Chews First Delaunay Triangulation refinement Scheme-Based Positioning of RSUs for Optimal Network Coverage in VANETs

The temporal network fragmentation and uncertain vehicle mobility are considered to impact the communication connectivity among the vehicular nodes of the network. In this context, Road Side Units (RSUs) play an anchor role in enhancing the vehicle-to-vehicle (V2V) communication connectivity and support Vehicle-to-Infrastructure (V2I) communication. In the current scenario, deploying a huge number of RSUs in the vehicular networks at an initial stage is completely impossible as it incurs high installation cost and authority restriction. Moreover, the optimal placement of RSUs in the vehicular network needs to be enforced for attaining maximized network coverage. In this paper, Chews First Delaunay Triangulation Refinement Scheme (CFDTRS) is proposed for optimal positioning of RSUs in order to attain optimal network coverage in the vehicular network with minimized cost. This CFDTRS considered the factors of vehicular density, number of obstacles in the map, intersection popularity and global coverage into account during the placement of RSUs. It is proposed with the objective of deploying required number of RSUs within the range of data transmission in order to achieve maximal coverage in the convex map, such that each area of the convex map is completely covered with at least a single RSU in the existence of multiple number of obstacles. The simulation results of the proposed CFDTRS attained from the real time situations of simplex, moderate and complex maps confirmed improved packet delivery rate of 9.32%, throughput by 10.74% with minimized packet loss of 9.14% and reduced end-to-end delay of 19.31$, compared to the benchmarked schemes considered for investigation.

Development of a topology-based current-flux characteristic approximation in a Hamiltonian model of a reluctance machine

The paper presents an algorithm for the construction of an approximation of a highly nonlinear current-flux characteristic of a synchronous reluctance machine. Such an approximation is required in a Hamiltonian model of an electric machine and the constructed approximation is suited to be used in such a model. It employs a simplicial approximation based on irregular points sets in the spaces of currents and fluxes. The sets are constructed by the iterative insertion of new points. Initially the sets contain an arbitrarily small number of elements. The insertion is based on an approximation error calculation. Based on the sets containing possibly small number of elements, the proposed procedure leads to smooth and precise approximation. Due to the nonlinearity of the approximated characteristics, ambiguities can occur. A method for the triangulation refinement of the sets of currents and fluxes that eliminates them is also presented. In the paper, a reluctance machine model using the constructed approximation is described and compared with a model using the approximation based on regular sets

EXPLOITING THE MEMORY HIERARCHY OF MULTICORE SYSTEMS FOR PARALLEL TRIANGULATION REFINEMENT

A novel parallelization of the Lepp-bisection algorithm for triangulation refinement on multicore systems is presented. Randomization and wise use of the memory hierarchy are shown to highly improve algorithm performance. Given a list of selected triangles to be refined, random selection of candidates together with pre-fetching of Lepp-submeshes lead to a scalable and efficient multi-core parallel implementation. The quality of the refinement is shown to be preserved.