In large scale multihop wireless networks, flat architectures are not scalable. In order to overcome this major drawback, clusterization is introduced to support selforganization and to enable hierarchical routing. When dealing with multihop wireless networks the robustness is a main issue due to the dynamicity of such networks. Several algorithms have been designed for the clusterization process. As far as we know, very few studies check the robustness feature of their clusterization protocols. Moreover, when it is the case, the evaluation is driven by simulations and never by a theoretical approach.In this paper, we show that a clusterization algorithm, that seems to present good properties of robustness, is self-stabilizing. We propose several enhancements to reduce the stabilization time and to improve stability. The use of a Directed Acyclic Graph ensures that the selfstabilizing properties always hold regardless of the underlying topology. These extra criterion are tested by simulations.
Vespa velutina, also known as the Asian hornet, is considered as an invasive species out of its native zone. In particular, since it preys on honey bees, its recent progression in Europe could soon pose a significant risk to the local apiculture activity. European beekeepers are therefore investigating adapted control strategies, including V. velutina nest destruction. Unfortunately, nest location pinpointing generally follows a manual process which can prove tedious, time-consuming and inaccurate. In this article, we propose the use of a network of micro aerial vehicles featuring autonomous and cooperative flight capabilities.We describe an adapted controlled mobility strategy and detail the design of our Virtual Force Protocol (VFP) which allows a swarm of vehicles to track and follow hornets to their nests, while maintaining connectivity through a wireless multi-hop communication route with a remote ground station used to store applicative data such as hornet trajectory and vehicle telemetry. In order to achieve the mission objectives with a minimum of vehicles, we identify through simulations appropriate value for the key parameters of VFP and discuss the obtained network performance.
This paper provides a contribution for NS-3 consisting of a new tool for generating Internet traffic. This tool is based on the Poisson Pareto Burst Process (PPBP), a Long-Range Dependent (LRD) model for network traffic. The PPBP model provides a simple and accurate network traffic generator that matches statistical properties of real-life IP networks. We have implemented this model in NS-3. We evaluate the computing performance of this PPBP implementation. Our results show a moderate overhead introduction in terms of memory needs and a roughly identical cost in CPU time as compared to a simple Poisson traffic generator.
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