QoS Routing Problem Research Articles

Artificial Intelligence Empowered QoS-Oriented Network Association for Next-Generation Mobile Networks

The increasing complexity and dynamics of 5G mobile networks have brought revolutionary changes in its modeling and control, where efficient routing and resource allocation strategies become beneficial. Software-Defined Network (SDN) makes it possible to achieve the automatic management of network resources. Relying on the powerful decision-making capability of SDNs, network association can be flexibly implemented for adapting to the dynamic of the real-time network status. In this paper, we first construct a jitter graph-based network model as well as a Poisson process-based traffic model in the context of 5G mobile networks. Second, we solve the problem of QoS routing with resource allocation based on queueing theory using a low computational complexity greedy algorithm, which takes finding a feasible path set as the main task and resource allocation as the auxiliary task. Finally, we design a QoS-oriented adaptive routing scheme based on Deep Reinforcement Learning (DRL) SPACE, which is a DRL architecture with parameterized action space, in order to find an optimal path from the source to the destination. To validate the feasibility of the greedy QoS routing strategy with resource allocation, we make a numerical packet-level simulation to model a M/M/C/N queuing system. Moreover, extensive simulation results demonstrate that our proposed routing strategy is able to improve the traffic’s QoS metrics, such as the packet loss ratio and queueing delay.

Quantum Max-min Ant Colony Algorithm For QoS Routing Problem

Aiming at the ant colony algorithm is weak to solve the problem of QoS routing, this paper proposes a routing algorithm that combines quantum computing with the max-min ant colony algorithm. The algorithm introduces a quantum selection strategy, uses qubit probability amplitude to encode the path, and dynamically adjusts the quantum rotation gate to update the path quantum coding on the basis of the minimum cost to meet the constraints and other optimal conditions, combined with the maximum and minimum pheromone determination mechanism to find the optimal path, effectively control the evolution speed and direction, and accelerate the algorithm convergence. Experimental results show that the algorithm is effective in controlling the speed and direction of evolution, and has better optimization ability and convergence performance than ant colony algorithm.

Optimal relay and channel selection schemes for multiconstrained QoS multicast routing in cognitive radio ad hoc networks

SummaryDuring multicasting in cognitive radio ad hoc network (CRAHN), apart from energy consumption, interchannel interference, path delay, and channel switching delay should be minimized. The channel selection should be done, based on spectrum opportunities and channel quality. Hence, the multicast routing problem becomes a multiconstrained QoS routing problem. This paper proposes optimal relay and channel selection schemes (ORCS) for multiconstrained QoS multicast routing in CRAHNs. For multicast tree construction, distributed minimum spanning tree (DMST) is used. For meeting the delay, energy, and interference constraints, relay nodes are chosen with minimum path delay, less energy consumption, and minimum interference. For effective channel assignment, channels with good channel quality, maximum spectrum accessibility, and sufficient common slots are selected. By simulation results, it has been shown that the proposed ORCS minimize the energy consumption and end‐to‐end delay.

Application of an improved Physarum polycephalum algorithm on QoS routing problem

Application of an improved Physarum polycephalum algorithm on QoS routing problem

Application of an improved Physarum polycephalum algorithm on QoS routing problem

Application of an improved Physarum polycephalum algorithm on QoS routing problem

Investigation of an improved tensor routing model in the telecommunications network represented in the basis of interpolar paths and internal node pairs

An improved tensor model of a telecommunication network (TCN) was selected for the study. The model is presented in terms of inter-polar paths and internal node pairs. The advantage of this model is the use of quality of service conditions in terms of bandwidth, average end-to-end delay, and packet loss probability. Within the framework of the chosen model, the technological routing problem is formulated in an optimization form together with the conditions and constraints imposed on routing variables. A system of criteria for optimality of routing solutions, which can be used to calculate optimal values for routing variables, is proposed. These criteria depending on the specifics of the routing problem focus on the optimal use of the available network resource and/or on the differentiated improvement of Quality of Service (QoS) indicators of network performance, to the numerical values of which one or another packet flow is sensitive. The analysis of the influence to the optimality criterion form on the nature of solutions to QoS-routing problems using the proposed tensor model of a telecommunications network is carried out. On a set of numerical examples, the improved tensor model of TCN both at the level of the proposed QoS-conditions and the considered QoS-optimality criteria confirmed its adequacy in solving the problems of a single path and multipath routing. The improved tensor model of TCN provided an adaptive response to changes in network load and the type of optimality criterion for routing solutions in terms of ensuring the required values of QoS-indicators – bandwidth, average end-to-end delay, and packet loss probability.

