In response to the high throughput needs of grid and cloud computing applications, several production networks have recently started to support advance reservation of dedicated circuits. An important open problem within this context is to devise advance reservation algorithms that can provide provable throughput performance guarantees independently of the specific network topology and arrival pattern of reservation requests. In this paper, we first show that the throughput performance of greedy approaches, which return the earliest possible completion time for each incoming request, can be arbitrarily worse than optimal. Next, we introduce two new online, polynomial-time algorithms for advance reservation, called BatchAll and BatchLim. Both algorithms are shown to be throughput-optimal through the derivation of delay bounds for 1+ bandwidth augmented networks. The BatchLim algorithm has the advantage of returning the completion time of a connection immediately as a request is placed, but at the expense of looser delay performance than BatchAll. We then propose a simple approach that limits path dispersion, i.e., the number of parallel paths used by the algorithms, while provably bounding the maximum reduction factor in the transmission throughput. We prove that the number of paths needed to approximate any flow is quite small and never exceeds the total number of edges in the network. Through simulation for various topologies and traffic parameters, we show that the proposed algorithms achieve reasonable delay performance, even at request arrival rates close to capacity bounds, and that three to five parallel paths are sufficient to achieve near-optimal performance.
Bibliographical noteFunding Information:
Manuscript received April 26, 2009; revised March 14, 2010; October 19, 2010; December 24, 2010; accepted December 28, 2010; approved by IEEE/ACM TRANSACTIONS ON NETWORKING Editor A. Feldmann. Date of publication January 28, 2011; date of current version October 14, 2011. This work was supported in part by the U.S. Department of Energy under ECPI Grant DE-FG02-04ER25605 and the U.S. National Science Foundation under CAREER Grant ANI-0132802 and Grant CCF-0729158. A shorter preliminary version of this paper appeared in the Proceedings of the High-Speed Networking Workshop at the IEEE International Conference on Computer Communications (INFOCOM), Phoenix, AZ, 2008.
- Approximation algorithms
- high-speed networks