Shared risk link Group (SRLG)-diverse path provisioning under hybrid service level agreements in wavelength-routed optical mesh networks
Shared risk link Group (SRLG)-diverse path provisioning under hybrid service level agreements in wavelength-routed optical mesh networks
复制标题
DOI：
10.1109/tnet.2005.852879
复制
发表时间：
2005-08
期刊：
影响因子：
--
通讯作者：
Lu Shen;Xi Yang;B. Ramamurthy
中科院分区：
文献类型：
--
作者：
Lu Shen;Xi Yang;B. Ramamurthy
波长路由光网络中的静态配置问题已被研究多年。然而，服务提供商仍然面临着光层业务提供的特殊要求所带来的挑战。在本文中，我们将一些现实约束纳入静态供应问题，并在不同的网络资源可用性条件下制定它。我们考虑三类共享风险链路组（SRLG）——多样化路径保护方案：专用、共享和无保护。我们将每个连接请求与光路长度约束和收入值相关联。当网络资源不足以容纳所有连接请求时，静态供应问题被表述为收入最大化问题，其目标是最大化总收入值。当网络拥有足够的资源时，问题就变成了容量最小化问题，其目标是最小化所使用的波长链路的数量。我们为这些问题提供整数线性规划（ILP）公式。由于解决这些 ILP 问题非常耗时，因此我们提出了一种禁忌搜索启发式方法来在合理的时间内解决这些问题。我们还基于之前的工作开发了一种重新路由优化启发式方法。给出了实验结果来比较禁忌搜索启发式和重新路由优化启发式所获得的解决方案。对于这两个问题，禁忌搜索启发式优于重新路由优化启发式。
The static provisioning problem in wavelength-routed optical networks has been studied for many years. However, service providers are still facing the challenges arising from the special requirements for provisioning services at the optical layer. In this paper, we incorporate some realistic constraints into the static provisioning problem, and formulate it under different network resource availability conditions. We consider three classes of shared risk link group (SRLG)-diverse path protection schemes: dedicated, shared, and unprotected. We associate with each connection request a lightpath length constraint and a revenue value. When the network resources are not sufficient to accommodate all the connection requests, the static provisioning problem is formulated as a revenue maximization problem, whose objective is maximizing the total revenue value. When the network has sufficient resources, the problem becomes a capacity minimization problem with the objective of minimizing the number of used wavelength-links. We provide integer linear programming (ILP) formulations for these problems. Because solving these ILP problems is extremely time consuming, we propose a tabu search heuristic to solve these problems within a reasonable amount of time. We also develop a rerouting optimization heuristic, which is based on previous work. Experimental results are presented to compare the solutions obtained by the tabu search heuristic and the rerouting optimization heuristic. For both problems, the tabu search heuristic outperforms the rerouting optimization heuristic.