scholarly journals Distributed Learning Based Joint Communication and Computation Strategy of IoT Devices in Smart Cities

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 973
Author(s):  
Tianyi Liu ◽  
Ruyu Luo ◽  
Fangmin Xu ◽  
Chaoqiong Fan ◽  
Chenglin Zhao
Keyword(s):  
Smart Cities ◽  
Wireless Channel ◽  
Edge Computing ◽  
Resource Allocation Algorithm ◽  
Q Learning ◽  
Joint Policy ◽  
Low Efficiency ◽  
Learning Policies ◽  
Iot Devices ◽  
The Internet Of Things

With the development of global urbanization, the Internet of Things (IoT) and smart cities are becoming hot research topics. As an emerging model, edge computing can play an important role in smart cities because of its low latency and good performance. IoT devices can reduce time consumption with the help of a mobile edge computing (MEC) server. However, if too many IoT devices simultaneously choose to offload the computation tasks to the MEC server via the limited wireless channel, it may lead to the channel congestion, thus increasing time overhead. Facing a large number of IoT devices in smart cities, the centralized resource allocation algorithm needs a lot of signaling exchange, resulting in low efficiency. To solve the problem, this paper studies the joint policy of communication and computing of IoT devices in edge computing through game theory, and proposes distributed Q-learning algorithms with two learning policies. Simulation results show that the algorithm can converge quickly with a balanced solution.

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 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 Automatic Failure Recovery for Container-Based IoT Edge Applications

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 3047
Author(s):  
Kolade Olorunnife ◽  
Kevin Lee ◽  
Jonathan Kua
Keyword(s):  
Internet Of Things ◽  
Smart Cities ◽  
Smart Homes ◽  
Edge Computing ◽  
Failure Recovery ◽  
Software Failures ◽  
Iot Applications ◽  
Remote Management ◽  
Management Ability ◽  
Iot Devices

Recent years have seen the rapid adoption of Internet of Things (IoT) technologies, where billions of physical devices are interconnected to provide data sensing, computing and actuating capabilities. IoT-based systems have been extensively deployed across various sectors, such as smart homes, smart cities, smart transport, smart logistics and so forth. Newer paradigms such as edge computing are developed to facilitate computation and data intelligence to be performed closer to IoT devices, hence reducing latency for time-sensitive tasks. However, IoT applications are increasingly being deployed in remote and difficult to reach areas for edge computing scenarios. These deployment locations make upgrading application and dealing with software failures difficult. IoT applications are also increasingly being deployed as containers which offer increased remote management ability but are more complex to configure. This paper proposes an approach for effectively managing, updating and re-configuring container-based IoT software as efficiently, scalably and reliably as possible with minimal downtime upon the detection of software failures. The approach is evaluated using docker container-based IoT application deployments in an edge computing scenario.

scholarly journals A Lightweight Two-Layer Blockchain Mechanism for Reliable Crossing-Domain Communication in Smart Cities

2021 ◽  
Author(s):  
Xiangyu Xu ◽  
Jianfei Peng
Keyword(s):  
Block Structure ◽  
Smart Cities ◽  
Consensus Protocol ◽  
Reliable Communication ◽  
Collusion Attack ◽  
Efficient Communication ◽  
Reliable Communications ◽  
Iot Devices ◽  
Cloud Servers ◽  
The Internet Of Things

The smart city is an emerging notion that is leveraging the Internet of Things (IoT) technique to achieve more comfortable, smart and controllable cities. The communications crossing domains between smart cities is indispensable to enhance collaborations. However, crossing-domain communications are more vulnerable since there are in different domains. Moreover, there are huge different devices with different computation capabilities, from sensors to the cloud servers. In this paper, we propose a lightweight two-layer blockchain mechanism for reliable crossing-domain communication in smart cities. Our mechanism provides a reliable communication mechanism for data sharing and communication between smart cities. We defined a two-layer blockchain structure for the communications inner and between smart cities to achieve reliable communications. We present a new block structure for the lightweight IoT devices. Moreover, we present a reputation-based multi-weight consensus protocol in order to achieve efficient communication while resistant to the nodes collusion attack for the proposed blockchain system. We also conduct a secure analysis to demonstrate the security of the proposed scheme. Finally, performance evaluation shows that our scheme is efficient and practical.

