We present a force-based genetic algorithm for self-spreading mobile nodes uniformly over a geographical area. Wireless mobile nodes adjust their speed and direction using a genetic algorithm, where each mobile node exchanges its genetic information of speed and direction encoded in its chromosomes with the neighboring nodes. Simulation experiments show encouraging results for the performance of our force-based genetic algorithm with respect to normalized area coverage.
Traffic between a source-destination pair is then split between the primary and secondary LSPs using an ABR-like explicit-rate feedback gathered from the network. Taking into consideration the packet reordering effect of packet-based load balancing schemes, we propose a novel traffic splitting mechanism that operates on a per-flow basis. We show using a variety of scenarios that deploying Bow.hased multipath traffic engineering not only provides significantly and consistently better throughput than that of a single path hut is also void of any packet reorderings.
There has been increased research interest in providing uniform distribution of autonomous mobile nodes controlled by active running software agents over an unknown geographical area in Mobile Ad-hoc networks (MANETs). This problem becomes more challenging under the harsh and bandwidth limited conditions imposed by military applications. In this framework, the software agent running at the application layer for each autonomous mobile node adjusts its direction and speed by using local information from its neighbors. A genetic algorithm (GA) is used by each node to select the ''fitter'' speed and direction options among exponentially large number of choices converging towards a uniform distribution. For a military application example, consider that in the observed occurrence of a threat situation, ifthe number ofautonomous mobile agents change with time (e.g., losing assets during an operation), the remaining agents should reposition themselves to compensate the lost in coverage and network connectivity. We implemented simulation software to evaluate the effectiveness of GAs within these types of military applications. The results show that GAs can be applied to autonomous mobile nodes and are an effective tool for providing a robust solution for network area coverage under restrained communication conditions.
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