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-In this paper, we propose a new ant-based algorithm for the dynamic routing and wavelength assignment (RWA) problem in optical WDM networks under the wavelength continuity constraint.Unlike conventional approaches, which usually require centralized global network information, our new RWA algorithm constructs the routing solution in a distributed manner by means of cooperative ants.To facilitate the ants' foraging task, we adopt in our algorithm a probabilistic routing table structure for route selection. The new algorithm is highly adaptive in that it always keeps a suitable number of ants in the network to cooperatively explore the network states and continuously update the routing tables, so that the route for a connection request can be determined promptly by the current states of routing tables with only a small setup delay. Some new schemes for path scoring and path searching are also proposed to enhance the performance of our ant-based algorithm. Extensive simulation results upon three typical network topologies indicate that the proposed algorithm has a very good adaptability to traffic variations and it outperforms both the fixed routing algorithm and the promising fixed-alternate routing algorithm in terms of blocking probability. The ability to guarantee both a low blocking probability and a small setup delay makes the new ant-based routing algorithm very attractive for both the optical circuit switching networks and future optical burst switching works.

SummaryGenetic Algorithms (GA) provide an attractive approach to solving the challenging problem of dynamic routing and wavelength assignment (RWA) in optical WDM networks, because they usually achieve a significantly low blocking probability. Available GA-based dynamic RWA algorithms were designed mainly for WDM networks with a wavelength continuity constraint, and they can not be applied directly to WDM networks with wavelength conversion capability. Furthermore, the available GA-based dynamic RWA algorithms suffer from the problem of requiring a very time consuming process to generate the first population of routes for a request, which may results in a significantly large delay in path setup. In this paper, we study the dynamic RWA problem in WDM networks with sparse wavelength conversion and propose a novel hybrid algorithm for it based on the combination of mobile agents technique and GA. By keeping a suitable number of mobile agents in the network to cooperatively explore the network states and continuously update the routing tables, the new hybrid algorithm can promptly determine the first population of routes for a new request based on the routing table of its source node, without requiring the time consuming process associated with current GA-based dynamic RWA algorithms. To achieve a good load balance in WDM networks with sparse wavelength conversion, we adopt in our hybrid algorithm a new reproduction scheme and a new fitness function that simultaneously takes into account the path length, number of free wavelengths, and wavelength conversion capability in route selection. Our new hybrid algorithm achieves a better load balance and results in a significantly lower blocking probability than does the Fixed-Alternate routing algorithm, both for optical networks with sparse and full-range wavelength converters and for optical networks with sparse and limited-range wavelength converters. This was verified by an extensive simulation study on the ns-2 network simulator and two typical network topologies. The ability to guarantee both a low blocking probability and a small setup delay makes the new hybrid dynamic RWA algorithm very attractive for current optical circuit switching networks and also for the next generation optical burst switching networks.

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Together with the 30-y ear-old signal Ll CIA, the new signal L2C, offered b y the modernized GPS program, assures a future for civil GPS dual-frequenc y receivers which propose a better performance than the current single-frequenc y ones. This paper introduces a novel combined acquisition method dedicated to the GPS dual-frequenc y Ll CIA and L2C receivers. The method exploits the capacit y of both the signal channels as well as the advantages of differential signal processing. High detection sensitivit y at a reasonable complexit y is the main advantage of the proposed method with respect to others in literature.

Abstract. In this paper, we consider the problem of survivable routing in dynamic WDM networks with single link failure model. Our work mainly concerns in how to dynamically determine a protection cycle (i.e., two link-disjoint paths between a node pair) to establish a dependable lightpath with backup paths sharing. This problem is identified as NP-complete, thus a heuristic for finding near optimal solution with reasonable computation time is usually preferred. Inspired from the principle of ant colony optimization, we propose in this paper an ant-based mobile agents algorithm for this problem with improved blocking performance. To enable the new ant-based algorithm, we propose to use on each network node both a routing table that contains a set of feasible protection cycles between source destination nodes and also a pheromone table for mobile agents. By keeping a suitable number of mobile agents in a network to continually and proactively update the routing tables based on the current network congestion state, the routing solution of a connection request can be obtained with a reasonable computation time. Extensive simulation results upon the ns-2 network simulator and two typical network topologies show that our new algorithm can achieve a significantly lower blocking probability than the promising algorithm for dynamic lightpath protection proposed in [11] with a comparable computation complexity.

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We study the survivable network design problem (SNDP) for simultaneous unicast and anycast flows in networks where the link cost follows All Capacities Modular Cost (ACMC) model. Given a network modeled by a connected, undirected graph and a set of flow demands, this problem aims at finding a set of connections with a minimized network cost in order to protect the network against any single failure. This paper proposes a new Genetic Algorithm with an efficient encoding to solve the SNDP in networks with ACMC model (A-SNDP). Our encoding scheme is simple and allows large search space. Extensive simulation results on real large topology instances show that the proposed algorithm is much more efficient than the Tabu Search and other conventional Genetic Algorithm in terms of minimizing the network cost.