading a stream changes quite frequently due to client departures.
850717
dPAM: a distributed prefetching protocol for scalable asynchronous multicast in P2P systems
We leverage the buffering capabilities of end-systems to achieve scalable, asynchronous delivery of streams in a peer-to-peer environment. Unlike existing cache-and-relay schemes, we propose a distributed prefetching protocol where peers prefetch and store portions of the streaming media ahead of their playout time, thus not only turning themselves to possible sources for other peers but their prefetched data can allow them to overcome the departure of their source-peer. This stands in sharp contrast to existing cache-and-relay schemes where the departure of the source-peer forces its peer children to go the original server, thus disrupting their service and increasing server and network load. Through mathematical analysis and simulations, we show the effectiveness of maintaining such asynchronous multicasts from several source-peers to other children peers, and the efficacy of prefetching in the face of peer departures. We confirm the scalability of our dPAM protocol as it is shown to significantly reduce server load.
768842
ArrayD: A general purpose software for Microarray design
BackgroundMicroarray is a high-throughput technology to study expression of thousands of genes in parallel. A critical aspect of microarray production is the design aimed at space optimization while maximizing the number of gene probes and their replicates to be spotted.ResultsWe have developed a software called 'ArrayD' that offers various alternative design solutions for an array given a set of user requirements. The user feeds the following inputs: type of source plates to be used, number of gene probes to be printed, number of replicates and number of pins to be used for printing. The solutions are stored in a text file. The choice of a design solution to be used will be governed by the spotting chemistry to be used and the accuracy of the robot.ConclusionsArrayD is a software for standard cartesian robots. The software aids users in preparing a judicious and elegant design. ArrayD is universally applicable and is available at http://www.igib.res.in/scientists/arrayd/arrayd.html.
5821670
Learning in Logic with RichProlog
Deduction and induction are unified on the basis of a generalized notion of logical consequence, having classical first-order logic as a particular case. RichProlog is a natural extension of Prolog rooted in this generalized logic, in the same way as Prolog is rooted in classical logic. Prolog can answer ?1 queries as a side effect of a deductive inference. RichProlog can answer ?1 queries, ?1 queries (as a side effect of an inductive inference), and ?2 queries (as a side effect of an inductive inference followed by a deductive inference). RichProlog can be used to learn: a learning problem is expressed as a usual logic program, supplemented with data, and solved by asking a ?2 query. The output is correct in the limit, i.e., when sufficient data have been provided.