Optimal capacity placement for path restoration in STM or ATM mesh-survivable networks
TL;DR: A method for capacity optimization of path restorable networks which is applicable to both synchronous transfer mode (STM) and asynchronous transfermode (ATM) virtual path (VP)-based restoration and jointly optimizing working path routing and spare capacity placement.
Abstract: The total transmission capacity required by a transport network to satisfy demand and protect it from failures contributes significantly to its cost, especially in long-haul networks. Previously, the spare capacity of a network with a given set of working span sizes has been optimized to facilitate span restoration. Path restorable networks can, however, be even more efficient by defining the restoration problem from an end to end rerouting viewpoint. We provide a method for capacity optimization of path restorable networks which is applicable to both synchronous transfer mode (STM) and asynchronous transfer mode (ATM) virtual path (VP)-based restoration. Lower bounds on spare capacity requirements in span and path restorable networks are first compared, followed by an integer program formulation based on flow constraints which solves the spare and/or working capacity placement problem in either span or path restorable networks. The benefits of path and span restoration, and of jointly optimizing working path routing and spare capacity placement, are then analyzed.
Citations
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03 Jul 2005
TL;DR: Failure independent path-protecting (FIPP) p-cycles are an extension of the basic p-cycle concept which retains the property of pre-crossconnection of protection paths while acheiving end-to-end failure-independent path protection switching against either span or node failures as discussed by the authors.
Abstract: Failure independent path-protecting (FIPP) p-cycles are an extension of the basic p-cycle concept which retains the property of pre-cross-connection of protection paths while acheiving end-to-end failure-independent path protection switching against either span or node failures. An issue with the current method of shared-backup path protection (SBPP) in a transparent optical network is that spare channels for the backup path must be cross-connected on-the-fly upon failure. It takes extra time and signaling to make the required cross-connections but, more importantly, until all connections are made it is not actually known if the backup optical path has adequate transmission integrity. Thus, pre-failure certainty about optical path integrity is an important reason to have backup paths fully pre-connected before failure. FIPP p-cycles support the same failure-independent, end-node activated switching of SBPP but with fully pre-connected protection paths. FIPP p-cycles may therefore be especially attractive for transparent optical networks. FIPP p-cycle network designs also exhibit capacity efficiency that is characteristic of path-oriented schemes. We think it is the only scheme known with these very high efficiencies, failure independence, and the property of fully pre-cross-connected protection paths.
26 citations
Cites background from "Optimal capacity placement for path..."
...The theoretical importance and complications arising from this difference are developed further in [2] (and [4], [5] and [7])....
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25 Oct 2004
TL;DR: The main findings are that p-cycles do exhibit threshold hop-limiting effects (at about two or three hops above those in corresponding mesh networks) and that cycle limiting is a simple and effective surrogate for direct limitation on path lengths in p-cycle design problems.
Abstract: p-cycles offer an approach to protection of optical transport networks which is as fast as a ring-based network but with mesh-like capacity efficiency. One misconception about p-cycle designs seems to be that they involve long protection paths, even though it is trivial to limit the circumference of cycles admitted to the design problem. In addition, through straddling span considerations the average protection path on a p-cycle is actually shorter than in a corresponding ring. Nonetheless there are some open questions regarding path and cycle circumference limit effects with p-cycles. One question is whether p-cycle networks exhibit a "threshold hop-limit" effect corresponding to that well-known aspect of span-restorable mesh networks. (Beyond the threshold hop-limit there are negligible savings in capacity.) To study this question we extend the existing p-cycle network design theory to include the capability of direct restriction of protection path lengths, rather than indirect restriction through circumference limits. A second, quite practical question is to ask how well simple limitation of cycle circumferences serves as a surrogate for a more involved design method of directly asserting a hop (or distance) limit on the maximum length of protection paths. The answers to the questions and the methods developed to address them both enhance our ability to design p-cycle networks in which optically transparent length may affect transmission quality, or where the length of protection paths may affect cost if regeneration is required en route of a protection path. The main findings are that p-cycles do exhibit threshold hop-limiting effects (at about two or three hops above those in corresponding mesh networks) and that cycle limiting is a simple and effective surrogate for direct limitation on path lengths in p-cycle design problems.
26 citations
Cites background from "Optimal capacity placement for path..."
...Another advantage is that p-cycle protection can be based either on ADM-like “capacity slice” nodal devices (as in [2]) or on OXCmanaged optical networks where the p-cycle configuration can be logically managed on a per-channel basis to implement multi-priority protection, to adapt to changed…...
