Abstract
The paradigm of Internet of Things (IoT) is transforming physical environments into smart and interactive platforms to offer a wide range of innovative services supported by the evolution towards 5G networks. A major class of emerging services relies on highly intensive computations to make real-time decisions with ultra-low latency. Edge computing has been established as an effective approach to reduce the latency overhead of cloud computing and effectively augment the computational capabilities of IoT devices. In this work, we leverage the mobility and agility of Unmanned Aerial Vehicles (UAVs) as mobile edge servers or cloudlets to offer computation offloading opportunities to IoT devices. In particular, we consider the joint problem of optimizing the number and positions of deployed UAV cloudlets in 3D space and task offloading decisions with cooperation among UAVs, in order to provision IoT services with strict latency requirements. We formulate the problem as a mixed integer program, and propose an efficient meta-heuristic solution based on the ions motion optimization algorithm. The performance of the meta-heuristic solution is evaluated and compared to the optimal solution as a function of various system parameters and for different application use cases. It is shown to achieve near-optimal performance with low complexity and, thus, can efficiently scale up to large IoT network scenarios.
Highlights
The development of 5G networks has fostered the advancement of numerous applications including augmented reality, autonomous driving, and remote operation systems
In case Internet of Things (IoT) device i offloads its tasks to one of the Unmanned Aerial Vehicles (UAVs), the incurred delay comprises the time tup,ij to upload the data to the home UAV j, the time tU2U,jk to deliver the task from the home UAV j to the cloudlet UAV k, the time tprocess,ik to fully process the task at the cloudlet UAV k, and the time tdown,ij to deliver the result back to the IoT device through the home UAV j
In this work, we leveraged the flexibility, enhanced line of sight connectivity, and low cost of UAVs to deploy them as mobile edge computing cloudlets to serve resource-constrained IoT devices
Summary
The development of 5G networks has fostered the advancement of numerous applications including augmented reality, autonomous driving, and remote operation systems. They formulated the problem to minimize the utilized power by the IoT devices and proposed an efficient heuristic algorithm to solve the optimization problem based on an iterative approach. In contrast to the related work, this paper presents a novel UAV-enabled edge computing solution for IoT networks by jointly optimizing the number of deployed UAVs, their positions in 3D space, the device-to-UAV associations, and the computation offloading decisions. We study the optimal 3D deployment of UAV-mounted cloudlets to support latency-sensitive IoT applications while considering a set of constraints related to the computational tasks, available resources, and quality of service targets. Each IoT device i requires its tasks to be fulfilled before a time limit Ti
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