QLB: QoS routing algorithm for Software-Defined Networking

Streaming media transmission requires strict quality of service (QoS) parameters such as maximum delay and delay jitter. An effective streaming media routing algorithm is a key factor in ensuring QoS. The existing solution only considers a single parameter indicator in the performance parameters such as bandwidth, delay, and utilization of the link, and fails to comprehensively measure the data flow in the network. It is not possible to comprehensively measure the relationship between the business attributes and the QoS parameters. Firstly, the deterministic upper bounds of QoS parameters in streaming media networks are solved by using network calculus theory, and the QoS parameters are normalized, and a multi-constrained QoS resource allocation model is established; the separation of control and forwarding planes is defined by using software-defined networking (SDN) to deploy the multi-constrained QoS resource allocation model in the control plane; the QoS routing system of streaming media network based on the SDN is designed and implemented, including flow table scheduling model, routing function, measurement and forwarding modules. In the routing function module of the SDN controller, a multi-constrained QoS routing algorithm based on network calculus is implemented. Experimental results show that the proposed multi-constrained QoS resource allocation model based on network calculus and the multi-constrained centralized QoS routing algorithm based on the SDN have good performance.

Localised quality of service (QoS) routing has recently been proposed as a viable alternative approach to traditional QoS routing algorithms that use global state information. In this approach, problems associated with maintaining global state information are avoided by having the source nodes to infer the network QoS state based on flow blocking statistics collected locally, and perform flow routing using this localised view of the network QoS state. A credit based routing algorithm (CBR) which is a simple yet effective localised QoS routing algorithm is introduced. Its performance is compared against the localised proportional sticky routing (PSR) algorithm using different types of network topologies, QoS requirements and traffic patterns and under a wide range of traffic loads. Extensive simulations show that the algorithm outperforms the PSR scheme while maintaining the same level of adaptivity and stability. Its performance is also compared against the global widest-shortest path algorithm (WSP) and it is shown that CBR gives a comparable performance with better time complexity and very low communication overhead.

The scheme of Quality of Service (QoS) routing algorithms based on local state information has recently been proposed as an alternative approach to the traditional QoS routing algorithms. By implementing this localized QoS routing algorithm, each source node predetermines and maintains a set of candidate paths for each destination. These sets of paths will help the source node to decide the most appropriate path for a connection request. Hence, it helps to avoid the problems associated with the maintenance of the global network state information. In this paper, we propose a new and effective localized QoS routing algorithm, compare its performance with those of other localized algorithms and a traditional QoS routing algorithm under the same type of network topology, QoS requirements and traffic patterns. The simulations results show that our proposed algorithm can perform better than other routing algorithms. DOI: 10.32913/rd-ict.vol3.no14.258

A lot of work has been done on routing in MANETs. However, the proposed routing solutions deal only with the best effort data traffic. Connections with quality of service (QoS) requirements are not supported. The QoS routing has been receiving increasingly intensive attention in the wireline network domain. However, for MANETs are proposed only few QoS routing algorithms. For MANETs, approximated solutions and heuristic algorithms should be developed and QoS routing algorithms should be adaptive, flexible, and intelligent. In our previous work, we proposed a genetic algorithm (GA) based routing method for mobile ad-hoc networks (GAMAN). In this paper, we enhance the proposed algorithm by adding an effective topology extraction algorithm to reduce the search space of GAMAN. We call this algorithm E-GAMAN. The E-GAMAN uses two QoS parameters for routing. The performance evaluation via simulations shows that E-GAMAN has a good performance.

