Abstract: Intelligent data aggregation approaches and technologies play an important and increasing role in practice due to the widespread adoption of mobile devices in many applications. Motivated not only by the increasing number of mobile devices, but also their ever-growing computing and sensing capabilities, there have been efforts to leverage these devices as destination for offloading computations/data in the context of IoT applications. The special issue aims at presenting a collection of high-quality research papers on the state-of-the-art in the smart data aggregation and routing techniques.
Keywords: Smart network applications, scientific computing and data management, data-driven service management, spatial data techniques, data processing in smart city applications
Abstract: Robots have recently gained a great attention due to their potential to work in dynamic and complex environments with obstacles, which make searching for an optimum path on-the-fly an open challenge. To address this problem, this paper proposes a Genetic Algorithm (GA) based path planning method to work in a dynamic environment called GADPP. The proposed method uses Bezier Curve to refine the final path according to the control points identified by our GADPP. To update the path during its movement, the robot receives a signal from a Base Station (BS) based on the alerts that are periodically triggered by…sensors. Compared to the state-of-the-art methods, GADPP improves the performance of robot based applications in terms of the path length, the smoothness of the path, and the required time to get the optimum path. The improvement ratio regarding the path length is between 6% and 48%. While the path smoothness is improved in the range of 8% and 52%. In addition, GADPP reduces the required time to get the optimum path by 6% up to 47%.
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