A genetic algorithm for the fuzzy shortest path problem in a fuzzy network

The shortest path problem (SPP) is an optimization problem of determining a path between specified source vertex s and destination vertex t in a fuzzy network. Fuzzy logic can handle the uncertainties, associated with the information of any real life problem, where conventional mathematical models may fail to reveal proper result. In classical SPP, real numbers are used to represent the arc length of the network. However, the uncertainties related with the linguistic description of arc length in SPP are not properly represented by real number. We need to address two main matters in SPP with fuzzy arc lengths. The first matter is how to calculate the path length using fuzzy addition operation and the second matter is how to compare the two different path lengths denoted by fuzzy parameter. We use the graded mean integration technique of triangular fuzzy numbers to solve this two problems. A common heuristic algorithm to solve the SPP is the genetic algorithm. In this manuscript, we have introduced an algorithmic method based on genetic algorithm for determining the shortest path between a source vertex s and destination vertex t in a fuzzy graph with fuzzy arc lengths in SPP. A new crossover and mutation is introduced to solve this SPP. We also describe the QoS routing problem in a wireless ad hoc network.

Power Line Communications Networking Method Based on Hybrid Ant Colony and Genetic Algorithm

When solving the routing problem with traditional ant colony algorithm, there is scarce in initialize pheromone and a slow convergence and stagnation for the complex network topology and the time-varying characteristics of channel in power line carrier communication of low voltage distribution grid. The algorithm is easy to fall into premature and local optimization. Proposed an automatic network algorithm based on improved transmission delay and the load factor as the evaluation factors. With the requirements of QoS, a logical topology of power line communication network is established. By the experiment of MATLAB simulation, verify that the improved Dynamic hybrid ant colony genetic algorithm (DH_ACGA) algorithm has improved the communication performance, which solved the QoS routing problems of power communication to some extent.

Efficient QoS Routing in Manet using Quantum

In mobile ad hoc networks, there is always a requirement of transferring real time multimedia information between a source-destination pair through a communication network. To support these communications and emergence of real-time applications, the basic requirement is to determine a feasible path which can join the source node and the destination node with a minimal cost .The paths are subjected to some constraints such as bandwidth, end-to-end delay, jitter and hop count. So, in order to assure an efficient performance, these QoS routing constraints must be properly handled. Therefore, complication of the problem is considered and accessible solution is provided using meta-heuristic algorithm rather than any other methods. To resolve the multi-constrained QoS routing problem in Mobile Ad-hoc Networks (MANETs), an intelligent algorithm has been proposed here to find the feasible path. This paper proposes a QPSO algorithm for solving multimedia routing which is capable of finding the low-cost route with bandwidth, delay and hop count as the constraints. In the proposed algorithm, the feasible path from the source node to the destination node is selected for communication which satisfies the minimum required bandwidth, less end-to-end delay and minimum hop count. The simulation results illustrate that the proposed QPSO algorithm with a novel node selection technique is able to find a better optimal path with multiple QoS constrains such as Bandwidth, hop count and network delay (end-to-end delay). It can meet the real-time requirements in multimedia communication networks.

Improved Ant Colony Algorithm and Its Application on the QoS Routing Problem

Quality of service is particularly important for data transmission in computer network. In order to improve the stability of the network and reduce network consumption, an improved ant colony algorithm has been proposed in this paper for solving QoS routing problem. The new state transition strategy and new pheromone updating strategy have been brought into ACA-QoS so as to avoid to easily fall to local optimal solutions and increase the convergence speed. Experiment results shows ACA-QoS has higher efficiency for finding the optimal paths in QoS routing problem and higher practical value.

