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.
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10 Aug 2009
TL;DR: The Forgiving Graph improves on the Forgiving Tree distributed data structure from [8] in the following ways: it ensures low stretch over all pairs of nodes, while the Forgging Tree only ensures low diameter increase.
Abstract: We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that, over a sequence of rounds, an adversary either inserts a node with arbitrary connections or deletes an arbitrary node from the network. The network responds to each such change by quick "repairs," which consist of adding or deleting a small number of edges.These repairs essentially preserve closeness of nodes after adversarial deletions, without increasing node degrees by too much, in the following sense. At any point in the algorithm, nodes v and w whose distance would have been l in the graph formed by considering only the adversarial insertions (not the adversarial deletions), will be at distance at most l log n in the actual graph, where n is the total number of vertices seen so far. Similarly, at any point, a node v whose degree would have been d in the graph with adversarial insertions only, will have degree at most 3d in the actual graph. Our distributed data structure, which we call the Forgiving Graph, has low latency and bandwidth requirements. The Forgiving Graph improves on the Forgiving Tree distributed data structure from [8] in the following ways: 1) it ensures low stretch over all pairs of nodes, while the Forgiving Tree only ensures low diameter increase; 2) it handles both node insertions and deletions, while the Forgiving Tree only handles deletions; 3) it does not require an initialization phase, while the Forgiving Tree initially requires construction of a spanning tree of the network.
42 citations
Cites background from "Optimal capacity placement for path..."
...There have been numerous papers that discuss strategies for adding additional capacity or rerouting in anticipation of failures [2,5,6,12,18,21,23]....
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TL;DR: This manuscript presents an introduction to the basic mathematical programming models for capacity allocation that have been proposed for mesh-based survivable networks.
Abstract: Designing a low cost, survivable, telecommunication network is an extremely complicated process. Most commercial products available to help with this process are based on simulation and/or proprietary heuristics. However, there is a growing consensus that mathematical programming belongs in the designer's “toolkit.” Easy-to-use modeling languages coupled with powerful optimization solvers have greatly reduced the burden of implementation of mathematical programming theory into the practice of commercial network design. This manuscript presents an introduction to the basic mathematical programming models for capacity allocation that have been proposed for mesh-based survivable networks.
42 citations
Cites background from "Optimal capacity placement for path..."
...[33,34] found that path restoration with stub release yielded a 19% capacity reduction over link restoration....
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TL;DR: It is shown that load balancing of the traffic across the disjoint paths can reduce the required backup capacity significantly significantly, and the SPM outperforms simple Open Shortest Path First (OSPF) rerouting by far.
Abstract: In this paper we propose the concept of an end-to-end (e2e) Self-Protecting Multi-Path (SPM) as a protection switching mechanism that may be implemented, eg, in Multiprotocol Label Switching (MPLS) networks In case of local outages, resilient networks redirect the traffic from a failed link over an e2e backup path to its destination In this case, Quality of Service (QoS) can only be provided if sufficient extra capacity is available If backup capacity can be shared among different backup paths, multi-path routing allows for considerable savings regarding this extra capacity The SPM consists of disjoint paths that carry the traffic both in normal operation mode and during local outages If a partial path is affected by a network failure, the traffic is just distributed to the remaining working paths This structure is easy to configure and the switching to failure mode operation is simple since no signalling is required Based on analytical results, we show that load balancing of the traffic across the disjoint paths can reduce the required backup capacity significantly The backup performance depends strongly on the network topology, and the SPM outperforms simple Open Shortest Path First (OSPF) rerouting by far
42 citations
Cites background from "Optimal capacity placement for path..."
...The results of [14] can be well implemented since this work applies only single-paths for both primary and backup paths and relocates only affected primary paths....
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19 Oct 2003
TL;DR: The results show that backup-multiplexing improves the utilization of channels but requires significant computing capacity under a fixed computing capacity budget, and is useful in cases where there is little time disjointness among SLDs.
Abstract: 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.
40 citations
27 Dec 2005
TL;DR: A new ILP model and a related heuristic method for FIPP p-cycle design that produces network designs with much faster runtimes are developed and results indicate that the heuristic generates FIPPp-cycle designs that have total capacity costs within 10-18% of optimally designed SBPP solutions.
Abstract: Recent work has proposed the concept of failure-independent path-protecting (FIPP) p-cycles as a pre-connected, failure independent, path-protecting network architecture [A Kodian, W D Grover (2005)] FIPP p-cycles extend p-cycles by adding the property, like shared backup path protection (SBPP), of providing end-to-end failure independent path switching against either span or node failures Especially in a transparent or translucent optical network, the property of pre-cross-connection of protection paths can be even more important than just increasing restoration-speed: when optical protection paths are pre-cross-connected, they can be guaranteed in advance to work when required FIPP p-cycles therefore offer a fully pre-connected, alternative to SBPP in which protection paths must be assembled on the fly from spare wavelength channels Design results from small networks in [A Kodian, W D Grover (2005)] showed that FIPP p-cycle designs can be as efficient as SBPP but it is very difficult to design larger networks using the ILP design model in [A Kodian, W D Grover (2005)] We now develop a new ILP model and a related heuristic method for FIPP p-cycle design that produces network designs with much faster runtimes Results indicate that the heuristic generates FIPP p-cycle designs that have total capacity costs within 10-18% of optimally designed SBPP solutions
40 citations
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