scholarly journals Resource Scheduling Based on Reinforcement Learning Based on Federated Learning

2021 ◽  
pp. 39-45
Author(s):  
Yabin Wang ◽  
◽  
Jing Yu
Keyword(s):  
Reinforcement Learning ◽  
Edge Computing ◽  
New Model ◽  
Learning Agents ◽  
Edge Node ◽  
Experiment Method ◽  
Iot Devices ◽  
The Internet Of Things

The emergence of edge computing makes up for the limited capacity of devices. By migrating intensive computing tasks from them to edge nodes (EN), we can save more energy while still maintaining the quality of service.Computing offload decision involves collaboration and complex resource management. It should be determined in real time according to dynamic workload and network environment. The simulation experiment method is used to maximize the long-term utility by deploying deep reinforcement learning agents on IOT devices and edge nodes, and the alliance learning is introduced to distribute the deep reinforcement learning agents. First, build the Internet of things system supporting edge computing, download the existing model from the edge node for training, and unload the intensive computing task to the edge node for training; upload the updated parameters to the edge node, and the edge node aggregates the parameters with the The model at the edge nodecan get a new model; the cloud can get a new model at the edge node and aggregate, and can also get updated parameters from the edge node to apply to the device.

scholarly journals Survei IoT Healthcare Device

2020 ◽  
Vol 3 (2) ◽  
pp. 153-164
Author(s):  
Yulia Suryandari
Keyword(s):  
Health Sector ◽  
Healthcare Services ◽  
Value Of Life ◽  
Healthcare Sector ◽  
Health Care Technology ◽  
Iot Devices ◽  
Care Technology ◽  
Industry Trends ◽  
The Internet Of Things

The Internet of Things (IoT) has enormous potential in creating the value of life related to technology. IoT has various application domains, including in the health sector. IoT-based healthcare services are expected to reduce costs, improve quality of life, and enrich user experience. The presence of IoT devices for healthcare services can also avoid unnecessary hospitalization and ensure that patients who need health services get it quickly. This paper surveys advances in IoT-based health care technology and reviews the latest architectures / platforms, platforms, applications and industry trends in IoT-based healthcare solutions. Some IoT devices and prototypes in the healthcare field are also discussed in this paper. Through this paper, it is expected that readers can be known and discuss IoT devices in the healthcare sector.

Bridging the IoT Gap Through Edge Computing

2019 ◽  
pp. 1-9
Author(s):  
R. I. Minu ◽  
G. Nagarajan
Keyword(s):  
Internet Of Things ◽  
Information Needs ◽  
Edge Computing ◽  
The Internet ◽  
Cloud Server ◽  
The Cost ◽  
The Internet Of Things ◽  
Clear Objective ◽  
Origin Point

In the present-day scenario, computing is migrating from the on-premises server to the cloud server and now, progressively from the cloud to Edge server where the data is gathered from the origin point. So, the clear objective is to support the execution and unwavering quality of applications and benefits, and decrease the cost of running them, by shortening the separation information needs to travel, subsequently alleviating transmission capacity and inactivity issues. This chapter provides an insight of how the internet of things (IoT) connects with edge computing.

scholarly journals Decentralized and Dynamic Band Selection in Uplink Enhanced Licensed-Assisted Access: Deep Reinforcement Learning Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Fitsum Debebe Tilahun ◽  
Chung G. Kang
Keyword(s):  
Reinforcement Learning ◽  
Resource Utilization ◽  
Base Station ◽  
Band Selection ◽  
Selection Strategy ◽  
Operational Mode ◽  
Selection Scheme ◽  
Aggregation Technology

Enhanced licensed-assisted access (eLAA) is an operational mode that allows the use of unlicensed band to support long-term evolution (LTE) service via carrier aggregation technology. The extension of additional bandwidth is beneficial to meet the demands of the growing mobile traffic. In the uplink eLAA, which is prone to unexpected interference from WiFi access points, resource scheduling by the base station, and then performing a listen before talk (LBT) mechanism by the users can seriously affect the resource utilization. In this paper, we present a decentralized deep reinforcement learning (DRL)-based approach in which each user independently learns dynamic band selection strategy that maximizes its own rate. Through extensive simulations, we show that the proposed DRL-based band selection scheme improves resource utilization while supporting certain minimum quality of service (QoS).

scholarly journals IoT and UAV Integration in 5G Hybrid Terrestrial-Satellite Networks