A New QoS Routing Northbound Interface for SDN

In this paper, we introduce SCOR (Software-defined Constrained Optimal Routing), a new Software Defined Networking (SDN) Northbound Interface for QoS routing and traffic engineering. SCOR is based on constraint-programming techniques and is implemented in the MiniZinc modelling language. It provides a powerful, high-level abstraction layer, consisting of 10 basic constraint-programming predicates. A key feature of SCOR is that it is declarative, where only the constraints and utility function of the routing problem need to be expressed, and the complexity of solving the problem is hidden from the user, and handled by a powerful generic solver. We show that the interface (set of predicates) of SCOR is sufficiently expressive to handle all the known and relevant QoS routing problems. We further demonstrate the practicality and scalability of the approach via a number of example scenarios, with varying network topologies, network sizes and number of flows.

A New QoS Routing Northbound Interface for SDN

In this paper, we introduce SCOR (Software-defined Constrained Optimal Routing), a new Software Defined Networking (SDN) Northbound Interface for QoS routing and traffic engineering. SCOR is based on constraint-programming techniques and is implemented in the MiniZinc modelling language. It provides a powerful, high-level abstraction layer, consisting of 10 basic constraint-programming predicates. A key feature of SCOR is that it is declarative, where only the constraints and utility function of the routing problem need to be expressed, and the complexity of solving the problem is hidden from the user, and handled by a powerful generic solver. We show that the interface (set of predicates) of SCOR is sufficiently expressive to handle all the known and relevant QoS routing problems. We further demonstrate the practicality and scalability of the approach via a number of example scenarios, with varying network topologies, network sizes and number of flows.

A New Cross-Layer QoS-Provisioning Architecture in Wireless Multimedia Sensor Networks

Emerging applications in automation, medical imaging, traffic monitoring and surveillance need real-time data transmission over Wireless Sensor Networks (WSNs). Guaranteeing Quality of Service (QoS) for real-time traffic over WSNs creates new challenges. Rapid penetration of smart devices, standardization of Machine Type Communications (MTC) in next generation 5G wireless networks have added new dimensions in these challenges. In order to satisfy such precise QoS constraints, in this paper, we propose a new cross-layer QoS-provisioning strategy in Wireless Multimedia Sensor Networks (WMSNs). The network layer performs statistical estimation of sensory QoS parameters. Identifying QoS-routing problem with multiple objectives as NP-complete, it discovers near-optimal QoS-routes by using evolutionary genetic algorithms. Subsequently, the Medium Access Control (MAC) layer classifies the packets, automatically adapts the contention window, based on QoS requirements and transmits the data by using routing information obtained by the network layer. Performance analysis is carried out to get an estimate of the overall system. Through the simulation results, it is manifested that the proposed strategy is able to achieve better throughput and significant lower delay, at the expense of negligible energy consumption, in comparison to existing WMSN QoS protocols.

QoS Routing Under Multiple Additive Constraints: A Generalization of the LARAC Algorithm

Consider a directed graph $G(V, E)$ , where $V$ is the set of nodes and $E$ is the set of links in $G$ . Each link $(u, v)$ is associated with a set of $k+ 1$ additive nonnegative integer weights $C_{uv} = (c_{uv}, w^{1}_{uv}, w^{2}_{uv},\ldots , w^{k}_{uv})$ . Here, $c_{uv}$ is called the cost of link $(u, v)$ and $w^{i}_{uv}$ is called the $i$ th delay of $(u, v)$ . Given any two distinguish nodes $s$ and $t$ , the QoS routing (QSR) problem QSR( $k$ ) is to determine a minimum cost $s-t$ path such that the $i^{\rm th}$ delay on the path is atmost a specified bound. This problem is NP-complete. The LARAC algorithm based on a relaxation of the problem is a very efficient approximation algorithm for QSR (1) . In this paper, we present a generalization of the LARAC algorithm called GEN-LARAC. A detailed convergence analysis of GEN-LARAC with simulation results is given. Simulation results provide an evidence of the excellent performance of GEN-LARAC. We also give a strongly polynomial time approximation algorithm for the QSR (1) problem.

