An Optical Multicast Routing with Minimal Network Coding Operations in WDM Networks

Network coding can improve the optical multicast routing performance in terms of network throughput, bandwidth utilization, and traffic load balance. But network coding needs high encoding operations costs in all-optical WDM networks due to shortage of optical RAM. In the paper, the network coding operation is defined to evaluate the number of network coding operation cost in the paper. An optical multicast routing algorithm based on minimal number of network coding operations is proposed to improve the multicast capacity. Two heuristic criteria are designed to establish the multicast routing with low network coding cost and high multicast capacity. One is to select one path from the former K shortest paths with the least probability of dropping the multicast maximal capacity. The other is to select the path with lowest potential coding operations with the highest link shared degree among the multiple wavelength disjoint paths cluster from source to each destination. Comparing with the other multicast routing based on network coding, simulation results show that the proposed multicast routing algorithm can effectively reduce the times of network coding operations, can improve the probability of reaching multicast maximal capacity, and can keep the less multicast routing link cost for optical WDM networks

An Optical Multicast Routing with Minimal Network Coding Operations in WDM Networks

Network coding can improve the optical multicast routing performance in terms of network throughput, bandwidth utilization, and traffic load balance. But network coding needs high encoding operations costs in all-optical WDM networks due to shortage of optical RAM. In the paper, the network coding operation is defined to evaluate the number of network coding operation cost in the paper. An optical multicast routing algorithm based on minimal number of network coding operations is proposed to improve the multicast capacity. Two heuristic criteria are designed to establish the multicast routing with low network coding cost and high multicast capacity. One is to select one path from the former shortest paths with the least probability of dropping the multicast maximal capacity. The other is to select the path with lowest potential coding operations with the highest link shared degree among the multiple wavelength disjoint paths cluster from source to each destination. Comparing with the other multicast routing based on network coding, simulation results show that the proposed multicast routing algorithm can effectively reduce the times of network coding operations, can improve the probability of reaching multicast maximal capacity, and can keep the less multicast routing link cost for optical WDM networks

Network coding via evolutionary algorithms

Network coding (NC) is a relatively recent novel technique that generalises network operation beyond traditional store-and-forward routing, allowing intermediate nodes to combine independent data streams linearly. The rapid integration of bandwidth-hungry applications such as video conferencing and HDTV means that NC is a decisive future network technology. NC is gaining popularity since it offers significant benefits, such as throughput gain, robustness, adaptability and resilience. However, it does this at a potential complexity cost in terms of both operational complexity and set-up complexity. This is particularly true of network code construction. Most NC problems related to these complexities are classified as non deterministic polynomial hard (NP-hard) and an evolutionary approach is essential to solve them in polynomial time. This research concentrates on the multicast scenario, particularly: (a) network code construction with optimum network and coding resources; (b) optimising network coding resources; (c) optimising network security with a cost criterion (to combat the unintentionally introduced Byzantine modification security issue). The proposed solution identifies minimal configurations for the source to deliver its multicast traffic whilst allowing intermediate nodes only to perform forwarding and coding. In the method, a preliminary process first provides unevaluated individuals to a search space that it creates using two generic algorithms (augmenting path and linear disjoint path. An initial population is then formed by randomly picking individuals in the search space. Finally, the Multi-objective Genetic algorithm (MOGA) and Vector evaluated Genetic algorithm (VEGA) approaches search the population to identify minimal configurations. Genetic operators (crossover, mutation) contribute to include optimum features (e.g. lower cost, lower coding resources) into feasible minimal configurations. A fitness assignment and individual evaluation process is performed to identify the feasible minimal configurations. Simulations performed on randomly generated acyclic networks are used to quantify the performance of MOGA and VEGA

Multicasting Homogeneous and Heterogeneous Quantum States in Quantum Networks

In this paper, we target the practical implementation issues of quantum multicast networks. First, we design a recursive lossless compression that allows us to control the trade-off between the circuit complexity and the dimension of the compressed quantum state. We give a formula that describes the trade-off, and further analyze how the formula is affected by the controlling parameter of the recursive procedure. Our recursive lossless compression can be applied in a quantum multicast network where the source outputs homogeneous quantum states (many copies of a quantum state) to a set of destinations through a bottleneck. Such a recursive lossless compression is extremely useful in the current situation where the technology of producing large-scale quantum circuits is limited. Second, we develop two lossless compression schemes that work for heterogeneous quantum states (many copies of a set of quantum states) when the set of quantum states satisfies a certain structure. The heterogeneous compression schemes provide extra compressing power over the homogeneous compression scheme. Finally, we realize our heterogeneous compression schemes in several quantum multicast networks, including the single-source multi-terminal model, the multi-source multi-terminal model, and the ring networks. We then analyze the bandwidth requirements for these network models.Comment: 24 pages, 9 figure

Evolutionary Approaches to Minimizing Network Coding Resources

We wish to minimize the resources used for network coding while achieving the desired throughput in a multicast scenario. We employ evolutionary approaches, based on a genetic algorithm, that avoid the computational complexity that makes the problem NP-hard. Our experiments show great improvements over the sub-optimal solutions of prior methods. Our new algorithms improve over our previously proposed algorithm in three ways. First, whereas the previous algorithm can be applied only to acyclic networks, our new method works also with networks with cycles. Second, we enrich the set of components used in the genetic algorithm, which improves the performance. Third, we develop a novel distributed framework. Combining distributed random network coding with our distributed optimization yields a network coding protocol where the resources used for coding are optimized in the setup phase by running our evolutionary algorithm at each node of the network. We demonstrate the effectiveness of our approach by carrying out simulations on a number of different sets of network topologies.Comment: 9 pages, 6 figures, accepted to the 26th Annual IEEE Conference on Computer Communications (INFOCOM 2007