The design of survivable mesh based communication networks has received considerable attention in recent years. One task is to route backup paths and allocate spare capacity in the network to guarantee seamless communications services survivable to a set of failure scenarios. This is a complex multi-constraint optimization problem, called the spare capacity allocation (SCA) problem. This paper unravels the SCA problem structure using a matrix-based model, and develops a fast and efficient approximation algorithm, termed successive survivable routing (SSR). First, per-flow spare capacity sharing is captured by a spare provision matrix (SPM) method. The SPM matrix has a dimension the number of failure scenarios by the number of links. It is used by each demand to route the backup path and share spare capacity with other backup paths. Next, based on a special link metric calculated from SPM, SSR iteratively routes/updates backup paths in order to minimize the cost of total spare capacity. A backup path can be further updated as long as it is not carrying any traffic. Furthermore, the SPM method and SSR algorithm are generalized from protecting all single link failures to any arbitrary link failures such as those generated by Shared Risk Link Groups or all single node failures. Numerical results comparing several SCA algorithms show that SSR has the best trade-off between solution optimality and computation speed.

/pdf/approximating-optimal-spare-capacity-allocation-by-o5zzajk47a.pdf

Approximating optimal spare capacity allocation by successive survivable routing

Spare capacity allocation (SCA) is an important part of a fault tolerant network design. In the spare capacity allocation problem one seeks to determine where to place spare capacity in the network and how much spare capacity must be allocated to guarantee seamless communications services survivable to a set of failure scenarios (e.g., any single link failure). Formulated as a multi-commodity flow integer programming problem, SCA is known to be NP-hard. We provide a two-pronged attack to approximate the optimal SCA solution: unravel the SCA structure and find an effective algorithm. First, a literature review on the SCA problem and its algorithms is provided. Second, a integer programming model for SCA is provided. Third, a simulated annealing algorithm using the above INP model is introduced. Next, the structure of SCA is modeled by a matrix method. The per-flow based backup path information are aggregated into a square matrix, called the spare provision matrix (SPM). The size of the SPM is the number of links. Using the SPM as the state information, a new adaptive algorithm is then developed to approximate the optimal SCA solution termed successive survivable routing (SSR). SSR routes link-disjoint backup paths for each traffic flow one at a time. Each flow keeps updating its backup path according to the current network state as long as the backup path is not carrying any traffic. In this way, SSR can be implemented by shortest path algorithms using advertised state information with complexity of O( Link/sup 2/). The analysis also shows that SSR is using a necessary condition of the optimal solution. The numerical results show that SSR has near optimal spare capacity allocation with substantial advantages in computation speed.

A method of designing a telecommunications network, the method comprising the steps of A) for all working demand flows required to be routed in the telecommunications network, finding an initial topology of spans between nodes in the telecommunications network that is sufficient for routing all working demand flows, while attempting to minimize the cost of providing the spans; B) given the initial topology of spans identified in step A, finding a set of additional spans that ensures restorability of working demand flows that are required to be restored in case of failure of any span in the initial topology of spans, while attempting to minimize the cost of providing additional spans; and C) starting with the initial topology of spans and the additional spans identified in step B, finding a final topology of spans between nodes in the telecommunications network that attempts to minimize the total cost of the final topology of spans, while routing all working demand flows and ensuring restorability of working demand flows required to be restored in case of failure of any span in the final topology of spans. A network so designed may be implemented in whole or in part.

http://www.ece.ualberta.ca/~grover/pdf/Grover-Doucette-AOR2001-MeshTopology.pdf

Topological design of survivable mesh-based transport networks

A method is given for deriving a backup path routing spare capacity template that is feasible, scalable, adaptive, much faster, and near global optimal in redundancy reduction. The method includes determining working paths, aggregating the working paths into a first matrix, determining backup paths, aggregating the backup paths into a second matrix, and deriving the template from the first and second matrices. A method is also given for successively approximating the optimal spare capacity allocation needed for a network. The method includes, determining the link cost associated with a selected traffic flow's backup path, determining an updated link cost that is less than the current link cost, determining a backup path with the updated link cost, and notifying the rest of the network of the backup path.

Apparatus and method for spare capacity allocation

This article addresses the problem of defining working and protection paths for scheduled lightpath demands (SLDs) in an optical transport network. An SLD is a demand for a set of lightpaths (connections), defined by a tuple (s, d, n, /spl alpha/, /spl omega/), where s and d are the source and destination nodes of the lightpaths, n is the number of requested lightpaths and /spl alpha/, /spl omega/ are the set-up and tear-down dates of the lightpaths. The problem is formulated as a combinatorial optimization problem where the objective is to minimize the number of channels required to instantiate the lightpaths. Two techniques are used to achieve this goal: channel reuse and backup-multiplexing. The former consists of assigning the same channel (either working or spare) to several lightpaths, provided that these lightpaths are not simultaneous in time. The latter consists of sharing a spare channel among multiple lightpaths. A spare channel cannot be shared if two conditions hold: a) the working paths of these lightpaths have at least one span in common and b) these lightpaths are simultaneous in time. In the other cases, the spare channel can be shared. We propose a simulated annealing (SA) based algorithm to find approximate solutions to this optimization problem since finding exact solutions is computationally intractable. The results show that backup-multiplexing improves the utilization of channels but requires significant computing capacity. Under a fixed computing capacity budget, the technique is useful in cases where there is little time disjointness among SLDs.

Diverse routing of scheduled lightpath demands in an optical transport network

Many sectors of society, business, and industry have become dependent on the availability of communication networks. Today virtually all forms of traffic, whether circuit switched as in telephony, cell-based, or packet-switched, such as in B-ISDN or the Internet, are combined into standard synchronous optical network (SONET) carrier signals for transport on fiber optic transmission systems. A pair of optical fibers operating at the SONET rate of 9.8 Gb/s (called an OC-192) carries the equivalent of 129,000 voice or data circuits. A single cable may contain 48 or more of these fibers. The sheer volume of traffic makes the impact of a cable cut widespread and severe. Such events are, however, surprisingly frequent in practice. They have not only caused widespread congestion effects, but more serious effects such as loss of 911 service, loss of credit card services, and even the shut down of a major air traffic control network (MacDonald, 1994).

R. R. Iraschko

Papers

Comparative Methods and Issues In Design of Mesh-Restorable STM and ATM Networks