Design and performance analysis of an inductive QoS routing algorithm

Implementing the dynamic couple of searching paths and resource allocation becomes increasingly important in the research of Quality of Service (QoS) routing. In this paper, we formulate the problem of dynamic QoS routing with resource allocation based on Worst-case Fair Weighted Fair Queuing (WF2Q) packet scheduling style. We propose an algorithm using the proved results -- the optimal path resource allocation algorithm (OPRA2), which can allow intelligent choice of the maximized reliability and minimized delay path according to the types of applications and adapt QoS parameters and allocated resources related to WF2Q in process of routing. It can find an optimal path which satisfies different QoS requirements and compute the amount of bandwidth and buffer resources needed at each node. We provide the simulation results to illustrate the effect of buffers and bandwidths according to the values of control parameters.

With the Development of mobile ad hoc network (MANET), Quality of Service (QoS) routing and power-aware routing become more and more important. In the past, QoS guarantee and power control issues were treated separately. In this paper, we propose a novel on-demand QoS routing protocol, PMQR (power-aware multi-path QoS routing) in TDMA-based MANETs. Our protocol combines QoS routing and power-aware routing, which can provide QoS guarantee and achieve energy conservation by taking into account both the transmission power and the remaining energy at the intermediate nodes between a source and a destination. PMQR also can establish multiple paths, even for a single call, when the route search cannot find a path that meets the QoS requirements. Simulation results show that PMQR has good network performance and balances the energy consumption of mobile hosts.

In Mobile Ad-Hoc Networks (MANET), the increasing demand for multimedia application is more challenging and the existing routing protocols are not adequate owing to the complex design requirements of Quality of Service (QoS) routing. This paper proposes a stateless position-based solution for QoS routing issues and offers an efficient end-to-end communication guarantee. The proposed Stateless QoS (SQoS) routing protocol is based on adaptive compass greedy routing to determine a qualified path which satisfies the QoS requirements and the void handling scheme overcomes the local maximum issue. In addition, the SQoS routing utilises the node overhearing capacity to obtain the link quality measurement to provide a guarantee for efficient end-to-end transmission through the identification of high-quality links for multimedia streams. The performance of the proposed SQoS routing protocol is compared with existing QoS-GPSR. Finally, the performance evaluation proves that the SQoS routing protocols outperform the existing protocols.

Protocols responsible for quality of service (QoS) routing are characterized by limited scalability and considerable complexity and traffic overhead. QoS routing implies resource reservation to support the application requirements. The QoS routing and resource reservation require the implementation of a signaling mechanism. Performing QoS routing and resource reservation at different network layers will cause redundant signaling. In this paper we propose a simple extension to the reservation protocol RSVP signaling mechanism that supports the simultaneous implementation of QoS probing routing and resource reservation. The extended RSVP uses only the IP protocol and eliminates the need of additional signaling mechanism in the network layer. We formalize and verify the signaling mechanism using color Petri net. A network simulator is constructed using the same tool to measure the performance of the proposed extended RSVP.

Nowadays, more and more researchers are paying their attention to green routing. In this paper, we consider power consumption as a kind of QoS (quality of service) and apply a new learning-based approach for energy efficient transportation and QoS routing. Compared with traditional rule-based methods, the proposed method can learn additional information from the networks to improve routing performance, and have the flexibility to meet different QoS requirements. First, we propose a new identification of network nodes, namely node vectors, and a basic routing algorithm using node vectors is designed accordingly. Then, energy efficient transportation and QoS routing are proposed by adding QoS constraints into the routing decision. Link attributes such as power consumption, bandwidth and delay can be learned from these node vectors with neural networks. The learned link attributes together with the estimated distance can be used for routing decisions with QoS constraints. Simulation results show that the proposed method is reliable in routing tasks, and can achieve a remarkable performance when compared with the state-of-the-art work on the delay constrained least cost path (DCLC) problem.

