EdgeABC: An architecture for task offloading and resource allocation in the Internet of Things

Xiao, Kaile; Gao, Zhipeng; Shi, Wei; Qiu, Xuesong; Yang, Yang; Rui, Lanlan

doi:10.1016/j.future.2020.02.026

Cited by 54 publications

(26 citation statements)

References 25 publications

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“…As shown in Fig 14 , each algorithm’s performance differences are illustrated when the data in the area are uniformly distributed. Literature [ 22 ] proposed EdgeABC, an emerging Internet of Things architecture, introduced blockchain to ensure the integrity of resource transaction data and the profit of service providers and proposed task shunting and resource allocation algorithms. Literature [ 23 ] offloaded the MEC server’s calculation through the small cell base station, connected to the macro BS through the wireless backhaul, and shared the MEC server’s computing resources among the offloaded MUs.…”

Section: Resultsmentioning

confidence: 99%

Deployment optimization of multi-stage investment portfolio service and hybrid intelligent algorithm under edge computing

Zhang

Shen

2021

PLoS ONE

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The purposes are to improve the server deployment capability under Mobile Edge Computing (MEC), reduce the time delay and energy consumption of terminals during task execution, and improve user service quality. After the server deployment problems under traditional edge computing are analyzed and researched, a task resource allocation model based on multi-stage is proposed to solve the communication problem between different supporting devices. This model establishes a combined task resource allocation and task offloading method and optimizes server execution by utilizing the time delay and energy consumption required for task execution and comprehensively considering the restriction processes of task offloading, partition, and transmission. For the MEC process that supports dense networks, a multi-hybrid intelligent algorithm based on energy consumption optimization is proposed. The algorithm converts the original problem into a power allocation problem via a heuristic model. Simultaneously, it determines the appropriate allocation strategy through distributed planning, duality, and upper bound replacement. Results demonstrate that the proposed multi-stage combination-based service deployment optimization model can solve the problem of minimizing the maximum task execution energy consumption combined with task offloading and resource allocation effectively. The algorithm has good performance in handling user fairness and the worst-case task execution energy consumption. The proposed hybrid intelligent algorithm can partition tasks into task offloading sub-problems and resource allocation sub-problems, meeting the user’s task execution needs. A comparison with the latest algorithm also verifies the model’s performance and effectiveness. The above results can provide a theoretical basis and some practical ideas for server deployment and applications under MEC.

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Section: Resultsmentioning

confidence: 99%

Deployment optimization of multi-stage investment portfolio service and hybrid intelligent algorithm under edge computing

Zhang

Shen

2021

PLoS ONE

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“…In [50], the authors introduced a new IoT architecture called "EdgeABC". This model consists of three layers: An IoT smart device layer, a distributed agent controller architecture based on blockchain, and a hierarchical edge computing servers.…”

Section: Research Surveymentioning

confidence: 99%

“…This model consists of three layers: An IoT smart device layer, a distributed agent controller architecture based on blockchain, and a hierarchical edge computing servers. The architecture in [50] utilized blockchain in the middle layer to ensure resource transaction data integrity. The study implemented a developed task offloading and resource allocation algorithm on blockchain in the form of a smart contract.…”

Section: Research Surveymentioning

confidence: 99%

A Survey on the Integration of Blockchain With IoT to Enhance Performance and Eliminate Challenges

2021

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Internet of things IoT is playing a remarkable role in the advancement of many fields such as healthcare, smart grids, supply chain management, etc. It also eases people's daily lives and enhances their interaction with each other as well as with their surroundings and the environment in a broader scope. IoT performs this role utilizing devices and sensors of different shapes and sizes ranging from small embedded sensors and wearable devices all the way to automated systems. However, IoT networks are growing in size, complexity, and number of connected devices. As a result, many challenges and problems arise such as security, authenticity, reliability, and scalability. Based on that and taking into account the anticipated evolution of the IoT, it is extremely vital not only to maintain but to increase confidence in and reliance on IoT systems by tackling the aforementioned issues. The emergence of blockchain opened the door to solve some challenges related to IoT networks. Blockchain characteristics such as security, transparency, reliability, and traceability make it the perfect candidate to improve IoT systems, solve their problems, and support their future expansion. This paper demonstrates the major challenges facing IoT systems and blockchain's proposed role in solving them. It also evaluates the position of current researches in the field of merging blockchain with IoT networks and the latest implementation stages. Additionally, it discusses the issues related to the IoT-blockchain integration itself. Finally, this research proposes an architectural design to integrate IoT with blockchain in two layers using dew and cloudlet computing. Our aim is to benefit from blockchain features and services to guarantee a decentralized data storage and processing and address security and anonymity challenges and achieve transparency and efficient authentication service.

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“…As an outcome, the size of the vending operators, estimated in the number of machines to be connected, ought not to be a hindrance to utilizing the solution at all. Vending machine operators can own multiple vending machines and operate their business in real-time [20,21]. Figure 6 describes the building blocks of the architecture of the software application that has been designed.…”

Section: Cloud System Architecturementioning

confidence: 99%

Internet of Things Based Smart Vending Machine using Digital Payment System

Alam

Sarma

Chakma

et al. 2021

IJEEI

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The advent of the Internet envisions a cashless society by enabling financial transactions through digital payments. Significantly, the emergence of coronavirus (COVID-19) disrupted our traditional cash handling means and triggered an inflexion point for switching towards contactless digital payments from physical cash payments. Furthermore, Internet of Things (IoT) technology escalates digital payments to the next level by enabling devices to render goods and services without requiring any human interaction. This research proposed an IoT-enabled cashless vending machine that incorporates both cloud computing and payment gateway for ordering and purchasing items through digital payment systems by using a mobile application. The system enables a pre-installed mobile application to scan the Quick Response (QR) code attached to the body of a vending machine, opens the portal of a webbased virtual machine through the code, allows user to choose and order items from the virtual vending, initiates and authorizes a digital payment through an IoT gateway installed inside the physical vending machine by establishing a connection between user's and vendor's financial entities, and finally, dispenses the ordered items by unlocking the shelves of the vending machine after the successful payment transaction. It operates in the Arduino platform with an ATmega 2560 Microcontroller and Esp8266 Wi-fi module as hardware components, mobile application software, and payment gateway API. The system performed an average response time of 14500 milliseconds to pick a product after running 150 consecutive API test calls. This result shows a satisfying time for enhancing customers' buying experiences with digital payment systems and a customizable and cost-effective IoT-based intelligent vending machine to introduce for mass production.

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EdgeABC: An architecture for task offloading and resource allocation in the Internet of Things

Cited by 54 publications

References 25 publications

Deployment optimization of multi-stage investment portfolio service and hybrid intelligent algorithm under edge computing

Deployment optimization of multi-stage investment portfolio service and hybrid intelligent algorithm under edge computing

A Survey on the Integration of Blockchain With IoT to Enhance Performance and Eliminate Challenges

Internet of Things Based Smart Vending Machine using Digital Payment System

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