Abstract
Mobile edge computing (MEC) enhanced satellite based internet of things (SAT-IoT) is an important complement for terrestrial networks based IoT, especially for the remote and depopulated areas. For MEC enhanced SAT-IoT networks with multiple satellites and multiple satellite gateways, the coupled user association, offloading decision, computing and communication resource allocation should be jointly optimized to minimize the latency and energy cost. In this paper, the latency and energy optimization for MEC enhanced SAT-IoT networks are formulated as a dynamic mixed-integer programming problem, which is hard to obtain the optimal solutions. To tackle this problem, we decompose the complex problem into two sub-problems. The first one is computing and communication resource allocation with fixed user association and offloading decision, and the second one is joint user association and offloading with optimal resource allocation. For the sub-problem of resource allocation, the optimal solution is proven to be obtained based on Lagrange multiplier method. And then, the second sub-problem is further formulated as a Markov decision process (MDP), and a joint user association and offloading decision with optimal resource allocation (JUAOD-ORA) is proposed based on deep reinforcement learning (DRL). Simulation results show that the proposed approach can achieve better long-term reward in terms of latency and energy cost.
Highlights
Internet of things (IoT) plays an important role in future intelligent networks
AND SCOPE In this paper, we focus on the Mobile edge computing (MEC) enhanced satellite based internet of things (SAT-IoT) networks with multiple satellites and multiple satellite gateways
We present a framework for latency and energy optimization in MEC enhanced SAT-IoT networks with multiple satellites and multiple satellite gateways
Summary
Internet of things (IoT) plays an important role in future intelligent networks. To provide reliable connection and high-quality service for massive devices in IoT, the fifth generation (5G) wireless networks treat massive connection as an indispensable component and devote many efforts to make it satisfy the requirements of tremendous emerging services [1]. The MEC enhanced SAT-IoT will make the resource management more complicate, and several issues such as user association, offloading decision, computing and communication resource allocation should be considered cooperatively to improve the network energy efficiency and reduce latency. The admission control, computational resource allocation and power control are jointly optimized for MEC enhanced IoT networks in [24], the joint computation offloading and user association for multi-tasks MEC systems is investigated in [25] to minimize overall energy consumption. The existing works ignore the joint optimization of user association, offloading decision, computing and communication resource allocation for MEC enhanced SAT-IoT networks. To minimize the weighted-sum latency of all of tasks and energy cost, every task needs to be handled by jointly optimizing user association, offloading decision, computing and communication resource allocation. According to (1)-(3), the Teff is related to the user association, offloading decision, available resource and resource allocation at each time slot
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
