scholarly journals Complexity-Performance Trade-offs in Robust Access Point Clustering for Edge Computing

2021 ◽  
Author(s):  
Nour-El-Houda Yellas ◽  
Selma Boumerdassi ◽  
Alberto Ceselli ◽  
Stefano Secci
Keyword(s):  
Access Point ◽  
Edge Computing ◽  
Trade Offs

scholarly journals Joint optimization of network selection and task offloading for vehicular edge computing

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Lujie Tang ◽  
Bing Tang ◽  
Li Zhang ◽  
Feiyan Guo ◽  
Haiwu He
Keyword(s):  
Large Scale ◽  
Vehicular Networks ◽  
Access Point ◽  
Edge Computing ◽  
Network Selection ◽  
Network Access ◽  
Task Execution ◽  
Point Selection ◽  
Vehicle Movement ◽  
Task Offloading

AbstractTaking the mobile edge computing paradigm as an effective supplement to the vehicular networks can enable vehicles to obtain network resources and computing capability nearby, and meet the current large-scale increase in vehicular service requirements. However, the congestion of wireless networks and insufficient computing resources of edge servers caused by the strong mobility of vehicles and the offloading of a large number of tasks make it difficult to provide users with good quality of service. In existing work, the influence of network access point selection on task execution latency was often not considered. In this paper, a pre-allocation algorithm for vehicle tasks is proposed to solve the problem of service interruption caused by vehicle movement and the limited edge coverage. Then, a system model is utilized to comprehensively consider the vehicle movement characteristics, access point resource utilization, and edge server workloads, so as to characterize the overall latency of vehicle task offloading execution. Furthermore, an adaptive task offloading strategy for automatic and efficient network selection, task offloading decisions in vehicular edge computing is implemented. Experimental results show that the proposed method significantly improves the overall task execution performance and reduces the time overhead of task offloading.

scholarly journals A Data-driven Platform for Simulating Vehicular Fog Computing Environment

2022 ◽  
Author(s):  
Ozgur Umut Akgul ◽  
Wencan Mao ◽  
Byungjin Cho ◽  
Yu Xiao
Keyword(s):  
Capacity Planning ◽  
Fog Computing ◽  
Deep Understanding ◽  
Temporal Variations ◽  
Edge Computing ◽  
Business Strategies ◽  
Open Platform ◽  
Trade Offs ◽  
Spatio Temporal ◽  
Computing Capacity

<div>Edge/fog computing is a key enabling technology in 5G and beyond for fulfilling the tight latency requirements of compute-intensive vehicular applications such as cooperative driving. Concerning the spatio-temporal variation in the vehicular traffic flows and the demand for edge computing capacity generated by connected vehicles, vehicular fog computing (VFC) has been proposed as a cost-efficient deployment model that complements stationary fog nodes with mobile ones carried by moving vehicles. Accessing the feasibility and the applicability of such hybrid topology, and further planning and managing the networking and computing resources at the edge, require deep understanding of the spatio-temporal variations in the demand and the supply of edge computing capacity as well as the trade-offs between achievable Quality-of-Services and potential deployment and operating costs. To meet such requirements, we propose in this paper an open platform for simulating the VFC environment and for evaluating the performance and cost efficiency of capacity planning and resource allocation strategies under diverse physical conditions and business strategies. Compared with the existing edge/fog computing simulators, our platform supports the mobility of fog nodes and provides a realistic modeling of vehicular networking with the 5G and beyond network in the urban environment. We demonstrate the functionality of the platform using city-scale VFC capacity planning as example. The simulation results provide insights on the feasibility of different deployment strategies from both technical and financial perspectives.</div>

scholarly journals Wireless Powered Mobile Edge Computing Systems: Simultaneous Time Allocation and Offloading Policies

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 965
Author(s):  
Amna Irshad ◽  
Ziaul Haq Abbas ◽  
Zaiwar Ali ◽  
Ghulam Abbas ◽  
Thar Baker ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Time Allocation ◽  
Minimum Cost ◽  
Access Point ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Computational Power ◽  
Local Computation ◽  
Computing Systems ◽  
Battery Capacity

To improve the computational power and limited battery capacity of mobile devices (MDs), wireless powered mobile edge computing (MEC) systems are gaining much importance. In this paper, we consider a wireless powered MEC system composed of one MD and a hybrid access point (HAP) attached to MEC. Our objective is to achieve a joint time allocation and offloading policy simultaneously. We propose a cost function that considers both the energy consumption and the time delay of an MD. The proposed algorithm, joint time allocation and offload policy (JTAOP), is used to train a neural network for reducing the complexity of our algorithm that depends on the resolution of time and the number of components in a task. The numerical results are compared with three benchmark schemes, namely, total local computation, total offloading and partial offloading. Simulations show that the proposed algorithm performs better in producing the minimum cost and energy consumption as compared to the considered benchmark schemes.

scholarly journals Edge and Fog Computing in Healthcare – A Review

2019 ◽  
Vol 20 (2) ◽  
pp. 191-206 ◽  
Author(s):  
Sujata Dash ◽  
Sitanath Biswas ◽  
Debajit Banerjee ◽  
Atta UR Rahman
Keyword(s):  
Healthcare System ◽  
Fog Computing ◽  
Edge Computing ◽  
Wireless Devices ◽  
Privacy Concerns ◽  
Health Care Informatics ◽  
Trade Offs ◽  
Architectural Framework ◽  
Edge And Fog Computing ◽  
Care Informatics