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TL;DR: A rigorous mathematical framework for designing the generalized survivable network (GSN), which has the special property that it remains survivable no matter how traffic is provisioned dynamically, as long as the input and output constraints at the nodes are fixed.
Abstract: Two important requirements for future backbone networks are full survivability against link failures and dynamic bandwidth provisioning. We demonstrate how these two requirements can be met by introducing a new survivable network concept called the generalized survivable network (GSN), which has the special property that it remains survivable no matter how traffic is provisioned dynamically, as long as the input and output constraints at the nodes are fixed. A rigorous mathematical framework for designing the GSN is presented. In particular, we focus on the GSN capacity planning problem, which finds the edge capacities for a given physical network topology with the input/output constraints at the nodes. We employ fixed single-path routing which leads to wide-sense nonblocking GSNs. We show how the initial, infeasible formal mixed integer linear programming formulation can be transformed into a more feasible problem using the duality transformation. A procedure for finding the realizable lower bound for the cost is also presented. A two-phase approach is proposed for solving the GSNCPP. We have carried out numerical computations for ten networks with different topologies and found that the cost of a GSN is only a fraction (from 39% to 97%) more than the average cost of a static survivable network. The framework is applicable to survivable network planning for ASTN/ASON, VPN, and IP networks as well as bandwidth-on-demand resource allocation.
25 citations
TL;DR: Design models for optimal capacity design of span-restorable mesh networks having any particular mixture of four basic “quality of protection” (QoP) classes are given and can be used by network and business planners to evaluate a number of different service structuring, pricing, and capacity-design strategies that may offer advantages to them and new options for their customers.
Abstract: In the modern business environment there is considerable interest in being able to support a range of different transport service classes in an optical network, and charge accordingly. In this work we consider the capacity design problem for a mesh-restorable optical network supporting any mixture of four basic “quality of protection” (QoP) classes. The service definitions are (gold): assured restorability, (silver): best efforts, (bronze): non-protected and (economy): preemptible service. We give design models for optimal capacity design of span-restorable (or corresponding link-protected) mesh networks having any particular mixture of these service classes. We also apply and test the design models under several multi-QoP test case scenarios to gain insights about various strategies and options possible in a multi-QoP design environment. An interesting finding is that in some test cases, 15 to 30% of all demand can be in the gold class enjoying 100% restorability solely through preemption of economy class service capacity. This suggests the potential to design and operate mesh-based networks that have no spare capacity at all in the conventional sense: all capacity is bearing service of some paying type. The resulting frequency of preemption in the economy class services is also studied. Results also show typically high levels of best-efforts restorability in the silver class occurring in networks that are strictly designed only for the restorability of the gold class services. High restorability of best effort services, however, requires the preemption of economy services. These methods and findings can be used by network and business planners to evaluate a number of different service structuring, pricing, and capacity-design strategies that may offer advantages to them and new options for their customers.
25 citations
Cites background from "Optimal capacity placement for path..."
...The same changes applies to other standard design models such as for non-joint spare capacity assignment (SCA [4]), jointly optimized working and spare capacity assignment (JCA [5]), or modular non-joint span restorable capacity (MSCA [6])....
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TL;DR: This investigation presents a strategy to construct a compact mathematical model of the path-restoration version of the spare capacity allocation problem that uses a node-arc formulation and combines constraints whenever multiple working paths affected by an edge failure have identical origins or destinations.
Abstract: This investigation presents a strategy to construct a compact mathematical model of the path-restoration version of the spare capacity allocation problem. The strategy uses a node-arc formulation and combines constraints whenever multiple working paths affected by an edge failure have identical origins or destinations. Another unique feature of this model is the inclusion of modularity restrictions corresponding to the discrete capacities of the equipment used in telecommunication networks.The new model can be solved using a classical branch-and-bound algorithm with a linear-programming relaxation. A preprocessing module is developed, which generates a set of cuts that strengthens this linear programming relaxation. The overhead associated with the cuts is offset by the improved bounds produced. A new branch-and-bound algorithm is developed that exploits the modularity restrictions. In an extensive empirical analysis, a software implementation of this algorithm was found to be substantially faster than CPLEX 6.5.3. For a test suite of 50 problems, each having 50 nodes and 200 demands from a uniform distribution with a small variance, our new software obtained solutions guaranteed to be within 4% of optimality in five minutes of CPU time on a DEC AlphaStation.
