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

In MANET, the multicast routing is considered as a non-deterministic polynomial (NP) complexity, it contains assorted objectives and restrictions. In the multicast issue of MANET, the Quality of services (QoS) based upon cost, delay, jitter, bandwidth, these are constantly deemed as multi-objective for intending multiple cast routing protocols. Conversely, mobile node has finite battery energy and the lifetime of network depending on its mobile node battery energy. If the mobile node has high battery energy consumption, it automatically reduces the network’s life time because of their route breaks. Alternatively, node’s battery energy has to be consumed to ensure higher level quality of services in multicast routing for transmitting the accurate data anywhere and anytime. Therefore, the network lifespan is deemed as multi-objective in the multicast routing (MR) problem. To overcome these issues, QoS and Dr. Valli Kumari Vatsavayi2 2Professor, Department of Electronic Communication and Engineering, Andhra University, visakhapatnam,Andhra Pradesh ,India. 2Email:vallikumariv001@yahoo.com Network Lifetime Aware Reliable Multicast Routing Protocol are proposed by applying Chaos integrated Cuckoo Search Rider Optimization Algorithm for effectual data transmission in MANET (QOS-MRP-CSROA-MANET). The proposed method is the joint execution of both the Cuckoo Search Algorithm with chaos theory (Chaotic-CSA) and Rider Optimization (ROA) algorithm and hence it is called as Chaotic-CSA-ROA, which is utilized to solve the MR problem of MANET. Here, the MR problem of MANET have five objectives, viz cost, delay, jitter, bandwidth, network lifetime are optimized with the help of Chaotic-CSA-ROA. Then the proposed method is simulated in NS2 simulator for validating the performance of the proposed QOS-MRP- CSROA-MANET system. Here, evaluation metrics, via delay, delivery ratio, drop, Network lifespan, overhead and throughput are analyzed with node, rate and speed. The proposed QOS-MRP-CSROA-MANET provide higher throughput in node as 32.9496% and 65.5839%, higher throughput in rate as 16.6049% and 30.4654%, higherthroughput in speed as 10.1298% and 7.0825%, low packet drop in node as 63.7313% and 52.2255%, low packet drop in rate as 51.5528% and 25.6220%, low packet drop in speed as 18.0857% and 24.5953% compared with existing methods, like QOS aware of multicast routing protocol using particle swarm optimization algorithm in MANET (QOS-MRP-PSOA-MANET) and QOS aware of multicast routing protocol using genetic algorithm in MANET (QOS-MRP-GA-MANET) respectively.

This paper discusses the multicast routing problem with multiple QoS constraints, which may deal with the delay, delay jitter, bandwidth and packet loss metrics, and describes a network model for researching the routing problem. It presents a multicast routing protocol with multiple QoS constraints (MRPMQ). The MRPMQ attempts to significantly reduce the overhead of constructing a multicast tree with multiple QoS constraints. In MPRMQ, a multicast group member can join or leave a multicast session dynamically, which should not disrupt the multicast tree. It also attempts to minimize overall cost of the tree, and satisfy the multiple QoS constraints and least cost (or lower cost) requirements. In this paper, the proof of correctness and a complexity analysis of the MRPMQ are also given. Simulation results show that MRPMQ is a feasible approach to multicast routing with multiple QoS constraints.

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.

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 wireless networks, the multicast QoS routing is a key technique to increase bandwidth utilization, but the multicast routing is typically complicated and difficult because it belongs to the NP-complete problem. The main goal of a delay-bounded wireless multicast algorithm is to determine the optimal multicast tree that has the least cost while satisfying the delay-bounded requirement. However, previous studies suffer from the Tree setup-break and dangling node problems, and yield a large number of control messages. This paper thus proposes the adaptive distributed multicast routing (ADMR) algorithm to guarantee cycle-free, and to overcome these two problems while yielding the least-cost delay-bounded multicast tree for high-density member multicast networks. Numerical results indicate that ADMR significantly outperforms the Jia-based algorithms in number of control messages and setup convergent time.

A near-optimal multicast scheme for mobile ad hoc networks using a hybrid genetic algorithm

The least-cost multicast routing with delay constrained is an NP-Complete problems, to deal with which, a Multi-Agent Immune Clonal Selection Algorithm based multicast routing (MAICSA) is proposed in this paper. MAICSA combines the characteristic of Multi-Agent with the search strategy of Immune Clonal Selection Algorithm. To compare with the conventional Genetic Algorithm (GA), MAICSA overcomes the most serious drawbacks, such as slow convergence rate and “prematurity”. The experimental results show that MAICSA has faster astringency and higher precision than traditional GA, MAGA (Multi-Agent multicast routing based on Genetic Algorithm) and MAIA (Multi-Agent multicast routing based on Immune Algorithm).