scholarly journals Federation of Internet of Things Testbeds for the Realization of a Semantically-Enabled Multi-Domain Data Marketplace

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3375 ◽  
Author(s):  
Luis Sánchez ◽  
Jorge Lanza ◽  
Juan Santana ◽  
Rachit Agarwal ◽  
Pierre Raverdy ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Smart Cities ◽  
Mitigation Strategies ◽  
Smart Building ◽  
Research And Innovation ◽  
Application Service ◽  
Crowd Sensing ◽  
Iot Devices ◽  
The One ◽  
The Internet Of Things

The Internet of Things (IoT) concept has attracted a lot of attention from the research and innovation community for a number of years already. One of the key drivers for this hype towards the IoT is its applicability to a plethora of different application domains. However, infrastructures enabling experimental assessment of IoT solutions are scarce. Being able to test and assess the behavior and the performance of any piece of technology (i.e., protocol, algorithm, application, service, etc.) under real-world circumstances is of utmost importance to increase the acceptance and reduce the time to market of these innovative developments. This paper describes the federation of eleven IoT deployments from heterogeneous application domains (e.g., smart cities, maritime, smart building, crowd-sensing, smart grid, etc.) with over 10,000 IoT devices overall which produce hundreds of thousands of observations per day. The paper summarizes the resources that are made available through a cloud-based platform. The main contributions from this paper are twofold. In the one hand, the insightful summary of the federated data resources are relevant to the experimenters that might be seeking for an experimental infrastructure to assess their innovations. On the other hand, the identification of the challenges met during the testbed integration process, as well as the mitigation strategies that have been implemented to face them, are of interest for testbed providers that can be considering to join the federation.

Virtual Mobile Edge Computing Based on IoT Devices Resources in Smart Cities

2020 ◽  
Author(s):  
Mohammed Laroui ◽  
Hatem Ibn Khedher ◽  
Hassine Moungla ◽  
Hossam Afifi ◽  
Ahmed E. Kamal
Keyword(s):  
Smart Cities ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Iot Devices

scholarly journals A lightweight cryptographic algorithm for the transmission of images from road environments in self-driving

Cybersecurity ◽  
2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Runchen Gao ◽  
Shen Li ◽  
Yuqi Gao ◽  
Rui Guo
Keyword(s):  
Large Scale ◽  
Edge Computing ◽  
Sensitive Information ◽  
Security Strategy ◽  
Privacy Leakage ◽  
Computational Overhead ◽  
Cryptographic Algorithm ◽  
Comparable Encryption ◽  
Iot Devices ◽  
The Internet Of Things

AbstractWith the large-scale application of 5G in industrial production, the Internet of Things has become an important technology for various industries to achieve efficiency improvement and digital transformation with the help of the mobile edge computing. In the modern industry, the user often stores data collected by IoT devices in the cloud, but the data at the edge of the network involves a large of the sensitive information, which increases the risk of privacy leakage. In order to address these two challenges, we propose a security strategy in the edge computing. Our security strategy combines the Feistel architecture and short comparable encryption based on sliding window (SCESW). Compared to existing security strategies, our proposed security strategy guarantees its security while significantly reducing the computational overhead. And our GRC algorithm can be successfully deployed on a hardware platform.

Streamlining IoT system development with open standards

2020 ◽  
Vol 62 (5-6) ◽  
pp. 215-226
Author(s):  
Ege Korkan ◽  
Sebastian Kaebisch ◽  
Sebastian Steinhorst
Keyword(s):  
Industry 4.0 ◽  
Smart Home ◽  
World Wide ◽  
System Development ◽  
Smart Cities ◽  
Time To Market ◽  
Wide Range ◽  
The World ◽  
Iot Devices ◽  
The Internet Of Things