25 citations
Cites background or methods or result from "Optimal capacity placement for path..."
...Iraschko et al. (1998) solved several problems using an arc-path formulation....
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...Iraschko et al. (1998) present a study comparing their path-restoration formulation to their link-restoration formulation....
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...The work by Iraschko et al. (1998) differs from our investigation in several respects....
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...Iraschko et al. (1998) reported gains (decreases in total capacity) of 4% to 27% from joint optimization, but noted that the working capacity often already exists (such as when upgrading or adding to a network)....
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References
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Book•
16 Feb 1970
TL;DR: Interestingly, integer programming and network flows that you really wait for now is coming, it's significant to wait for the representative and beneficial books to read.
Abstract: (1970). Integer Programming and Network Flows. Journal of the Operational Research Society: Vol. 21, No. 4, pp. 500-501.
638 citations
TL;DR: Self-healing network techniques suitable for ATM networks in order to realize a high-reliablity B-ISDN are proposed and high-speed restoration technique which exploits the benefits of the VP is proposed and described.
Abstract: This paper proposes self-healing network techniques suitable for ATM networks in order to realize a high-reliablity B-ISDN. First, the characteristics of the virtual paths (VP) and their influence on failure restoration are discussed. A high-speed restoration technique which exploits the benefits of the VP is then proposed and described. The technique simplifies the message transmission processes and reduces the number of generated messages by using preassigned backup virtual paths. Next, the scheme used to design the backup VP routes and spare resource distribution for each link is proposed in order to create a network that applies the proposed restoration scheme. Next, self-reconstruction techniques of backup virtual paths are proposed for the realization of a reversionless restoration cycle. Finally, the feasibility of the distributed control operation is discussed. >
233 citations
TL;DR: A comparative study of the effectiveness of KSP versus Max Flow as an alternative rerouting criteria in the context of transport network span restoration, and the hypothesis is made that a generalized "trap" topology is responsible for all KSP-Max Flow capacity differences.
Abstract: In the development of technologies for span failure restoration, a question arises about the restoration rerouting characteristics to be specified. In theory, maximal rerouting capacity is obtained with a maximum flow (Max Flow) criterion. However, rerouting that realizes the k-successively shortest link disjoint paths (KSP) may be faster, easier, and, in distributed implementation, more robust than a distributed counterpart for Max Flow. The issue is, therefore, what the restoration capacity penalty is if KSP is used instead of Max Flow. To explore this tradeoff, the authors present a comparative study of the effectiveness of KSP versus Max Flow as an alternative rerouting criteria in the context of transport network span restoration. The comparison applies to both centrally controlled and distributed restoration systems. Study methods include exhaustive span failure experiments on a range of network models, and parametric and analytical investigations for insight into the factors resulting in KSP versus Max Flow differences. The main finding is that KSP restoration capacity is more than 99.9% of that from Max Flow in typical network models. The hypothesis is made that a generalized "trap" topology is responsible for all KSP-Max Flow capacity differences. The hypothesis is tested experimentally and used to develop analytical bounds which agree well with observed results. These findings and data are relevant to standards makers and equipment developers in specifying and engineering future restorable networks. >
199 citations
NEC1
TL;DR: In order to achieve fast restoration, a distributed control mechanism that is applicable to both line and path restoration is proposed, and the shared use of spare channels for various failure scenarios, including multiple failure cases, are allowed.
Abstract: With the advent of networking technologies intelligent network elements, such as the digital cross-connect system (DCS), will make it possible to dynamically reconfigure a network for restoration purposes. Both restoration control of DCSs and spare-channel design issues are presented, and how they work together so that a fast and economical SONET self-healing network is obtained. In order to achieve fast restoration, a distributed control mechanism that is applicable to both line and path restoration is proposed. The proposed method allows the shared use of spare channels for various failure scenarios, including multiple failure cases, so that the efficient use of spare channels can be achieved. A linear-programming-based scheme is proposed to obtain spare-channel assignment, where a network-flow technique is used. Through a simulation study, a fast and economical self-healing network is verified. >
193 citations
"Optimal capacity placement for path..." refers background or methods in this paper
...Previous work used an IP approach based on -flow -cut considerations to solve the spare capacity placement problem in a span-restorable network [4], [11], [20]....
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...Issues related to the restoration mechanisms themselves are addressed in related works [1], [2], [4], [21], [27]....
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Proceedings Article•
01 Jan 1987
180 citations