A fault tolerant channel allocation scheme in distributed cloud networks

被引:1
|
作者
Cho, Jae-Il [1 ,2 ]
Park, Kiheon [6 ]
Kim, TaeYeon [3 ]
Jeon, Hongseok [3 ]
Lee, Wonhyuk [4 ]
Kim, Hyuncheol [5 ]
机构
[1] Elect & Telecommun Res Inst, Taejon 305700, South Korea
[2] Sungkyunkwan Univ, Suwon 440746, South Korea
[3] Elect & Telecommun Res Inst, Taejon 305806, South Korea
[4] Korea Inst Sci & Technol Informat, Taejon 305806, South Korea
[5] Namseoul Univ, Dept Comp Sci, Cheonan, South Korea
[6] Sungkyunkwan Univ, Coll Informat & Commun Engn, Suwon 440746, South Korea
关键词
Cloud networks; Micro datacenter; Reverse Shared Risk Link Group; Recovery contention; Fast restoration; WDM; ALGORITHMS;
D O I
10.1007/s10586-015-0487-z
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the cloud computing, storage and computing resources are moving to remote resources such as virtual servers and storage systems in large datacenters, which raise many performance and management challenges. The distributed cloud networks must have an ability to maintain an acceptable level of service during network failures to provide high resilience against service failures. This paper presents an eccentric fault tolerant path grouping scheme that can achieve mobility independent Quality of Service guaranteed services in distributed cloud networks To make this possible, we propose a path allocation and restoration strategy called "Reverse Shared Risk Link Group" and demonstrates how this concept can be applied to minimize recovery contention in cloud networks and to assess the network convergence associated with failures. To reflect little more actual situations, we assume that the bandwidth of cloud connection requests can be some fraction of the lightpath capacity. Simulation results show that the proposed recovery scheme outperforms other schemes with fewer signaling traffics and contention probability. Very fast restorability can be accomplished for multiple failures. We also has developed an analytical model and performed analysis for the proposed scheme in terms of two performance factors: mean system time and reservation blocking probability.
引用
收藏
页码:1423 / 1433
页数:11
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