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3704 ◽  
Author(s):  
Mario Marchese ◽  
Aya Moheddine ◽  
Fabio Patrone
Keyword(s):  
Mobile Communications ◽  
Satellite Networks ◽  
Use Cases ◽  
Fifth Generation ◽  
Smart Agriculture ◽  
Iot Devices ◽  
Terrestrial Network ◽  
Scalable Network ◽  
The Internet Of Things

The Fifth Generation of Mobile Communications (5G) will lead to the growth of use cases demanding higher capacity and a enhanced data rate, a lower latency, and a more flexible and scalable network able to offer better user Quality of Experience (QoE). The Internet of Things (IoT) is one of these use cases. It has been spreading in the recent past few years, and it covers a wider range of possible application scenarios, such as smart city, smart factory, and smart agriculture, among many others. However, the limitations of the terrestrial network hinder the deployment of IoT devices and services. Besides, the existence of a plethora of different solutions (short vs. long range, commercialized vs. standardized, etc.), each of them based on different communication protocols and, in some cases, on different access infrastructures, makes the integration among them and with the upcoming 5G infrastructure more difficult. This paper discusses the huge set of IoT solutions available or still under standardization that will need to be integrated in the 5G framework. UAVs and satellites will be proposed as possible solutions to ease this integration, overcoming the limitations of the terrestrial infrastructure, such as the limited covered areas and the densification of the number of IoT devices per square kilometer.

scholarly journals Satellite Edge Computing for the Internet of Things in Aerospace

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4375 ◽  
Author(s):  
Yuxuan Wang ◽  
Jun Yang ◽  
Xiye Guo ◽  
Zhi Qu
Keyword(s):  
Internet Of Things ◽  
Computing System ◽  
Edge Computing ◽  
The Internet ◽  
New Paradigm ◽  
Long Distance ◽  
Modeling Analysis ◽  
Iot Devices ◽  
Terrestrial Network ◽  
The Internet Of Things

As one of the information industry’s future development directions, the Internet of Things (IoT) has been widely used. In order to reduce the pressure on the network caused by the long distance between the processing platform and the terminal, edge computing provides a new paradigm for IoT applications. In many scenarios, the IoT devices are distributed in remote areas or extreme terrain and cannot be accessed directly through the terrestrial network, and data transmission can only be achieved via satellite. However, traditional satellites are highly customized, and on-board resources are designed for specific applications rather than universal computing. Therefore, we propose to transform the traditional satellite into a space edge computing node. It can dynamically load software in orbit, flexibly share on-board resources, and provide services coordinated with the cloud. The corresponding hardware structure and software architecture of the satellite is presented. Through the modeling analysis and simulation experiments of the application scenarios, the results show that the space edge computing system takes less time and consumes less energy than the traditional satellite constellation. The quality of service is mainly related to the number of satellites, satellite performance, and task offloading strategy.

scholarly journals Moving to the Edge-Cloud-of-Things: Recent Advances and Future Research Directions

Electronics ◽  
2018 ◽  
Vol 7 (11) ◽  
pp. 309 ◽  
Author(s):  
Hind Bangui ◽  
Said Rakrak ◽  
Said Raghay ◽  
Barbora Buhnova
Keyword(s):  
Cloud Computing ◽  
Leading Edge ◽  
Cloud Services ◽  
Future Research ◽  
Research Directions ◽  
Iot Applications ◽  
Future Research Directions ◽  
Iot Devices ◽  
The Internet Of Things

Cloud computing has significantly enhanced the growth of the Internet of Things (IoT) by ensuring and supporting the Quality of Service (QoS) of IoT applications. However, cloud services are still far from IoT devices. Notably, the transmission of IoT data experiences network issues, such as high latency. In this case, the cloud platforms cannot satisfy the IoT applications that require real-time response. Yet, the location of cloud services is one of the challenges encountered in the evolution of the IoT paradigm. Recently, edge cloud computing has been proposed to bring cloud services closer to the IoT end-users, becoming a promising paradigm whose pitfalls and challenges are not yet well understood. This paper aims at presenting the leading-edge computing concerning the movement of services from centralized cloud platforms to decentralized platforms, and examines the issues and challenges introduced by these highly distributed environments, to support engineers and researchers who might benefit from this transition.

scholarly journals EdgeX over Kubernetes: Enabling Container Orchestration in EdgeX

2021 ◽  
Vol 12 (1) ◽  
pp. 140
Author(s):  
Seunghwan Lee ◽  
Linh-An Phan ◽  
Dae-Heon Park ◽  
Sehan Kim ◽  
Taehong Kim
Keyword(s):  
Edge Computing ◽  
Computing Platform ◽  
Fundamental Limitations ◽  
Service Deployment ◽  
Dynamic Resource Management ◽  
Numerous Data ◽  
Dynamic Resource ◽  
Iot Devices ◽  
Container Orchestration ◽  
The Internet Of Things

