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The deployment of a swarm of cooperative Unmanned Aerial Vehicles (UAVs) to pursue a mission is knowing an increasing success nowadays. This is mainly because deploying a group of cooperating UAVs instead of one single UAV offers numerous advantages, including the extension of the mission coverage, fault tolerance in case of losing a UAV during a mission, and improving the data gathering accuracy. Multicast routing, on the other hand, is a critical operation for UAV swarm networks, as it facilitates critical tasks including information transmission and swarm coordination. Moreover, designing efficient multicast protocols with Quality of Service (QoS) can be challenging due to various factors such as limited energy constraints and the dynamically changing topology with 3D movement which causes frequent changes in the network topology. Therefore, in this paper, we investigate the multicast routing problem in a swarm of UAVs. We first provide a detailed classification of existing efforts in swarm routing protocols in terms of transmission strategies. And second, we propose a new Energy Efficient Inter-UAV Multicast Routing Protocol for surveillance and monitoring applications called "COCOMA". We illustrate through extensive simulations that COCOMA achieves the desired efficient communication backbone and Quality-of-Service. We also discuss and implement an improvement of COCOMA called COCOMA+ and show that both versions are efficient and effective in term of reducing the total emission energy by at least 10 dBm compared to the state-of-art work SP-GMRF. In addition, our proposal optimizes also the End-to-End Delay, the number of hops in the routing process, and the network throughput which consequently leads to increasing the packet delivery ratio by more than to 22% compared to SP-GMRF protocol. [ABSTRACT FROM AUTHOR]

Nowadays, Multi-access Edge Computing (MEC) and Internet of Flying Things (IoFT) clouds are attracting significant attention from both academic and industrial research sectors as a new paradigm for providing flexible and elastic services. This new paradigm utilizes the recent technologies of Cloud Computing (CC) and Internet of things (IoT). The conjunctive application of these new technologies engenders an impressive vision of the future in which everything is connected to the Internet via Fifth Generation (5G) technology that integrates the MEC server; this will provide instant computing applications with low latency and fast service response. In the present study, we propose a Game Theory approach for Cloud Services in MEC- and UAV-enabled networks (GTCS) that enables a normal end user to select the most suitable Unmanned Aerial Vehicle (UAV)-Service-Provider based on a set of specific features, limitations, and prices. Given that every service provider has specific features, limitations, and prices, users must select the most suitable provider. A technique based on Game Theory (GT) is used to select the optimum provider by considering user requirements and UAV provider qualities. Simulation results obtained using the OMNet++ simulator and Inet framework evidence the efficiency and good performance of our method, which presents a low latency of 0.45 s at maximum between the two scenarios, a high successful execution ratio that reaches 100% with 50 Unmanned Aerial Vehicles (UAVs), and good management of energy consumption with only 14.5% energy loss in the worst case. [ABSTRACT FROM AUTHOR]