QoS Multicast Routing Algorithm Research Articles

A quantum-inspired binary firefly algorithm for QoS multicast routing

A quantum-inspired binary firefly algorithm for QoS multicast routing

A quantum-inspired binary firefly algorithm for QoS multicast routing

The quality of service multicast routing problem (QoSMRP) is one of the main issues for transmission in wireless mesh networks. It is known to be an NP-hard problem, so many heuristic algorithms have been employed to solve this problem. This paper proposes a new quantum-inspired binary firefly algorithm (QIBFA) to solve the QoSMRP. QIBFA is based on the combination of the standard binary firefly algorithm (BFA) with the concept and principles of the quantum evolutionary algorithm (QEA). Its main idea is the introduction of the Q-bit and the quantum operator adopted in the quantum-inspired evolutionary algorithm (QEA) into the binary firefly algorithm to avoid the premature convergence, ensure the diversity of the solutions and enhance the performance of the BFA. The simulation results show the efficiency and the superiority of our proposed algorithm compared with other existing algorithms in the literature.

I-QCA: An intelligent framework for quality of service multicast routing in multichannel multiradio wireless mesh networks

Multicast routing has brought a revolution by enabling the delivery of the same content to a group of receivers simultaneously. However, multicast routing in multichannel multiradio wireless mesh networks has been proved to be an NP-hard problem. To achieve optimal performance in multichannel multiradio wireless mesh networks the channel assignment strategy plays an important role. In this paper, we present an intelligent Quality of service multicast routing and Channel Assignment (i-QCA) algorithm which solves the multicast tree construction and channel assignment problem conjointly by intelligent computational methods. The multicast tree construction algorithm is based on the differential evolution approach. The channel assignments in prior works are mostly oriented toward heuristic or meta heuristic approaches and hence produce suboptimal results. The proposed algorithm consists of a genetic algorithm based channel assignment strategy and determines a delay, jitter bounded minimal interference lowcost multicast tree. Our experimental results clearly show that the proposed algorithm achieves much better performance as compared to Multi Channel Multicast (MCM) and QoS Multicast Routing and Channel Assignment (QoS-MRCA) algorithm in multichannel multiradio wireless mesh network environments.

An Enhanced Safety Algorithm for Network QoS Multicast Routing Optimization

In the traditional QoS multicast network routing algorithm, when the node encounters abnormal traffic network data, the node data overflows. The current protocol is lack of directional guidance for overflow, which causes abnormal data jitter and disorder, the data path planning of traditional Qos protocol blocked and network delay. In order to solve this problem, this paper presents an enhanced safety algorithm for QoS multicast network routing optimization. The constraint relationship between security level of input parameters of network service request and trust level of network service is set, in order to judge and screen the traffic overflow nodes generated by abnormal operation. Then filtered set of network services is used to construct a multi-path network services digraph and converts it into web services selection tree in use of pointing relationship between sub-services. Finally, it sorts the paths and according to the size of Qos path selects the optimal one to carry out through tracing method. Simulation results show the new algorithm has optimum network quality of service and lower complexity. DOI : http://dx.doi.org/10.11591/telkomnika.v12i4.4245

QoS Multicast Routing Algorithm Based on Crowding Ant Colony Algorithm

The basic ant colony algorithm is easy to fall into local optimum and its convergent speed is slow for solving multiple QoS multicast routing problems. Therefore, a crowding ant colony algorithm is proposed in this paper to solve the problems. Crowded degree in artificial fish swarm algorithm is used to adjust nodes transition strategy dynamically according to the congestion of nodes. Stagnation behavior is judged by the similarity of multicast tree and chaos perturbation is utilized to update the pheromone trail on the multicast tree that may fall into local optimum in order that solutions can range out of local optimum. According to simulations, the global search is enhanced at the initial and convergence rate has improved greatly at the later. The improved algorithm is feasible and effective.

Bandwidth Constrained Multicast Routing for TDMA-Based Mobile Ad Hoc Networks

 Abstract—Multicasting, which is a one-to-many communication, is motivated by the increasing importance of real-time and multimedia applications with different QoS requirements. The QoS metric considered in this work is the bandwidth. We approach this problem by assuming a common channel shared by all hosts under a TDMA (Time Division Multiple Access) channel model. In this paper, we propose a new TDMA-based QoS multicast routing algorithm--PSLCB, which aims at minimizing the number of forwarders so as to reduce bandwidth consumption. Simulations results show that compared with ODMRP, our proposed QoS routing algorithm improve packet delivery ratio and reduce end-to-end packet delay. Index Terms—slot, multicast, bandwidth, routing

QoS Multicast Routing Algorithm Based on Particle Swarm Optimization

QoS Multicast Routing Algorithm Based on Particle Swarm Optimization

FPGA Implementation of QoS Multicast Routing Algorithm of Mine Internet of Things Perception Layer based on Ant Colony Algorithm

FPGA Implementation of QoS Multicast Routing Algorithm of Mine Internet of Things Perception Layer based on Ant Colony Algorithm

An Energy Efficient Wireless Sensor Network QOS Multicast Routing Algorithms Based on Ant Colony Algorithm

Multicast routing technology of wireless sensor network is a method of transferring special data to a group of clients selectively; therefore, quality of the services is the key to evaluate the method. Ant colony algorithm is a bionic optimization algorithm. Improved QoS Multicast Routing Algorithm is proposed based on energy constraint and based on ant colony algorithm, it takes into account the energy cost routing, making the nodes to establish of minimum cost path under the condition of energy constraint. The results show that this algorithm can obtain better energy balance, improve the network services of the time. This algorithm applies to energy-sensitive multicast applications in wireless sensor networks.

