Preplanned restoration of multicast demands in optical networks☆
Introduction
Demand for multicast HD-TV and even higher resolutions grows rapidly, requiring increasingly more bandwidth. After a link failure the total of available network resources drops. Remaining ‘healthy’ links have to transmit also the traffic that was routed over the link that failed. In such cases, it is a key question how to save as many resources as possible. However, users would not accept high outage time – called mean down time (MDT) – of any service Ref. [1]. In case of multicast traffic the problem is even more important as not only one user, but a set of users may be affected by even a single link failure. Different kinds of protection methods (e.g.: 1 + 1 protection) offer very low MDT. However, the resources used by the back-up paths are reserved even if no link is down Ref. [2]. Heuristic restoration techniques – i.e. calculation of the new path ‘on the fly’ – may provide solution within affordable but not zero time. Nevertheless, these methods tend to produce solutions that may not be optimal in the sense of resource utilization, especially for multicast. As the MDT is a very important, exact method, such as ILP (integer linear programming), cannot be applied, due to their calculation complexity.
Preplanned restoration of unicast demands has been studied deeply. In Ref. [3] a stochastic approach is presented, in Ref. [4] a distributed, probabilistic solution is proposed. Methods for single – and multilayer restoration, and their comparison were given in Ref. [5].
Preplanned restoration of multicast demands has been studied for different networks and architectures – including application level multicasting (ALM) Ref. [6] – in different phases of the life of a demand – i.e. at creation, when it is modified, etc. – Refs. [7], [8], etc. These approaches are well known for their good properties – i.e. cost effectiveness, acceptable blocking ratio, etc. However, according to our knowledge, the preplanned restoration of a static multicast demand in multi-layer optical network has not been studied. In the following, we will investigate this question.
In core networks most of the multicast demands are static – e.g. virtual private networks, TV multicasts, etc. Their paths do not alter in time. Thus, it is possible to calculate restoration paths for all the plausible failure scenarios. However, it is not affordable to calculate the global optimal restoration paths for all demands at once. This restriction is the result of three circumstances:
- 1.
There is dynamic background traffic in the network. This traffic cannot be incorporated into the calculation of restoration plan.
- 2.
It is possible that the global optimum can only be achieved if existing and intact demands are rerouted. By interrupting and rerouting these demands the Quality of Service (QoS) drops. This is not permissible.
- 3.
Calculation of optimal paths for multiple unicast demands or a single multicast demand is NP-hard, Ref. [9]. This calculation is affordable only in special cases.
Our aim in this paper is to show how the problem of preplanned restoration of multicast demands can be simplified and solved in a way that it may give a good and valid solution in most cases, meanwhile its off-line and on-line calculation time is moderated.
The paper is organized as follows: Section 2 gives a basic overview of the topic. Formalization of the used environment is given in Section 3. Known solutions are summarized in Section 4. The details of the proposed method are given in Section 5, while our simulation results in Section 6. We conclude our work in Section 7.
Section snippets
Problem formalization and goal of the research
A two-layer network is assumed, where the upper, electronic layer is time switching capable, while the lower, optical one is wavelength (space) switching capable. The electronic layer is able to perform traffic grooming. The two layers are assumed to be interconnected.
Network topology, the number of fibers, and the description of the traffic are assumed given. The capacity of wavelength (WL) channels, and the cost of routing can also be given. We assume static traffic consisting of multicast
Formalization of wavelength graph transformation
In the followings we present a way how the transformation between the source graph and the WG can be formalized. Until now, according to our knowledge, this method has not been formalized in such details.
One may define the graph as follows: Definition 1 A directed graph is given with a tuple, G(N, a), where: N is the set of nodes, , is the edge function – edge exists between two nodes only if the assigned value is true.
As loops should not exist in optical networks, one may add the following
Known methods
In this section we will summarize the most important methods and approaches used to prepare for or respond to link failures. These methods can be divided into two big groups:
- 1.
Methods that have some kind of reserved back-up,
- 2.
Algorithms that try to react as fast and effectively as possible at the time when the failure happens without any back-up or a priory knowledge.
