## 2 Related Work
### Multiple Edge Servers and Remote Cloud  
[PERSON] et al. [19] proposed an energy-efficient edge-cloud framework for computation offloading of a multi-UAV system. They formulated an optimization problem as a three-layer game in which the offloading decision could be determined in a decentralized way. In addition, efficient decentralized algorithms are developed in which the performance of the game is analyzed through its efficiency ratio and the Nash equilibrium can be achieved. Finally, experimental results demonstrate that these algorithms can dramatically decrease the consumption of energy by 30% with less than 10% performance loss compared with other benchmark solutions. [PERSON] et al. [24] presented an energy-efficient cloud-assisted edge computing framework for collaborative task computation offloading in IoT sensors. This framework was composed of a three-tier network with IoT sensors in the first tier and the edge server and the cloud server in the other two tiers. In addition, an offloading strategy was formulated as a mixed-integer problem in which minimizing the energy consumption of IoT sensors was the main goal. Furthermore, a semi-definite relaxation-based energy-efficient collaborative task offloading algorithm was developed to solve this problem and to obtain the optimum decision of offloading. Finally, the simulation results showed that this algorithm can outperform the existing algorithm in terms of energy consumption. In addition, it can efficiently adapt to different system parameters. The standard MEC structure with fixed nodes is not able to satisfy the needs of users for computing resources and connections with rapidly changing characteristics of time, space, and spectrum. To solve this problem, ref. [31] discusses the use of an air-to-ground MEC-integrated environment, consisting of the deployment of UAVs and ground vehicles as additional edge nodes. The UAVs make it possible to ensure coverage of the network in complex geographical areas, and provide a wider selection of services. The proposed network consists of three levels: the level of cloud computing, the level of edge computing, and the level of devices. The integrated structure basically assumes the use of the main advantages provided by software-defined networking: centralization of control, separation of user data from control data, and a large abstraction of basic structures. The hypervisor in this network is responsible for the virtualization of the resources of user devices, as well as for the computing and storage resources of the upper level (relative to the device level). Variants of the proposed network structure correspond to the main scenarios in networks: support for ultra-low latency--URLLC, distributed processing and analysis of big data along with the caching of content and delivery to mobile devices--eMBB, and scalable arrays and mobile communications management--mMTC. The benefits provided by the structure include adaptive resource allocation, differentiated QoS guarantees, enhanced connectivity between network nodes, and efficient mobility management. The delay in transferring data from mobile devices to a remote computing cloud has a large load value in existing traffic offloading systems. To solve this problem, ref. [32] developed code for a traffic offloading system oriented to the network edge called Echo. The network structure for the Echo code consists of three levels: mobile devices, border, and cloud. Echo uses a centralized mechanism in which the decision to offload traffic is carried out at the edge nodes. The code for unloading traffic is implemented on Android devices. Echo solves the problem of which method and which platform are used--the cloud platform or the border. For more efficient use of the resources of the edge nodes, the Preemption-Constrained Shortest-Remaining Time-First (PC-SRTF) scheduling algorithm is used to minimize the average time for solving the problem. The proposed code provides a guarantee of the quality of service when unloading traffic at border nodes.