The Internet of Things (IoT) is expected to bring new opportunities for improving several services for the Society, from transportation to agriculture, from smart cities to fleet management. In this framework, massive connectivity represents one of the key issues. This is especially relevant when IoT systems are expected to cover a large geographical area or a region not reached by terrestrial network connections. In such scenarios, the usage of satellites might represent a viable solution for providing wide area coverage and connectivity in a flexible and affordable manner. Our paper presents a survey on current solutions for the deployment of IoT services in remote/rural areas by exploiting satellites. Several architectures and technical solutions are analyzed, underlining their features and limitations, and real test cases are presented. It has been highlighted that low-orbit satellites offer an efficient solution to support long-range IoT services, with a good trade-off in terms of coverage and latency. Moreover, open issues, new challenges, and innovative technologies have been focused, carefully considering the perimeter that current IoT standardization framework will impose to the practical implementation of future satellite based IoT systems.

In order to increase the penetration of electric vehicles, a network of fast charging stations that can provide drivers with a certain level of quality of service (QoS) is needed. However, given the strain that such a network can exert on the power grid, and the mobility of loads represented by electric vehicles, operating it efficiently is a challenging and complex problem. In this paper, we examine a network of charging stations equipped with an energy storage device and propose a scheme that allocates power to them from the grid, as well as routes customers. We examine three scenarios, gradually increasing their complexity. In the first one, all stations have identical charging capabilities and energy storage devices, draw constant power from the grid and no routing decisions of customers are considered. It represents the current state of affairs and serves as a baseline for evaluating the performance of the proposed scheme. In the second scenario, power to the stations is allocated in an optimal manner from the grid and in addition a certain percentage of customers can be routed to nearby stations. In the final scenario, optimal allocation of both power from the grid and customers to stations is considered. The three scenarios are evaluated using real traffic traces corresponding to weekday rush hour from a large metropolitan area in the US. The results indicate that the proposed scheme offers substantial improvements of performance compared to the current mode of operation; namely, more customers can be served with the same amount of power, thus enabling the station operators to increase their profitability. Further, the scheme provides guarantees to customers in terms of the probability of being blocked (and hence not served) by the closest charging station to their location. Overall, the paper addresses key issues related to the efficient operation, both from the perspective of the power grid and the drivers satisfaction, of a network of charging stations.

Cloud computing is an emerging paradigm that provides computing, communication and storage resources as a service over a network. Communication resources often become a bottleneck in service provisioning for many cloud applications. Therefore, data replication which brings data (e.g., databases) closer to data consumers (e.g., cloud applications) is seen as a promising solution. It allows minimizing network delays and bandwidth usage. In this paper we study data replication in cloud computing data centers. Unlike other approaches available in the literature, we consider both energy efficiency and bandwidth consumption of the system. This is in addition to the improved quality of service QoS obtained as a result of the reduced communication delays. The evaluation results, obtained from both mathematical model and extensive simulations, help to unveil performance and energy efficiency tradeoffs as well as guide the design of future data replication solutions.

The device-to-device (D2D) communication paradigm in 5G networks provides an effective infrastructure to enable different smart city applications such as public safety. In future smart cities, dense deployment of wireless sensor networks (WSNs) can be integrated with 5G networks using D2D communication. D2D communication enables direct communication between nearby user equipments (UEs) using cellular or ad hoc links, thereby improving the spectrum utilization, system throughput, and energy efficiency of the network. In this paper, we propose a hierarchal D2D communication architecture where a centralized software-defined network (SDN) controller communicates with the cloud head to reduce the number of requested long-term evolution (LTE) communication links, thereby improving energy consumption. The concept of local and central controller enables our architecture to work in case of infrastructure damage and hotspot traffic situation. The architecture helps to maintain the communication between disaster victims and first responders by installing multi-hop routing path with the support of the SDN controller. In addition, we highlight the robustness and potential of our architecture by presenting a public safety scenario, where a part of the network is offline due to extraordinary events such as disaster or terrorist attacks.

The research and development (R&D) and the standardization of the 5th Generation (5G) mobile networking technologies are proceeding at a rapid pace all around the world. In this paper, we introduce the emerging concept of network slicing that is considered one of the most significant technology challenges for 5G mobile networking infrastructure, summarize our preliminary research efforts to enable end-to-end network slicing for 5G mobile networking, and finally discuss application use cases that should drive the designs of the infrastructure of network slicing.

Smart cities take advantage of recent Information and Communication Technology (ICT) developments to provide added value to existing public services and improve quality of life for the citizens. The Internet of Things (IoT) paradigm makes the Internet more pervasive where objects equipped with computing, storage, and sensing capabilities are interconnected with communication technologies. Because of the widespread diffusion of IoT devices, applying the IoT paradigm to smart cities is an excellent solution to build sustainable ICT platforms. Having citizens involved in the process through mobile crowdsensing (MCS) techniques augments capabilities of these ICT platforms without additional costs. For proper operation, MCS systems require the contribution from a large number of participants. Simulations are therefore a candidate tool to assess the performance of MCS systems. In this paper, we illustrate the design of CrowdSenSim, a simulator for mobile crowdsensing. CrowdSenSim is designed specifically for realistic urban environments and smart cities services. We demonstrate the effectiveness of CrowdSenSim for the most popular MCS sensing paradigms (participatory and opportunistic), and we present its applicability using a smart public street lighting scenario.