Proposed algorithm
In Section 4.1 the restoration path is calculated and reserved in advance, in Section 4.2 nothing is calculated beforehand. Some kind of a golden mean can be established between them. This would mean that the restoration path is calculated in advance for all possible failure cases but it is not reserved. This idea was investigated in case of unicast demands many times, see Section 1. The nearest proposition for such solution for multicast, according to our knowledge, was proposed for ALM in
Our simulation assumptions
During the simulations we supposed that we had a static multicast demand and background traffic of unicast demands. We also supposed that the distribution of the source and destination nodes of any demand are uniform, while the holding and the arrival times of the unicast demands are exponential. Unicast demands were routed by Dijkstra’s algorithm.
In see Section 4.3 the resource saving properties of the proposed method versus generic protection methods was shown if the restoration of the
Conclusion
We have proposed a new family of restoration methods, the restoration based on preplaning created in a restricted network with ‘x’ method (RBPx). With the use of our new formalization of wavelength graph transformation (WGT), we proved its optimality for a set of cost functions. We confirmed with simulations its superiority over simple restoration heuristic based on Dijkstra’s method if the edge cost function is dominated by the used bandwidth. We also showed that the RPBx can be 5–10 times
Péter Soproni received his M.Sc. degree in Computer Science from the Budapest University of Technology and Economics (BME), Hungary, in 2008. He is currently a Ph.D. student at the Department of Telecommunication and Media Informatics (TMIT) in the same institute. He has participated in several research projects supported by the EU and the Hungarian government including IP NOBEL II, BONE and TIGER2. His research interests include simulation, algorithmic optimization, optimization of routing,
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Cited by (1)
Multicast routing algorithms for sparse splitting optical networks
2016, Computer CommunicationsCitation Excerpt :For example, the work in [31] and in [32] investigates the problem of protecting multicast sessions in optical networks, taking into account physical layer impairments. In [33], a restoration method that provides relatively fast restoration of multicast demands is proposed, while in [34] the problem of sub-wavelength level protection for dynamic multicast traffic grooming is investigated, and a new technique is proposed that aims at minimizing the network resources allocated for the protection of the traffic requests. Recently, optimization algorithms were also proposed for multicast routing in elastic optical networks (EONs) [35–38].
Péter Soproni received his M.Sc. degree in Computer Science from the Budapest University of Technology and Economics (BME), Hungary, in 2008. He is currently a Ph.D. student at the Department of Telecommunication and Media Informatics (TMIT) in the same institute. He has participated in several research projects supported by the EU and the Hungarian government including IP NOBEL II, BONE and TIGER2. His research interests include simulation, algorithmic optimization, optimization of routing, traffic engineering and planning of optical networks, as well as soft-computing especially bacterial algorithms. He has experience in NET and Linux based software development.
Tibor Cinkler [M’95] ([email protected]) has received M.Sc. (’94) and Ph.D. (’99) degrees from the Budapest University of Technology and Economics (BME), Hungary, where he is currently associate professor at the Department of Telecommunications and Media Informatics (TMIT). His research interests focus on optimization of routing, traffic engineering, design, configuration, dimensioning and resilience of IP, Ethernet, MPLS, ngSDH, OTN and particularly of heterogeneous GMPLS-controlled WDM-based multilayer networks. He is author of over 180 refereed scientific publications and of 4 patents.
He has been involved in numerous related European and Hungarian projects including ACTS METON and DEMON; COST 266, 291, 293; IP NOBEL I and II and MUSE; NoE e-Photon/ONe, e-Photon/ONe+ and BONE; CELTIC PROMISE and TIGER2; NKFP, GVOP, ETIK; and he has been member of ONDM, DRCN, BroadNets, AccessNets, IEEE ICC and Globecom, EUNICE, CHINACOM, Networks, WynSys, ICTON, etc. Scientific and Programm Committees. He has been guest editor of a Feature Topic of the IEEE ComMag and reviewer for many journals. He has organized DRCN 2001, ONDM 2003 and Networks 2008 conferences in Budapest.
He teaches various courses on networking and optimization at the university, as well as for companies and also gives tutorials at conferences and summer and winter schools. He received numerous awards including: Dimitris Chorafas Prize for Engineeing, ICC best paper award, numerous HTE awards (HTE is the Hungarian IEEE sister society) (including Tivadar Puskás, Virág-Pollák 3 times, and the 60-year anniversary medal Bolyai Medal, etc.
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This paper has been supported by HSNLab, Budapest University of Technology and Economics, http://www.hsnlab.hu.