Joint Optimization of Transmission and Computation Resources for Satellite and High Altitude Platform Assisted Edge Computing

Ding, Changfeng; Wang, Jun-Bo; Zhang, Hua; Lin, Min; Li, Geoffrey Ye

doi:10.1109/twc.2021.3103764

Cited by 72 publications

(30 citation statements)

References 41 publications

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“…As we are passing 5G and soon entering 6G and beyond, HAPS can be of invisible treasure as it can be used for computation offloading [22], edge computing [23], even base station [24] to meet human needs. HAPS can be another type of ranging source which is quasi-stationary and much closer to the ground of the Earth.…”

Section: Discussionmentioning

confidence: 99%

High Altitude Platform Station (HAPS)-Aided GNSS for Urban Areas

Zheng

Atia

Yanıkömeroğlu

2022

2022 IEEE International Conference on Wireless for Space and Extreme Environments (WiSEE)

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Today the global averaged civilian positioning accuracy is still at meter level for all existing Global Navigation Satellite Systems (GNSSs), and the civilian positioning performance is even worse in regions such as the Arctic region and the urban areas. In this work, we examine the positioning performance of the High Altitude Platform Station (HAPS)aided GPS system in an urban area via both simulation and physical experiment. HAPS can support GNSS in many ways, herein we treat the HAPS as an additional ranging source. From both simulation and experiment results, we can observe that HAPS can improve the horizontal dilution of precision (HDOP) and the 3D positioning accuracy. The simulated positioning performance of the HAPS-aided GPS system is subject to the estimation accuracy of the receiver clock offset. This work also presents the future work and challenges in modelling the pseudorange of HAPS.

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Section: Discussionmentioning

confidence: 99%

High Altitude Platform Station (HAPS)-Aided GNSS for Urban Areas

Zheng

Atia

Yanıkömeroğlu

2022

2022 IEEE International Conference on Wireless for Space and Extreme Environments (WiSEE)

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“…In addition to them, several studies have been performed to optimize both the communication and computing resources for minimizing energy consumption or task-completion latency under various system models. Due to the deep penetration of unmanned systems in communication architectures recently, there have been research trend to mount the computing capability to the unmanned vehicles such as high-altitude platform [6], [7] and low-earth orbital (LEO) satellite [8], and solve various optimization problem [9], [10]. Particularly, Tun et al [9] considered the unmanned aerial vehicle (UAV)-assisted scenario and jointly optimized task offloading decision, resource allocation, and UAV trajectory while considering the communication and computation latency requirements.…”

Section: Related Workmentioning

confidence: 99%

On Offloading Decision for Mobile Edge Computing Systems Considering Access Reservation Protocol

Kim

Adu

et al. 2023

IEEE Access

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For several years, mobile edge computing (MEC) has been highlighted as a promising technique to support emerging computation-intensive applications in cellular networks, e.g., 5G and 6G. Most previous studies have mainly focused on jointly optimizing communication (i.e., radio) and computation resources to improve offloading performance without considering specific communication protocols required for operating the MEC systems in practice. In this article, we newly design a contention-based access reservation protocol (ARP) for efficiently supporting simultaneous task offloading requests from a number of edge devices (EDs), and further define necessary signalings required to determine an optimal offloading factor. Thereafter, we formulate an optimization problem to find the optimal offloading factor that minimizes the task-completion latency. Through simulations, we mainly evaluate the task-completion latency performance of the MEC system incorporated with our proposed access reservation protocol under a multiple-input multiple-output (MIMO) environment. Particularly, we thoroughly investigate several practical aspects such as the effect of the number of edge devices attempting to join the task offloading, the number of antennas equipped at the edge device, and the amount of reserved radio resources required for configuring access reservation protocol on the optimal offloading decision. From the results, we verify the validity of our approach, and provide meaningful insights regarding how the network should be configured to fruitfully exploit the offloading with the MEC systems. INDEX TERMSMobile edge computing, Computation offloading, Offloading decision, Access reservation protocol, Multiple-input multiple-output VOLUME 4, 2021

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“…In these works, satellites are not connected with each other. The work in [39] and [40] investigated the joint computation assignment and resource allocation problem in multi-tier computing architectures composed of mobile devices, LEO satellites, etc. Authors in [41] and [42] proposed hybrid computation offloading architectures to solve the joint computation and resource allocation problem, where computing tasks could be offloaded to both ground servers and visible LEO satellites.…”

Section: B Computing and Transmission Joint Optimizationmentioning

confidence: 99%