Throughput Optimal On-Line Algorithms for Advanced Resource Reservation in Ultra High-Speed Networks

Advanced channel reservation is emerging as an important feature of ultra high-speed networks requiring the transfer of large files. Applications include scientific data transfers and database backup. In this paper, we present two new, on-line algorithms for advanced reservation, called BatchAll and BatchLim, that are guaranteed to achieve optimal throughput performance, based on multi-commodity flow arguments. Both algorithms are shown to have polynomial-time complexity and provable bounds on the maximum delay for 1+epsilon bandwidth augmented networks. The BatchLim algorithm returns the completion time of a connection immediately as a request is placed, but at the expense of a slightly looser competitive ratio than that of BatchAll. We also present a simple approach that limits the number of parallel paths used by the algorithms while provably bounding the maximum reduction factor in the transmission throughput. We show that, although the number of different paths can be exponentially large, the actual number of paths needed to approximate the flow is quite small and proportional to the number of edges in the network. Simulations for a number of topologies show that, in practice, 3 to 5 parallel paths are sufficient to achieve close to optimal performance. The performance of the competitive algorithms are also compared to a greedy benchmark, both through analysis and simulation.Comment: 9 pages, 8 figure

Connected Identifying Codes for Sensor Network Monitoring

Abstract—Identifying codes have been proposed as an abstraction for implementing monitoring tasks such as indoor localization using wireless sensor networks. In this approach, sensors ’ radio coverage overlaps in unique ways over each identifiable region, according to the codewords of an identifying code. While connectivity of the underlying identifying code is necessary for routing data to a sink, existing algorithms that produce identifying codes do not guarantee such a property. As such, we propose a novel polynomial-time algorithm called ConnectID that transforms any identifying code into a connected version that is also an identifying code and is provably at most twice the size of the original. We evaluate the performance of ConnectID on various random graphs, and our simulations show that the connected codes generated are actually at most 25% larger than their non-connected counterparts. Index Terms—Localization, graph theory, approximation algorithms. I

On the Capacity Limits of Advanced Channel Reservation Architectures

The next generation of grid applications demand fast and reliable transfers of extremely large volumes of data between distributed sites around the world. For example, the U.S. Department of Energy’s Genomes to Life (GTL) project aim