AbstractThe Internet of Things (IoT) is bringing Internet connectivity to a wide range of devices which results in an increasing number of products for smart home, industry 4.0 and/or smart cities. Even though IoT has the ambition to reach an increasing amount of devices and be scalable across different domains, lack of interoperability inhibits this scope to be attained. Recent standardization efforts by the World Wide Web Consortium (W3C) are addressing the interoperability problem by the means of Thing Description (TD) that allows humans and machines to understand the capabilities and communication interfaces of IoT devices. In this paper, we show a more systematic and streamlined development of IoT devices and systems that relies on the TD standard. We introduce three different complementary methods that can be applied independently in the different stages of the development, or as a framework to streamline the development of IoT devices and systems. As a result of using the TD standard, interoperability between IoT devices of various stakeholders is ensured from early stages and the time to market is reduced.

scholarly journals Fog Fragment Cooperation on Bandwidth Management Based on Reinforcement Learning

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6942
Author(s):  
Motahareh Mobasheri ◽  
Yangwoo Kim ◽  
Woongsup Kim
Keyword(s):  
Reinforcement Learning ◽  
Learning Algorithm ◽  
Fog Computing ◽  
Learning Approach ◽  
Data Generation ◽  
Bandwidth Management ◽  
Q Learning ◽  
Decision Making Problem ◽  
Iot Devices ◽  
The Internet Of Things

The term big data has emerged in network concepts since the Internet of Things (IoT) made data generation faster through various smart environments. In contrast, bandwidth improvement has been slower; therefore, it has become a bottleneck, creating the need to solve bandwidth constraints. Over time, due to smart environment extensions and the increasing number of IoT devices, the number of fog nodes has increased. In this study, we introduce fog fragment computing in contrast to conventional fog computing. We address bandwidth management using fog nodes and their cooperation to overcome the extra required bandwidth for IoT devices with emergencies and bandwidth limitations. We formulate the decision-making problem of the fog nodes using a reinforcement learning approach and develop a Q-learning algorithm to achieve efficient decisions by forcing the fog nodes to help each other under special conditions. To the best of our knowledge, there has been no research with this objective thus far. Therefore, we compare this study with another scenario that considers a single fog node to show that our new extended method performs considerably better.

scholarly journals Detecting security attacks in cyber-physical systems: a comparison of Mule and WSO2 intelligent IoT architectures

2021 ◽  
Vol 7 ◽  
pp. e787
Author(s):  
José Roldán-Gómez ◽  
Juan Boubeta-Puig ◽  
Gabriela Pachacama-Castillo ◽  
Guadalupe Ortiz ◽  
Jose Luis Martínez
Keyword(s):  
Real Time ◽  
Smart Cities ◽  
Cyber Physical Systems ◽  
Security Attacks ◽  
Physical Systems ◽  
The Real ◽  
Real Time Detection ◽  
Iot Devices ◽  
Definition Of ◽  
The Internet Of Things

The Internet of Things (IoT) paradigm keeps growing, and many different IoT devices, such as smartphones and smart appliances, are extensively used in smart industries and smart cities. The benefits of this paradigm are obvious, but these IoT environments have brought with them new challenges, such as detecting and combating cybersecurity attacks against cyber-physical systems. This paper addresses the real-time detection of security attacks in these IoT systems through the combined used of Machine Learning (ML) techniques and Complex Event Processing (CEP). In this regard, in the past we proposed an intelligent architecture that integrates ML with CEP, and which permits the definition of event patterns for the real-time detection of not only specific IoT security attacks, but also novel attacks that have not previously been defined. Our current concern, and the main objective of this paper, is to ensure that the architecture is not necessarily linked to specific vendor technologies and that it can be implemented with other vendor technologies while maintaining its correct functionality. We also set out to evaluate and compare the performance and benefits of alternative implementations. This is why the proposed architecture has been implemented by using technologies from different vendors: firstly, the Mule Enterprise Service Bus (ESB) together with the Esper CEP engine; and secondly, the WSO2 ESB with the Siddhi CEP engine. Both implementations have been tested in terms of performance and stress, and they are compared and discussed in this paper. The results obtained demonstrate that both implementations are suitable and effective, but also that there are notable differences between them: the Mule-based architecture is faster when the architecture makes use of two message broker topics and compares different types of events, while the WSO2-based one is faster when there is a single topic and one event type, and the system has a heavy workload.

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