As a key issue in multicast routing with quality of service (QoS) support, constrained minimum Steiner tree (CMST) problem has been a research focus for more than a decade, and tens of heuristics have been developed to solve this NP-complete problem. Among all the previously proposed algorithms, the bounded shortest path algorithm (BSMA) (IEEE INFOCOM'95 1995; 1:377–385) have been proved to be capable of producing a multicast tree that has on average the lowest cost. However, such an excellent cost performance is accompanied with an extremely high time complexity. Recently, Feng et al. presented an alternative implementation of BSMA, which makes use of the latest research results on the delay-constrained least cost (DCLC) routing problem. Simulations indicate that, in comparison with the original implementation, the alternative implementation has a much lower time complexity with virtually identical cost performance, and it also runs much faster than many renowned heuristics such as KPP (IEEE/ACM Trans. Networking 1993; 1(3):286–292) and CAO (The design and evaluation of routing algorithms for real-time channels. Technical Report ICSI TR-94-024, International Computer Science Institute, University of California at Berkeley, June 1994). In this paper, we propose a brand new heuristic TCF, which is based on an idea called ‘tightest constraint first.’ TCF runs a DCLC heuristic only once for each destination and therefore has a provably low time complexity. We further propose an iterative heuristic ITCF, which uses TCF to obtain an initial tree and then gradually refines it. Extensive simulations demonstrate that, in the average sense, TCF can achieve a cost performance comparable to or better than that of BSMA, the cost performance of ITCF is even better than that of TCF, TCF runs approximately twice as fast as ITCF, and ITCF runs 2–4 times as fast as the best implementation of BSMA. Copyright © 2005 John Wiley & Sons, Ltd.

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.

Bandwidth-delay constrained least-cost multicast routing is a typical NP-complete problem. Although some swarm-based intelligent algorithms (e.g., genetic algorithm (GA)) are proposed to solve this problem, the shortcomings of local search affect the computational effectiveness. Taking the ability of building a robust network of Physarum network model (PN), a new hybrid algorithm, Physarum network-based genetic algorithm (named as PNGA), is proposed in this paper. In PNGA, an updating strategy based on PN is used for improving the crossover operator of traditional GA, in which the same parts of parent chromosomes are reserved and the new offspring by the \(Physarum\) network model is generated. In order to estimate the effectiveness of our proposed optimized strategy, some typical genetic algorithms and the proposed PNGA are compared for solving multicast routing. The experiments show that PNGA has more efficient than original GA. More importantly, the PNGA is more robustness that is very important for solving the multicast routing problem.

Multicast routing for wavelength division multiplexing optical network is a challenging problem in optical networks. The Multicast Routing and Wavelength Assignment (MRWA) problem has been proved to be a NP complete problem. In this paper, the MRWA problem in Wavelength Division Multiplexing (WDM) has been modeled as a Multi-Objective Multicast Routing and Wavelength Assignment (MOMRWA) optimization problem with three optimization objectives, including minimizing the resource cost, minimizing the end-to-end delay and minimizing the used channels. Some Quality of Service metrics have also been considered in MOMRWA. To tackle the MOMRWA problem, a multi-objective genetic algorithm, namely MRWA_SSNSGA-II, has been proposed, which is based on the Steady-State Non-Dominated Sorting Genetic Algorithm II combined with the Efficient Non-Domination Level Update (ENLU) strategy. The purpose of the ENLU strategy is to reduce the computing time of maintaining the Non-Domination Level structure. In order to avoid the loop generated by the gene recombination, a light tree recovery mechanism based on the Minimum Path Cost Heuristic has been proposed. We evaluate our proposed MRWA_SSNSGA-II on a large number of test instances with different sizes. Experimental results demonstrate that MRWA_SSNSGA-II outperformed some recent GA based multi-objective optimization algorithms for MOMRWA problem in terms of the solution quality.

MRAGA (Multicast Routing Algorithm based on Genetic algorithm) for the Delay-Constrained Minimum-Energy MulticastRouting problem was presented.The genetic operators of this algorithm reduce the transmission delay and energy consumption of multicast trees, thus accelerating the convergence speed of the algorithm.Experiment results show that the multicast tree found by this algorithm not only guarantee the delay constraint, but also has the minimum energy consumption.Furthermore, this algorithm converges quickly.

In this paper, we considered previously existing multicast routing algorism and protocol and especially put more attention on CBT routing protocol to analyze its strength and weakness. As a result, traffic was converged upon core router because of structural problem of CBT protocol and according to the converged traffic, there was congestion at the core link, thus it caused efficiency degrades of the whole routing. Therefore, we proposed a way of conversion to Anycast Routing method from the method of CBT multicast tree routing that was suitable for traffic decentralization even though there was high bandwidth depended on increment of traffic load. In order to support multimedia service that requires from small to large bandwidth and to consider multicast routing protocol to improve characteristic of multicast packet’s delay, CBT/Anycast routing method can be proposed as an alternative plan for freedom of bandwidth in traffic.KeywordsInternet applicationsmulticast routinganycast routingcore base tree

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.

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.