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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TL;DR: A self-healing algorithm for the problem of reliable multiparty computation, in which n parties want to jointly compute a function f over n inputs, that can reduce message cost by a factor of 432 when compared with algorithms that are not self- healing.
Abstract: In the problem of reliable multiparty computation (RMC), there are n parties, each with an individual input, and the parties want to jointly compute a function f over n inputs; note that it is not required to keep the inputs private. The problem is complicated by the fact that an omniscient adversary controls a hidden fraction of the parties. We describe a self-healing algorithm for this problem. In particular, for a fixed function f, with n parties and m gates, we describe how to perform RMC repeatedly as the inputs to f change. Our algorithm maintains the following properties, even when an adversary controls up to $$t \le (\frac{1}{4} - \epsilon ) n$$
parties, for any constant $$\epsilon >0$$
. First, our algorithm performs each reliable computation with the following amortized resource costs: $$O(m + n \log n)$$
messages, $$O(m + n \log n)$$
computational operations, and $$O(\ell )$$
latency, where $$\ell $$
is the depth of the circuit that computes f. Second, the expected total number of corruptions is $$O(t (\log ^*{m})^2)$$
, after which the adversarially controlled parties are effectively quarantined so that they cause no more corruptions. Empirical results show that our algorithm can reduce message cost by a factor of 432 when compared with algorithms that are not self-healing.
7 citations
09 Jul 2007
TL;DR: A randomized alternative for the optimization of hybrid systems' performance is explored by first presenting the general hybrid optimal control problem, and then converting it into an optimization problem within a statistical learning framework.
Abstract: In this paper we explore a randomized alternative for the optimization of hybrid systems' performance. The basic approach is to generate samples from the family of possible solutions, and to test them on the plant's model to evaluate their performance. This result is obtained by first presenting the general hybrid optimal control problem, and then converting it into an optimization problem within a statistical learning framework. The results are applied to examples already existing in the literature, in order to highlight certain operational aspects of the proposed methods.
7 citations
01 Jan 2001
TL;DR: The robust optimization model has been extended to provide either dedicated protection or shared protection against single link failures and cost reductions up to 35% were observed via the use of shared protection versus dedicated protection.
Abstract: In a previous investigation, we developed a robust optimization model for the wavelength division multiplexing routing and provisioning problem. The robust model incorporates a fixed budget and uses a piece-wise linear regret function to model over and under provisioning. In this investigation, the robust optimization model has been extended to provide either dedicated protection or shared protection against single link failures. Both models are mixed integer linear programs with a large number of continuous variables and only two integer variables per link. Each has been implemented using A Mathematical Programming Language (AMPL) and computational solvability has been demonstrated on a pair of test cases. Cost reductions up to 35% were observed via the use of shared protection versus dedicated protection. Acknowledgement This investigation was partially supported by grants from Nortel Networks and the Office of Naval Research under Award Number N00014-96-1-0315.
7 citations
AT&T1
TL;DR: A fast algorithm for restoration capacity planning with a proven performance ratio of at most 2+?
Abstract: Amajor task of telecommunication network planners is deciding where spare capacity is needed, and howmuch, so that interrupted traffic may be rerouted in the event of a failure. Planning the spare capacity so as to minimize cost is an NP-hard problem, and for large networks, even the linear relaxation is too large to be solved with existing methods. The main contribution of this paper is a fast algorithm for restoration capacity planning with a proven performance ratio of at most 2+?, and which generates solutions that are at most 1% away from optimal in empirical studies on a range of networks, with up to a few hundred nodes. As a preliminary step, we present the first (1 + ?)-approximation algorithm for restoration capacity planning. The algorithm could be practical for moderate-size networks. It requires the solution of a multicommodity-flow type linear program with O(m|G|) commodities, however, where G is the set of distinct traffic routes, and therefore O(m2|G|) variables. For many networks of practical interest, this results in programs too large to be handled with current linear programming technology. Our second result, therefore, has greater practical relevance: a (2+?)- approximation algorithm that requires only the solution of a linear program with O(m) commodities, and hence O(m2) variables. The linear program has been of manageable size for all practical telecommunications network instances that have arisen in the authors' applications, and we present an implementation of the algorithm and an experimental evaluation showing that it is within 1% of optimal on a range of networks arising practice.We also consider a more general problem in which both service and restoration routes are computed together. Both approximation algorithms extend to this case, with approximation ratios of 1 + ? and 4 + ?, respectively.
7 citations
Cites background from "Optimal capacity placement for path..."
...Ir a chko, MacGregor and Grover [9] report computational results for their integer programmin g heuristic, but give no estimate of the absolute quality of the solutions....
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...Herzberg, Bye and Utano [8] and Iraschko, MacGregor and Grover [9] give integer programmin g formulations for various restoration capacity planning problems, based on enumerating all p ossible restoration paths between demand endpoints....
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...Herzberg, Bye and Utano [8] and Iraschko, MacGregor and Grover [9] give integer programming formulations for various restoration capacity planning problems, based on enumerating all possible restoration paths between demand endpoints....
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...Ira chko, MacGregor and Grover [9] report computational results for their integer programming heuristic, but give no estimate of the absolute quality of the solutions....
[...]
TL;DR: A centralized method for optimally selecting the set of active and backup paths in an optical transport network in the cases of shared-path restoration and 1:1 protection schemes and novel mixed integer linear programming (MILP) formulations for both schemes.
Abstract: In this paper we provide a centralized method for optimally selecting the set of active and backup paths in an optical transport network in the cases of shared-path restoration and 1:1 protection schemes We provide novel mixed integer linear programming (MILP) formulations for both the schemes, for a network with full wavelength conversion capability The given formulations are not restricted to consider single link failures: the concept of fault event is introduced to handle the possibility that multiple links go simultaneously under fault The optimization objective includes the total capacity requirement plus an additional term related to the active paths reliability We use a simple decomposition heuristic to support the resolution process The optimization is solved for various sample scenarios in order to evaluate the resource saving achieved with the shared-path restoration scheme The impact of different factors such as topology, traffic demand and structure of failures on the resource saving is analyzed Also, we provide guidelines about handling differentiated levels of protection within the framework of the proposed formulations
7 citations
Cites background from "Optimal capacity placement for path..."
...MILP approachestòòff-line'' protection/restoration problems were proposed in Herzberg and Bye [14], Wayne et al. [15] and Doshi et al. [16] (the last two works in particular used the concept of fault event in their formulations)....
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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