The architectural framework of Fog and edge computing reveals that the network components which lie between the cloud and devices computes application oriented operations. In this paper, an in-depth review of fog and mist computing in the area of health care informatics is analyzed, classified, and discussed various applications cited in the literature. For that purpose, applications are classified into different categories and a list of application-oriented tasks that can be handled by fog and edge computing are enlisted. It is further added that on which layer of the network system such fog and edge computing tasks can be computed and trade-offs with respect to requirements relevant to healthcare are provided. The review undertaken in this paper focuses on three important areas: firstly, the enormous amount of computing tasks of healthcare system can take mileage of these two computing principles; secondly, the limitation of wireless devices can be overcome by having higher network tiers which can execute tasks and aggregate the data; and thirdly, privacy concerns and dependability prevent computation tasks to completely move to the cloud. Another area which has been considered in the study is how Edge and Fog computing can make the security algorithms more efficient. The findings of the study provide evidence of the need for a logical and consistent approach towards fog and mist computing in healthcare system.

scholarly journals A Data-driven Platform for Simulating Vehicular Fog Computing Environment

2022 ◽  
Author(s):  
Ozgur Umut Akgul ◽  
Wencan Mao ◽  
Byungjin Cho ◽  
Yu Xiao
Keyword(s):  
Capacity Planning ◽  
Fog Computing ◽  
Deep Understanding ◽  
Temporal Variations ◽  
Edge Computing ◽  
Business Strategies ◽  
Open Platform ◽  
Trade Offs ◽  
Spatio Temporal ◽  
Computing Capacity

<div>Edge/fog computing is a key enabling technology in 5G and beyond for fulfilling the tight latency requirements of compute-intensive vehicular applications such as cooperative driving. Concerning the spatio-temporal variation in the vehicular traffic flows and the demand for edge computing capacity generated by connected vehicles, vehicular fog computing (VFC) has been proposed as a cost-efficient deployment model that complements stationary fog nodes with mobile ones carried by moving vehicles. Accessing the feasibility and the applicability of such hybrid topology, and further planning and managing the networking and computing resources at the edge, require deep understanding of the spatio-temporal variations in the demand and the supply of edge computing capacity as well as the trade-offs between achievable Quality-of-Services and potential deployment and operating costs. To meet such requirements, we propose in this paper an open platform for simulating the VFC environment and for evaluating the performance and cost efficiency of capacity planning and resource allocation strategies under diverse physical conditions and business strategies. Compared with the existing edge/fog computing simulators, our platform supports the mobility of fog nodes and provides a realistic modeling of vehicular networking with the 5G and beyond network in the urban environment. We demonstrate the functionality of the platform using city-scale VFC capacity planning as example. The simulation results provide insights on the feasibility of different deployment strategies from both technical and financial perspectives.</div>

scholarly journals Opportunistic Access Point Selection for Mobile Edge Computing Networks

2020 ◽  
pp. 1-1 ◽  
Author(s):  
Junjuan Xia ◽  
Lisheng Fan ◽  
Nan Yang ◽  
Yansha Deng ◽  
Trung Q. Duong ◽  
...  
Keyword(s):  
Access Point ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Point Selection ◽  
Opportunistic Access ◽  
Selection For

scholarly journals On-Body Edge Computing Through E-Textile Programmable Logic Array

2021 ◽  
Vol 2 ◽  
Author(s):  
Frances Cleary ◽  
David C. Henshall ◽  
Sasitharan Balasubramaniam
Keyword(s):  
Health Monitoring ◽  
Data Privacy ◽  
Access Point ◽  
The Body ◽  
Edge Computing ◽  
Programmable Logic ◽  
Remote Health Monitoring ◽  
New Form ◽  
Smart Garments ◽  
Remote Health

E-textiles have received tremendous attention in recent years due to the capability of integrating sensors into a garment, enabling high-precision sensing of the human body. Besides sensing, a number of solutions for e-textile garments have also integrated wireless interfaces, allowing sensing data to be transmitted, and also inbuilt capacitive touch sensors, allowing users to provide instructions. While this has provided a new level of sensing that can result in unprecedented applications, there has been little attention placed around on-body edge computing for e-textiles. This study focuses on the need for a noninvasive and remote health-monitoring solution with inbuilt on-body edge computing, and how enabling such sensing and computing capabilities in a fabric environment can act as a new method for healthcare monitoring through the use of embedded computing intelligence in smart garments. Facilitating computing in e-textiles can result in a new form of on-body edge computing, where sensor information is processed very close to the body before being transmitted to an external device or wireless access point. This form of computing can provide new security and data privacy capabilities and, at the same time, provide opportunities for new energy-harvesting mechanisms to process the data through the garment. This study proposes this concept through embroidered programmable logic arrays (PLAs) integrated into e-textiles. In the same way that PLAs have programmable logic circuits by interconnecting different AND, NOT, and OR gates, we propose e-textile–based gates that are sewn into a garment and connected through conductive thread stitching. Two designs are proposed, and this includes single- and multi-layered PLAs. Experimental validations have been conducted at the individual gates and the entire PLA circuits to determine the voltage utilization and logic computing reliability. The multilayered PLA garment superseded the single-layered garment with higher levels of accuracy in the yielded results due to the enhanced design layout, which reduces the potential for short circuits and errors occurring. Our proposed approach can usher in a new form of on-body edge computing for e-textile garments for future wearable technologies, and, in particular, with the current pandemic that requires noninvasive remote health-monitoring applications.

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