Class-Based Constraint-Based Routing with Implemented Fuzzy Logic in MPLS-TE Networks

Hindawi Publishing Corporation Journal of Computer Networks and Communications Volume 2014, Article ID 237810, 7 pages http://dx.doi.org/10.1155/2014/237810 Research Article Class-Based Constraint-Based Routing with Implemented Fuzzy Logic in MPLS-TE Networks Michal Pištek and Martin Medvecký Institute of Telecommunications, Faculty of Electrical Engineering and Information Technology, Slovak University of Technology in Bratislava, Ilkovičova 3, 812 19 Bratislava, Slovakia Correspondence should be addressed to Michal Pištek; Received 30 May 2014; Revised 14 November 2014; Accepted 5 December 2014; Published 18 December 2014 Academic Editor: Eduardo da Silva Copyright © 2014 M. Pištek and M. Medvecký. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The paper deals with constraint-based routing (CBR) in MPLS-TE networks and proposes a new CBR algorithm based on fuzzy logic called Fuzzy Class-Based Algorithm (FCBA). Multiprotocol label switching with traffic engineering (MPLS-TE) networks represent a popular mechanism to effectively use resources of service providers’ core networks. The paths can be either built by administrators (explicit routing) or built by using existing routing algorithms which mostly decide based on the shortest paths towards the destination which might not be sufficient in nowadays’ multimedia networks. To address this problem various CBR algorithms have emerged which take into consideration various aspects important to existing traffic like QoS parameters or administrative policies. FCBA makes routing decisions based on traffic classes and by using fuzzy logic we can assign normalized values to various constraints based on the traffic class’ preferences (e.g., low delay paths for voice traffic) and network administrator’s preferences (e.g., avoiding congested links). The paper provides comparison of FCBA with existing CBR approaches based on their ability to provide QoS parameters loss. The simulations show that FCBA provides the best results for the highest priority traffic where it uses lower priority traffic to efficiently utilize the network. 1. Introduction Nowadays the modern telecommunication networks should be able to transfer very varied multimedia traffic resulting in a fully converged network. Transferring data, voice, and video traffic in one network requires effective mechanisms which take the various traffics’ requirements in consideration [1]. Such requirements are in a form of quality of service (QoS) parameters. The proposed QoS mechanism should try to meet the desired delay, jitter, or loss values desired by the traffic flows [2]. Recently MPLS-TE networks have been widely implemented in the core networks of telecommunication operators. MPLS-TE provides connection-oriented approach in IP networks. It creates end-to-end paths (LSPs) where it can guarantee bandwidth and with traffic engineering it can truly optimize the network’s resources. It enables using explicit routes which might not be ideal according to the routing algorithms but they enable using network’s resources more efficiently. Otherwise MPLS-TE relies on the routing algorithms to build the LSPs. The routing algorithms play an important role in terms of QoS ensuring and optimal resource allocation from the network’s point of view. Routing based on the destination address using minimal hop count as the decision criteria is not sufficient anymore. Administrative policies, performance requirements, load balancing, and scalability are thus becoming increasingly significant factors in the routing decisions. Constraint-based routing (CBR) uses such parameters to make the routing decisions. Many CBR algorithms were proposed which in most cases do not take into consideration various aspects important to various traffic types so we propose a class-based algorithm which ensures that delay-intolerant higher priority classes are treated differently from delay-tolerant lower priority classes. The algorithm uses multiple constraints to make the routing decision. The decision is based on fuzzy logic which allows the algorithm to take all the constraints into consideration 2 Journal of Computer Networks and Communications using their normalized (fuzzificated) values by predefined membership functions which provide conversion between real and fuzzy values. We use additional class-based metric weights to differentiate how much impact the particular constraint has on the particular traffic priority to make sure that the high priority classes are treated as best as possible whereas the lower priority classes use higher weights for the metrics improving the overall network utilization. The paper is divided as follows. In the following chapter we provide a brief survey of CBR and fuzzy logic. The existing CRB algorithms are represented in Section 3. In Section 4 we propose the new CBR algorithm called Fuzzy Class-Based Algorithm. Section 5 presents our simulation model and the simulation results are discussed in Section 6 where we focus on the differences in routing decisions of the proposed and compared CBR algorithms. We conclude the paper in Section 7. For example, bandwidth of the path 𝐵path can be represented as 2. Background 2.1. Constraint-Based Routing. Constraint-based routing (CBR) represents a class of routing algorithms that base path selection decisions on a set of requirements or constraints, in addition to the destination. These constraints may be imposed by administrative policies, or by QoS requirements. Constraints imposed by policies are referred to as policy constraints, and the associated routing is referred to as policy routing (or policy-based routing). Constraints imposed by QoS requirements, such as bandwidth, delay, or loss, are referred to as QoS constraints, and the associated routing is referred to as QoS routing [3]. QoS constraints are represented in the form of metrics. One metric for each constraint is to be specified like bandwidth metric, jitter (variation in delay) metric, delay metric, number of hops metric, packet loss ratio, and so forth for one node to all other nodes in the network. Metric for a complete path with respect to each parameter is determined by the composition rules of metrics. The metrics might have the following character. (i) Additive Metric. The value of that constraint for a path is the addition of all links constituting path (delay, hop count, cost, and jitter). For example, overall delay of the path 𝐷path is represented as a sum of the partial delay values of the links forming the path 𝐷path = ∑ 𝑑link . (1) (ii) Multiplicative Metric. Using this metric, the value for the complete path is multiplication of all its edges (reliability, loss ratio). For example, the overall reliability of the path 𝑅path is represented as 𝑅path = ∏ 𝑟link . (2) (iii) Con (...truncated)