An Agent-based Distributed QoS Multicast Routing Algorithm

Abstract In accordance with multiple constrained QoS multicast routing problem, a new algorithm AQRAA (Agent-based Distributed QoS Multicast Routing Algorithm in Ad Hoc networks) is proposed based on Agent. AQRA takes advantage of the cooperation of different Agent groups to find the optimum multicast routing that satisfies the QoS constraint. AQRA exchanges and transmits routing information to obtain local optimum route and avoid cycle during the Agent meeting. The flexible routing switching and locking guarantees a successful routing connection. The experimental results indicate the feasibility and efficiency of AQRAA.

A Probability Theory Based Intelligent QoS Multicast Routing Algorithm

In this paper, taking the characteristics of NGI (Next Generation Internet) into account, and base on its network model and mathematical model, a probability theory based intelligent QoS multicast routing algorithm is presented. Under inaccurate information of QoS parameters, using fast searching ability of DE (Differential Evolution), the proposed algorithm tries to find a multicast routing tree with the maximum probability of meeting with QoS requirement under the given cost. Simulation results have shown that the proposed algorithm is both feasible and effective.

Tree-based differential evolution algorithm for QoS multicast routing

Differential evolution (DE) algorithm has attracted more and more attention due to its fast optimization performance and good stability. When DE algorithm is applied into multi-constrained multicast routing optimization problem, a common solution to such problem is to merge the paths into a tree after finding paths from the source node to each destination node. This method maybe obtains the better result, but it can consume a lot of computational time. To solve the problem, a tree-based DE algorithm is introduced in this paper. The central operations of the algorithm are realized with tree structure. This method saves the time of finding paths and integrating them to construct a multicast tree. The experiments show that the proposed algorithm can achieve higher success rate than several common algorithms with much smaller running time for different networks.

Hybrid discrete PSO with GA operators for efficient QoS-multicast routing

QoS multicast routing is a non-linear combinatorial optimization problem that arises in many multimedia applications. Providing QoS support is crucial to guarantee effective transportation of multimedia service in multicast communication. Computing the band-width-delay constrained least cost multicast routing tree is a NP-complete problem. In this paper, a novel heuristic QoS multicast routing algorithm with bandwidth and delay constraints is proposed. The algorithm applies the discrete particle swarm optimization algorithm to optimally search the solution space for the optimal multicast tree which satisfies the QoS requirement. New PSO operators have been introduced to modify the original PSO velocity and position update rules to adapt to the discrete solution space of the multicast routing problem. A new adjustable PSO-GA hybrid multicast routing algorithm which combines PSO with genetic operators was proposed. The proposed hybrid technique combines the strengths of PSO and GA to realize the balance between natural selection and good knowledge sharing to provide robust and efficient search of the solution space. Two driving parameters are utilized in the adjustable hybrid model to optimize the performance of the PSO-GA hybrid by giving preference to either PSO or GA. The proposed algorithm is utilized with an efficient dynamic component that is capable of handling dynamic situations arising due to either change in the multicast group membership or node/link failure without the reconstruction of the multicast tree. Simulation results show that the proposed hybrid algorithm can overcome the disadvantages of particle swarm optimization and genetic algorithm, and achieve better QoS performance. Results show that with the correct combination of GA and PSO the hybrid does outperform both the standard PSO and GA models, The flexibility in the choice of parameters in the hybrid algorithm improves the evolutionary operators to generate strong-developing individuals that can achieve faster convergence and avoids premature convergence to local optima.

Based on AFSA-Tabu search algorithm combined QoS Multicast Routing Algorithm

Based on AFSA-Tabu search algorithm combined QoS Multicast Routing Algorithm

A Novel Fast Multi-objective Evolutionary Algorithm for QoS Multicast Routing in MANET

Multicast routing is regarded as a critical component in networks especially the real-time applications become increasingly popular in recent years. Existing multicast routing under certain QoS Constraints tend to use conventional IP QoS architecture based on GA. In this paper, we propose a novel fast multi-objective evolutionary algorithm called QMOEA for solving multicast routing problem (MRP) in MANET. The steps are that, through the analysis of the strengths and limitations of the well-known multicast architecture, we firstly give an improved Core Based Tree model to simplify the MRP. Based on this model, we then propose the QMOEA which integrates the “Greedy”and “family competition”approaches to speed up the convergence and to maintain the diversity of population. After that, we present the theoretical validations for the proposed method to show its efficiency, and finally, the performance of MANET scaled from 20 to 200 nodes with different types of service is evaluated by OPNET, our experimental res...

A new multicast routing protocol with QoS constraints

A QoS multicast routing algorithm for DiffServ networks called PQMRD(Per-class QoS Multicast Routing in DiffServ networks) was proposed.It used different routing strategy to select route in terms of different QoS requirement;in addition,admission control and resource reservation were performed while selecting route.It is proved by the simulation result that inter-class unfairness problem is alleviated.

A Novel Fast Multi -objective Evolutionary Algorithm for QoS Multicast Routing in MANET

A Novel Fast Multi -objective Evolutionary Algorithm for QoS Multicast Routing in MANET

A fuzzy genetic algorithm for QoS multicast routing

It is impossible for nodes in an actual dynamic network to maintain the global accurate network state information. Therefore, it is unreasonable and inefficient to express the QoS constraints with deterministic crisp values. In this paper, the QoS multicast routing problem is solved by use of the generalized fuzzy-constrained fuzzy-optimization model. Both imprecision of the network state information and the fuzziness of QoS constraints are taken into account invoking fuzzy set theory. A new fuzzy genetic algorithm for QoS multicast routing is also presented and simulation experiments demonstrate that the algorithm is efficient.