Distance Vector-based Advance Reservation with Delay Performance Guarantees

We explore and demonstrate the feasibility of implementing distributed solutions for advance reservation of network resources. We introduce a new distributed, distance-vector algorithm, called Distributed Advance Reservation (DAR), that provably returns the earliest time possible for setting up a connection between any two nodes. Our main findings are the following: (i) we prove that widest path routing and path switching (i.e, allowing a connection to switch between different paths) are necessary to guarantee earliest scheduling; (ii) we propose and analyze a novel approach for loop-free distributed widest path routing, leveraging the recently proposed DIV framework. Our routing results directly extend to on-demand and inter-domain QoS routing problems.

Based on the Genetic Algorithm to Optimize the QoS Routing Algorithm

This article introduce the genetic algorithm to solve the routing problem with QoS requirements, solve the traditional routing algorithms in completely the limitation of the NP problem. QoS routing optimization model is given, and the detailed design of genetic algorithm encoding scheme, fitness function, selection operator, crossover operator and mutation operator. Finally, the simulation experiment algorithm according to have better convergence and stability, in solving the problem of QoS routing is feasible.

Real-Time Link-Reliability Routing for QoS in Wireless Sensor Networks

This paper proposes a Real-Time Link Reliability Routing protocol for wireless sensor networks (WSNs). The protocol achieves to reduce packet deadline miss ratio while considering link reliability, two-hop velocity and power efficiency and utilizes memory and computational effective methods for estimating the link metrics. Numerical results provide insights that the protocol has a lower packet deadline miss ratio and improved sensor network lifetime. The results show that the proposed protocol is a feasible solution to the QoS routing problem in wireless sensor networks that support real-time applications.

A Multiple Constrained QoS Routing Algorithm for the Wireless Sensor Networks

Routing problem is one of the most important issues to a wireless sensor network (WSN). It is the key problem to find an efficient energy strategy for prolonging network's lifetime because power supply might be impossible. This paper discusses the multicast routing problem of WSN with multiple QoS constraints, which may deal with the delay, bandwidth, hop count and packet reception rat and surplus energy metrics, and finds a minimum resource consumption path while satisfying multiple constraints optimization conditions, and describes a network model for researching the multicast routing problem. It presents a dynamic multicast routing algorithm with multiple QoS constraints (MCQoSRA). The MCQoSRA successfully solves the QoS routing problems when multicast nodes change dynamically in the networks. The MCQoSRA only requires the local state information of the link (or node), but does not require any global network sate to be maintained. In MCQoSRA, a multicast group member can join or leave the multicast session dynamically. The MCQoSRA can effectively decrease the overhead for constructing a multicast tree and the delay of the nodes, and improve the success ratio of seeking links. Simulation results show that the MCQoSRA provides an available means to implement multicast routing, and adapt to all kinds of the topology networks, and have better expansibility.

An Efficient Approximate Algorithm for Disjoint QoS Routing

Disjoint routing is used to find the disjoint paths between a source and a destination subject to QoS requirements. Disjoint QoS routing is an effective strategy to achieve robustness, load balancing, congestion reduction, and an increased throughput in computer networks. For multiple additive constraints, disjoint QoS routing is an NP-complete class that cannot be exactly solved in polynomial time. In the paper, the disjoint QoS routing problem was formulated as a 0-1 integer linear programming. The complicating constraints were included in the objective function using an adaptive penalty function. The special model with a totally unimodular constraint coefficient matrix was constructed and could be solved rapidly as a linear programming. An efficient algorithm using an adaptive penalty function and 0-1 integer linear programming for the disjoint QoS routing problems was designed. The proposed algorithm could obtain the optimal solution, considerably reducing the computational time consumption and improving the computational efficiency. Theoretical analysis and simulation experiments were performed to evaluate the proposed algorithm performance. Through the establishment of random network topologies using Matlab, the average running time, the optimal objective value, and the success rate were evaluated based on the optimal values obtained in Cplex. The simulation experiments validated the effectiveness of the proposed heuristic algorithm.

QoS Routing Algorithm Using Competitive PCNN

The solution of the multi-constrained QoS routing is translated into a shortest path problem for a weighted graph, and the problem of multi-constrained QoS routing is successfully solved using the properties of pulse wave parallel propagation of the competitive PCNN. The number of iteration of our algorithm is dependent of the length of the globally optimal multi-constrained QoS routing between source node and destination node and independent of the number of nodes and edges and the complexity of network distribution structure. The method shows better computational performance and dominance and has important significance in both theory and applications.