Currently, more than 9 billion things are connected in the Internet of Things (IoT). This number is expected to exceed 20 billion in the near future, and the number of things is quickly increasing, indicating that numerous data will be generated. It is necessary to build an infrastructure to manage the connected things. Cloud computing has become important in terms of analysis and data storage for IoT. In this paper, we consider a cloud broker, which is an intermediary in the infrastructure that manages the connected things in cloud computing. We study an optimization problem for maximizing the profit of the broker while minimizing the response time of the request and the energy consumption. A multi-objective particle swarm optimization (MOPSO) is proposed to solve the problem. The performance of the proposed MOPSO is compared with that of a genetic algorithm and a random search algorithm. The results show that the MOPSO outperforms a well-known genetic algorithm for multi-objective optimization.
Intelligent Transportation Systems (ITS) is one of the keywords to describe smart cities, aiming at efficient public transport, smart parking, enhanced road safety, intelligent traffic management, onvehicle entertainment, and so on. In ITS, Roadside Unit (RSU) deployment should be well-designed due to it serves as a service provider and a gateway to the Internet for vehicular users. In this article, we propose an RSU deployment strategy which maximizes the communication coverage and reduces the energy consumption of RSUs, simultaneously. We first formulate a multi-objective optimization RSU deployment problem and solve it by an evolutionary algorithm. Then we conduct extensive simulations and simulation results demonstrate that our proposed strategy significantly improves both the energy efficiency and the network connectivity.
Intelligent Transportation Systems (ITS) is one of the keywords to describe smart cities, aiming at efficient public transport, smart parking, enhanced road safety, intelligent traffic management, onvehicle entertainment, and so on. In ITS, Roadside Unit (RSU) deployment should be well-designed due to it serves as a service provider and a gateway to the Internet for vehicular users. In this article, we propose an RSU deployment strategy which maximizes the communication coverage and reduces the energy consumption of RSUs, simultaneously. We first formulate a multi-objective optimization RSU deployment problem and solve it by an evolutionary algorithm. Then we conduct extensive simulations and simulation results demonstrate that our proposed strategy significantly improves both the energy efficiency and the network connectivity.
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