Fog Computing is an emerging paradigm that extends Cloud Computing towards the edge of the network. In particular, Fog Computing refers to a distributed computing infrastructure confined on a limited geographical area within which some Internet of Things (IoT) applications/services run directly at the network edge on smart devices having computing, storage, and network connectivity, named Fog Nodes, with the goal of improving efficiency and reducing the amount of data that needs to be sent to the Cloud for massive data processing, analysis and storage. This paper proposes an efficient strategy to offload computationally intensive tasks from end-user devices to Fog Nodes. The computation offload problem is formulated here as a matching game with externalities, with the aim of minimizing the worst case service time by taking into account both computational and communications costs. In particular, this paper proposes a strategy based on the deferred acceptance algorithm to achieve the efficient allocation in a distributed mode and ensuring stability over the matching outcome. The performance of the proposed method is evaluated by resorting to computer simulations in terms of worst total completion time, mean waiting and mean total completion time per task. Moreover, with the aim of highlighting the advantages of the proposed method, performance comparisons with different alternatives are also presented and critically discussed. Finally, a fairness analysis of the proposed allocation strategy is also provided on the basis of the evaluation of the Jain’s index.

Wireless communications have received much attention during the last decades due to easy implementation, the possibility of delivering multimedia services to rural communities, and the suitability for public safety and for communicating in emergency situations. In particular, a wireless network designed for an emergency scenario must be capable of monitoring sensitive areas and must enable people to connect immediately after a disaster. This article discusses the main features of a wireless network that aims to interconnect several heterogeneous systems and provide multimedia access to groups of people to better monitor a specific area, to have a fast response in case of a disaster, and to efficiently coordinate all of the forces during the disaster management phase.

Video service delivery over 3GPP Long Term Evolution-Advanced (LTE-A) networks is gaining momentum with the adoption of the evolved Multimedia Broadcast Multicast Service (eMBMS). In this paper, we address the challenge of optimizing the radio resource allocation process so that heterogeneous groups of users, according to their propagation conditions, can receive layered video streams at predefined and progressively decreasing service levels matched to respective user groups. A key aspect of the proposed system model is that video streams are delivered as eMBMS flows that utilize the random linear network coding (NC) principle. Furthermore, the transmission rate and NC scheme of each eMBMS flow are jointly optimized. The simulation results show that the proposed strategy can exploit user heterogeneity to optimize the allocated radio resources while achieving desired service levels for different user groups.

Space communications is an ideal candidate to handle critical and emergency situations arising on a regional to global scale, provided there is effective integration among them. The article presents a review of solutions offered by space communication systems for early warning and emergency communication services. It includes an up-to-date review of public research and standardization activity in the field, with a specific focus on mass alert. The main technical issues and challenges are also discussed along with the cutting-edge research from the scientific community.

Recently, quantum computing and communications rapidly developed to interconnect heterogeneous quantum devices. In particular, some researchers have been performed about terrestrial quantum communications over typical optical fiber links. However, this technology is affected by extremely high losses that can be faced only through the deployment of several repeaters, which in turn involve impractical costs for end-to-end (E2E) route management. Quantum Satellite Networks (QSNs) can overcome the limitations of terrestrial optical networks, such as a remarkable signal attenuation over long distances and difficulty of intercontinental communications. The recent studies on quantum satellite communications motivated our research towards a Low Earth Orbit (LEO) quantum satellite backbone for interconnecting quantum on Earth Servers in order to achieve an unprecedented computational capacity. Specifically, our paper proposes a near optimum E2E path evaluation procedure allowing an efficient switching in order to maximize the entanglement generation rate. Indeed, this is one of the main issues that involve the Data Link Layer and the Network Layer of the Quantum Internet (QI) protocol stack, which is in its early standardization phase. In particular, the design of our approach is based on the Software-Defined Networking (SDN) paradigm with the aim of minimizing the number of hops for E2E connection and maximizing network capacity. Therefore, we compare distributed and centralized approaches in order to achieve a trade-off between performance and cost.