With the exponential growth of the Internet of Things (IoT), edge computing is in the limelight for its ability to quickly and efficiently process numerous data generated by IoT devices. EdgeX Foundry is a representative open-source-based IoT gateway platform, providing various IoT protocol services and interoperability between them. However, due to the absence of container orchestration technology, such as automated deployment and dynamic resource management for application services, EdgeX Foundry has fundamental limitations of a potential edge computing platform. In this paper, we propose EdgeX over Kubernetes, which enables remote service deployment and autoscaling to application services by running EdgeX Foundry over Kubernetes, which is a product-grade container orchestration tool. Experimental evaluation results prove that the proposed platform increases manageability through the remote deployment of application services and improves the throughput of the system and service quality with real-time monitoring and autoscaling.

scholarly journals The Internet of Things (IoT) and Social Interaction: Influence of Source Attribution and Human Specialization

2021 ◽  
Vol 9 (1) ◽  
pp. 17-28
Author(s):  
Siddhartha Vadlamudi
Keyword(s):  
Internet Of Things ◽  
Multiple Source ◽  
The Internet ◽  
Source Attribution ◽  
Source Effects ◽  
Physical Setting ◽  
Worldwide Web ◽  
Iot Devices ◽  
The Internet Of Things

The evolvement of IT has open new doors in connecting many devices to the worldwide web that successively produce data around the physical setting using the IoT. However, the system of message turns out to be slightly intricate in human specialization-internet of things communication for the reason that the IoT is a system including diverse objects transferring data This study examines the hypothetical pathway by which the changes in source attribution that is multiple against single and specialization that is multi-functionality against single functionality of IoT devices affect the quality of human- internet of things interaction. The result from the study obtained from 80 participants that took part in the experiment shows that multiple source attribution improves the condition of information basically for the low-involvement people supports further probes the multiple source effects. However, this study recommends improvement of attribution source and human specialization-IoT.

scholarly journals An Intelligent Offloading System Based on Multiagent Reinforcement Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yu Weng ◽  
Haozhen Chu ◽  
Zhaoyi Shi
Keyword(s):  
Reinforcement Learning ◽  
Base Station ◽  
Intelligent Vehicles ◽  
Edge Computing ◽  
Core Network ◽  
Resource Requirement ◽  
Node Scheduling ◽  
Multiagent Reinforcement Learning ◽  
Selection Of

Intelligent vehicles have provided a variety of services; there is still a great challenge to execute some computing-intensive applications. Edge computing can provide plenty of computing resources for intelligent vehicles, because it offloads complex services from the base station (BS) to the edge computing nodes. Before the selection of the computing node for services, it is necessary to clarify the resource requirement of vehicles, the user mobility, and the situation of the mobile core network; they will affect the users’ quality of experience (QoE). To maximize the QoE, we use multiagent reinforcement learning to build an intelligent offloading system; we divide this goal into two suboptimization problems; they include global node scheduling and independent exploration of agents. We apply the improved Kuhn–Munkres (KM) algorithm to node scheduling and make full use of existing edge computing nodes; meanwhile, we guide intelligent vehicles to the potential areas of idle computing nodes; it can encourage their autonomous exploration. Finally, we make some performance evaluations to illustrate the effectiveness of our constructed system on the simulated dataset.

scholarly journals Investment Decisions And The Parallel Funding Routes: Informal savings as a new tool of funding decision in the Cameroonian SMEs

2018 ◽  
Vol 6 (09) ◽  
Author(s):  
Emmanuel BEYINA
Keyword(s):  
Investment Decision ◽  
Investment Decisions ◽  
Medium Size ◽  
Funding Decision ◽  
Risk Capital ◽  
New Model ◽  
Decision Delay

The criteria of the choice of investment elaborated by theoricians are based on rationality of deciders who after some work often consider two types of aids to investment decision: delay of getting back invested capital and net actualized value. Whereas other forms of aid to funding decision exist. We are proposing in the framework of this article, a new model of aid to funding decision corresponding to the new informal funding. We think that risk capital in the framework of informal funding (Ndjangi) can bring forth long-term funding as strategy, and solutions to questions of rationality of the heads of Small and Medium size Enterprise (SMEs) that prefers the delay of getting back invested capital, solutions to problems of decision of choice, and at last solutions to the quality of profitability of investments.

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