We consider the problem of quality of service (QoS) routing in multi-hop wireless networks where data are transmitted from a source node to a destination node via multiple hops. The routing component of a QoS-routing algorithm essentially involves the link and path metric calculation which depends on many factors such as the physical and link layer designs of the underlying wireless network, transmission errors due to channel fading and interference, etc. The task of link metric calculation basically requires us to solve a tandem queueing problem which is the focus of this paper. We present a unified tandem queue framework which is applicable for many different physical layer designs. We present both exact and approximated decomposition approaches. Using the queueing framework, we can derive different performance measures, namely, end-to-end loss rate, end-to-end average delay, and end-to-end delay distribution. The proposed decomposition approach is validated and some interesting insights into the system performance are highlighted. We then present how to use the decomposition queueing approach to calculate the link metric and incorporate this into the route discovery process of the QoS routing algorithm. The extension of the queueing and QoS routing framework to wireless networks with class-based queueing for QoS differentiation is also presented.

Multicast routing is an effective way to communicate among multiple hosts in a network. For multimedia applications, the routing algorithms should consider many Quality of Service (QoS) parameters such as delay, cost and so on to find a new route. However, to find routes with two or more QoS parameters is an NP-hard problem. This paper describes a new evolutionary scheme for optimization of multicast QoS routing based on the hybrid of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), called HGAPSO. In HGAPSO, individuals in a new generation are created, not only by crossover and mutation operation as in GA, but also by PSO. The upper-half of the best-performing individuals in a population are regarded as elites. Instead of being reproduced directly to the next generation, these elites are first enhanced. The group constituted by the elites is regarded as a swarm, and each elite corresponds to a particle within it. In this regard, the elites are enhanced by PSO, an operation which mimics the maturing phenomenon in nature. This scheme can simultaneously optimize the cost of the tree, the maximum end-to-end delay, the average delay and the maximum link utilization. In this way, a set of optimal solutions, known as Pareto set, is calculated in only one run, without a priori restrictions. It has revealed an efficient method of the reconstruction of multicast tree topology and the experimental results demonstrated better performance than the conventional GA optimization method.

Mobile ad Hoc Networks (MANETs) are one of the most important technologies supporting Ubiquitous and Pervasive Computing (UPC). As many UPC applications pose Quality of Service (QoS) constraints, their implementation in MANETs becomes dependent on the MANET algorithms for QoS routing. In this paper Genetic Algorithms (GAs) for QoS routing in MANETs are considered. GAs can solve the NP search of QoS routes with multiple constraints, and then address the UPC QoS requirements. The focus is on tree-based GAs, which represent the set of paths from source to destination as a tree and encode them through the crossed junctions. They encode single paths in the chromosome. We investigate on the effects of binary encoding schema on tree-based GAs. To this purpose we design a GA with binary encoding that maps classes of paths in single chromosomes. These classes are both collectively exhaustive and mutually exclusive. The GA with binary encoding uses an adaptive mutation probability for deeper exploration of the search space, and local search on classes of paths. Simulation results compare the GA with binary encoding with two applications of GAMAN, the main existing tree-based GA. They show that the binary encoding allows the GA to converge faster although it introduces additional computational costs.

Recent studies provide evidence that Quality of Service (QoS) routing can provide increased network utilization compared to routing that is not sensitive to QoS requirements of traffic. However, there are still strong concerns about the increased cost of QoS routing, both in terms of more complex and frequent computations and increased routing protocol overhead. The main goals of this paper are to study these two cost components, and propose solutions that achieve good routing performance with reduced processing cost. First, we identify the parameters that determine the protocol traffic overhead, namely (a) policy for triggering updates, (b) sensitivity of this policy, and (c) clamp down timers that limit the rate of updates. Using simulation, we study the relative significance of these factors and investigate the relationship between routing performance and the amount of update traffic. In addition, we explore a range of design options to reduce the processing cost of QoS routing algorithms, and study their effect on routing performance. Based on the conclusions of these studies, we develop extensions to the basic QoS routing, that can achieve good routing performance with limited update generation rates. The paper also addresses the impact on the results of a number of secondary factors such as topology, high level admission control, and characteristics of network traffic.

QoS routing in GMPLS-capable integrated IP/WDM networks with router cost constraints