maximizing restorable throughput in mpls networks

M.LAKSHMI,N.LAKSHMI

Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology

ISSN: 2321-3337          Impact Factor:1.521         Volume:3         Issue:2         Year: 25 August,2014         Pages:375-380

International Journal of Advanced Research in Computer Science Engineering and Information Technology

Abstract

MPLS recovery mechanisms are increasing in popularity because they can guarantee fast restoration and high QoS assurance. Their main advantage is that their backup paths are established in advance, before a failure event takes place. Most research on the establishment of primary and backup paths has focused on minimizing the added capacity required by the backup paths in the network. This so-called Spare Capacity Allocation (SCA) metric is less practical for network operators who have a fixed capacitated network and want to maximize their revenues. We present a comprehensive study on restorable throughput maximization in MPLS networks. We present the first polynomial-time algorithms for the split table version of the problem. We provide a lower bound for the approximation ratio and propose an approximation algorithm with an almost identical bound. We present an efficient heuristic which is shown to have excellent performance. One of our most important conclusions is that when one seeks to maximize revenue, local recovery should be the recovery scheme of choice.

Kewords

IP,LR(LOCAL RECOVERY).

Reference

[1] Chieh-Jen Cheng, Chao-Ching Wang, Wei-Chun Ku, Tien-Fu Chen , and Jinn-Shyan Wang, “Scalable High-Performance Virus Detection Processor Against a Large Pattern Set for Embedded Network Security” Commun. vol. 51, pp. 62–70,2011. [2] O. Villa, D. P. Scarpazza, and F. Petrini, “Accelerating real-time string searching with multicore processors,” Computer, vol. 41, pp. 42–50,2008. [3] D. P. Scarpazza, O. Villa, and F. Petrini, “High-speed string searching against large dictionaries on the Cell/B.E. processor,” in Proc. IEEE Int. Symp. Parallel Distrib. Process., 2008, pp. 1–8. [4] D. P. Scarpazza, O. Villa, and F. Petrini, “Peak-performance DFA based string matching on the Cell processor,” in Proc. IEEE Int. Symp. Parallel Distrib. Process., 2007, pp. 1–8. [5] L. Tan and T. Sherwood, “A high throughput string matching architecture for intrusion detection and prevention,”in Proc. 32nd Annu. Int. Symp. Comput. Arch., 2005, pp. 112–122. [6] S. Dharmapurikar, P. Krishnamurthy, and T. S. Sproull, “Deep packet inspection using parallel bloom filters,” IEEE Micro, vol. 24, no. 1, pp.52–61, Jan. 2004. [7] R.-T. Liu, N.-F. Huang, C.-N. Kao, and C.-H. Chen, “A fast string matching algorithm for network processor-based intrusion detection system,” ACMTrans. Embed. Comput. Syst., vol. 3, pp. 614–633, 2004. [8] F. Yu, R. H. Katz, and T. V. Lakshman, “Gigabit rate packet pattern matching using TCAM,” in Proc. 12th IEEE Int. Conf. Netw. Protocols, 2004, pp. 174–178.intrusion detection system,” ACMTrans. Embed. Comput. Syst., vol. 3, pp. 614–633, 2004.