Heterogeneous Roadside Unit Placement in Eco-Sustainable Communication Networks for Intelligent Transportation

Abstract

Faced with the growing demand of highway message propagation, network security, as well as the great challenges of global energy crisis, mobile interconnection and energy conservation are considered to be the key factors to promote the development of automotive electronics innovation in Intelligent Transportation System (ITS). Existing network planning is mainly performance-oriented and often neglects the radiation concerns, which have direct impacts not only on the environment but also on the network operators' long-term profitability. In this paper, we investigate a novel optimization framework for multiple Roadside unit (RSU) deployment in eco-sustainable communication networks for intelligent transportation (IT). The term "eco-sustainable" refers to low carbon, low exposure to radiation, low energy consumption and energy cost. We propose a generic integer linear programming (ILP) model which optimally and simultaneously: (i) minimizes the total cost, (ii) identifies the locations of RSUs, (iii) takes radiation constraints into consideration, (iv) meets the minimum information rate, (v) satisfies the coverage requirements so as to allow the users' accesses through the heterogeneous RSUs. We solve the model using Gurobi, which is the newest ILP solver by now. In addition, a new algorithm is proposed. Computational results show that compared with Gurobi, although there is a gap between the results, a shorter running time stands out in the new algorithm. Besides, we use AIMMS to get an interface of the final result intuitively, which makes improvements in visualization. We can also find when low exposure to radiation is concerned under the "Eco-Sustainable" network planning strategy, more dispersed RSUs to be distributed along with greater changes in the resulting network configuration, and thus the corresponding RSUs energy reduction, carbon emissions reduction as well as operational cost savings can be achieved.