Solve tree setup-break problem and minimize control overhead in delay-bounded distributed wireless multicast QoS routing

Cognitive wireless mesh networks (CWMNs) were developed to improve the utilization ratio of licensed spectrum. Since the spectrum opportunities for users vary over time and location, enhancing the spectrum effectiveness is a goal and also a challenge for CWMNs. Multimedia applications have recently generated much interest in CWMNs supporting quality-of-service (QoS) communications. Multicast routing and spectrum allocation is an important challenge in CWMNs. In this paper, we study to design an effective multicast routing algorithm based on diversity rate with respect to load balancing and the number of transmissions for CWMNs. In this paper, a load balancing wireless links weight computing function and computing algorithm based on diversity rate (DRLB) are proposed, and a load balancing channel and rate allocating algorithm based on diversity rate (DR2CS) is proposed. On this basis, a load balancing joint multicast routing, channel and rate allocation algorithm based on diversity rate with QoS constraints for CWMNs (LMR2D) is proposed. Balancing the load of node and channel, and minimizing the number of transmissions of multicast tree are the objectives of LMR2D. Firstly, LMR2D computes the weight of wireless links using DRLB and Dijkstra for constructing the load balancing multicast tree step by step. Secondly, LMR2D uses DR2CS to allocate channel and rate of channel to links which is based on the wireless broadcast advantage. Simulation results show that LMR2D can achieve the expected goal. It can not only balance the load of node and channel, but also need lower number of transmissions for multicast tree.

The quality of service (QoS) multicast routing problem is one of the main issues for transmission in communication networks. It is known to be an NP-hard problem, so many heuristic algorithms have been employed to solve the multicast routing problem and find the optimal multicast tree which satisfies the requirements of multiple QoS constraints such as delay, delay jitter, bandwidth and packet loss rate. In this paper, we propose an improved chaotic binary bat algorithm to solve the QoS multicast routing problem. We introduce two modification methods into the binary bat algorithm. First, we use the two most representative chaotic maps, namely the logistic map and the tent map, to determine the parameter [Formula: see text] of the pulse frequency [Formula: see text]. Second, we use a dynamic formulation to update the parameter α of the loudness [Formula: see text]. The aim of these modifications is to enhance the performance and the robustness of the binary bat algorithm and ensure the diversity of the solutions. The simulation results reveal the superiority, effectiveness and efficiency of our proposed algorithms compared with some well-known algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Jumping Particle Swarm Optimization (JPSO), and Binary Bat Algorithm (BBA).

Multicast communication has been commonly used in multiprocessor systems. Current multicast routing methods such as tree-based and path-based approaches may suffer from the problem of multicast deadlocks or long routing delay. In this work we propose a hybrid multicast routing algorithm that combines the advantages of both path-based and tree-based methods. The proposed algorithm together with a router design that requires no additional virtual channel can achieve deadlock-free multicast routing. Very high routing efficiency is achieved by the proposed algorithm due to an adaptive routing strategy according to the traffic load. Experimental results show that the saturation point (in terms of injection ratio) of our algorithm is significantly higher than those of the state-of-the-art tree- and path-based multicast routing algorithms, while at the saturation points of these two algorithms, our algorithm has a routing latency that is 21% and 43% smaller than those of the tree- and the path-based algorithms, respectively.

The need for supporting real time multimedia applications for users of Mobile Ad hoc Network (MANET) is becoming essential. The aim of this paper is to construct bandwidth-satisfied multicast tree for QoS routing in TDMA-based mobile ad hoc networks. The paper proposes an efficient path bandwidth calculation algorithm. An effective multicasting routing algorithm is presented to build a multicast tree among all the multicast members. Simulation results show that compared with MAODV, our proposed QoS routing algorithm can significantly improve the performance of QoS multicast routing in MANETs in terms of success ratio and average delay.

For multimedia applications, the routing algorithms should consider many Quality of Service (QoS) parameters. However, to find routes with two or more QoS parameters is an NP-hard problem. Therefore, recently many researchers are trying to use heuristic methods such as Genetic Algorithm (GA). In a previous work, a QoS multicast routing based on GA was proposed. However, in this algorithm, the multicast routing falls in the local minimum and cannot satisfy the application requirements. In this paper, we propose a new QoS multicast routing protocol, which has better genetic operations than the conventional algorithm, resulting in a better performance.

Performance evaluation of a mesh-evolving quality-of-service-aware multicast routing protocol for mobile ad hoc networks

Prompt and reliable communication between vehicular nodes are essential as its limited coverage and dynamic mobility rate introduces frequent change of network topology. The key feature of vehicular communication that establishes direct connectivity or Road Side Unit-based data transfer among vehicular nodes is responsible for sharing emergency information during critical situations. Multicast routing data dissemination among vehicular nodes is considered to be the potential method of parallel data transfer as they facilitate the option of determining an optimal multicast tree from feasible number of multicast trees established between the source and destinations. This estimation of optimal multicast tree using meta-heuristic techniques is confirmed to improve the throughput and reliability of the network when QoS-based constraints are imposed during multicast routing. An Improved Shuffled Frog-Leaping Algorithm-Based QoS Constrained Multicast Routing (ISFLABMR) is proposed for estimating an optimal multicast tree that confirms effective multi-constrained applied multicast routing between vehicular nodes. ISFLABMR minimizes the cost of transmission to 22% by reducing the number of multicast clusters formed during multicasting through the utilization of local and global-based optimizations. The simulation results of ISFLABMR proveits predominant reduction rate of 24% and 21% in average packet latency and energy consumptions incurred under multicast routing.

