A mobile ad hoc network (MANET) facilitates mobile hosts to communicate with one another based on wireless infrastructure. There are no base stations in ad hoc networks and the mobile hosts act as routers for data packets. Since the mobile hosts in a MANET keep moving, topological changes take place frequently in the network. This cause routing information kept by the nodes to get outdated easily. Effective ways of getting updated routing information is needed. This problem becomes more complex in wireless networks, where bandwidth is limited. This paper proposes an improved dynamic source routing (DSR) algorithm as a solution to this problem. The proposed algorithm, the Improved Dynamic Source Routing (I-DSR), has a hybrid feature, combined proactive and reactive, that enables all the hosts to get updated changing topology information with a low cost in communication instead of enabling only a few hosts to get the information when there is a route request for a new moved destination. In anticipation of the need of a route request to the new moved destination by other hosts, the operations in the algorithm are designed to eliminate these needs for route request flooding and eventually generate a small number of control packets.
Through simulations, we demonstrate that I-DSR gives better network performance than the well-known on-demanding routing protocol, Dynamic Source Routing (DSR) Protocol. As it is improved from DSR, it just needs a few modification on DSR and is easy to implement.
This paper addresses the problem of wavelength assignment and wavelength routing in a wide-area optical network, where Wavelength Division Multiplexing (WDM) technology has emerged as the transmission and switching choice. One of the major design issues in this network is the assignment of the limited number of wavelengths among network stations so that higher aggregate capacity can be achieved. The problem of wavelength assignment and routing is proved to be NP-hard problem. The present literature on this topic is a large repertoire of heuristics that produce good solutions in a reasonable amount of time. These heuristic, however, have restricted applicability in a practical environment because they have a number of fundamental problems including high time complexity, lack of scalability with respect to optimal solutions. In this paper, we propose genetic based algorithm with an objective to simultaneously meet the goals of height performance and fast running time. In addition, we propose to apply the Greedy Random Adaptive Search Procedure (GRASP) to solve the wavelength assignment problem. We demonstrate that our proposed algorithms can achieve lower blocking probability while taking considerably less running time when compared to one of the best known heuristic wavelength assignment algorithms proposed by Zhang and Acampora, in which close to optimal solution can be obtained.