With the growing demand of multimedia applications, quality of service (QoS) assured that multicast routing is an important issue in wireless mesh networks. Finding a multicast tree which satisfies the multiple constraints is a NP-Complete problem. In this paper, we propose a discrete particle swarm optimization (DPSO) approach for finding the minimum tree cost from a given source to a set of destination with delay and bandwidth constraint. The concept of relative position base indexing (RPI) is used to convert a continuous space to discrete space for multicast routing. The simulation is carried out in NS-2.26 and the comparison is made with respect to tree cost under two scenarios, namely varying node mobility and increasing number of nodes. The results demonstrate that DPSO has better speed, performance, and efficiency than multicast routing based on genetic algorithm.

In this paper, we study the multicast routing problem in ATM networks. The multicast routing problem, also known as the Steiner tree problem, has been well studied in the literature. However, less attention has been made for the definition of link costs and evaluating the performance of multicast routing algorithm from the network revenue point of view. Therefore, in this paper, we first proposed two approaches, namely, the Markov decision process-based (MDP) and maximum free residual capacity-based (MFC) approaches for defining link costs. We then developed three heuristic algorithms for finding near optimal multicast trees. Our simulation results indicate algorithms that estimating link costs based on the MDP approach yield better performance than those that based on the MFC approach. Among the three multicast routing algorithms that use MDP approach for estimating link costs, the algorithm that treats a multicast call as a collection of multiple point-to-point calls yields the worst performance while the algorithm that based on the genetic algorithm yields the best performance.

Wavelength‐division multiplexed (WDM) networks using wavelength‐routing are considered to be potential candidates for the next generation wide‐area backbone networks. At present, Internet Protocol (IP) is considered as de facto standard for transferring data in a wide‐area network. As WDM technology matures, there is a growing interest in integrated IP‐over‐WDM networks. Supporting multicasting in these networks poses a challenging topic. In IP multicast routing, only a subset of nodes may have multicast capability. The nodes that are not supporting multicast routing are by‐passed using IP tunneling concept. Because of IP tunneling, a node with optical splitting capability may not be considered while constructing a multicast tree. This results in poor bandwidth utilization. Some times, non‐delivery of data to some destinations may also happen. Hence, the IP multicast routing protocol need to consider the capabilities of the nodes. But, it may require some modifications to the existing IP multicast routing algorithms. We propose an approach, where nodes with splitting capability and wavelength conversion capability are connected and form a backbone. Hence, IP multicast routing algorithms need not consider the special capabilities of the nodes and these algorithms do not require any modifications. In multicast routing establishing a protection path is a difficult task, since the capabilities of nodes differ from each other. Using our approach it is possible to recover from a link or node failure. Also in a wide area network, delay involved in generating and establishing connections for multicast traffic is very high. In our approach, this delay is low, since it makes use of pre‐established connections (i.e., pre‐established backbone). The effectiveness of our proposed approach is demonstrated using extensive simulation experiments. The blocking performance of the proposed approach is also studied for dynamically arriving multicast sessions.

A genetic algorithm for energy-efficient based multicast routing on MANETs

Multicasting is an efficient and effective approach for supporting content distribution based on the current Internet infrastructure. In this paper, we have proposed a source-initiated CRMA (cycle-breaking rollback multicast routing algorithm), which is a congestion-aware QoS (quality of service) based multicast routing algorithm. CRMA attempts to achieve the objective of minimizing network congestion conditions while satisfying bandwidth and end-to-end path delay requirements from users. Our proposed approach has several features: (1) it constructs a shared symmetric distribution tree for multicast source(s) and its members rather than the conventional approach of constructing multicast tree; (2) CRMA combines the multicast path computation with resource allocation through introducing the WFQ (weighted fair queuing) packet scheduling into path computation; (3) CRMA can be easily implemented and integrated into the common shortest path router architecture without a thorough adjustment. Through extensive simulations, we demonstrate that our CRMA can effectively reduce the cost, which is the reflection of network congestion conditions, of the computed multicast tree, compared to other proposed multicast routing schemes.

Multicast routing is establishing a tree which is rooted from the source node and contains all the multicast destinations. A multicast routing tree with multiple QoS constraints may be the tree in which the delay, delay-jitter, packet-loss and bandwidth should satisfy the pre-specified bounds. This paper presents a hierarchical QoS multicast routing protocol (HQMRP) for mobile ad-hoc networks. It can provide QoS-sensitive routes in a scalable and flexible way, in the network environment with mobility. In the proposed HQMRP scheme, each local node just only needs to maintain local multicast routing information and/or summary information of other clusters (or domains), but does not requires any global ad hoc network states to be maintained. The HQMRP attempts to significantly reduce the overhead of constructing a multicast tree with multiple QoS constraints. The performance measures of HQMRP are evaluated using simulation. Simulation results show that HQMRP is an available approach to multicast routing decision for mobile ad-hoc networks.

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.

In this paper, a QoS (quality of service) multicast routing scheme in NGI (next generation Internet) is proposed based on genetic engineering and microeconomics. It can not only deal with network status inaccuracy, but also help prevent network overload and meet with intra-group fairness, trying to find a multicast routing tree with bandwidth, delay, delay jitter and error rate satisfaction degree, bandwidth availability degree and fairness degree achieved or approached Pareto optimum