Incentive mechanism design for edge‐cloud collaboration in mobile crowd sensing

Li, Zhuo; Zhang, Lihan; Chen, Xin

doi:10.1002/ett.4105

Cited by 4 publications

(4 citation statements)

References 24 publications

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“…Therefore, cloud collaboration is rapidly applied in many fields, which can not only provide massive data computing and storage support for intelligent equipment, but also reduce the installation cost of user equipment. However, due to the remote deployment of cloud servers [ 4 ], the computing tasks generated by some network edges are all transferred to the cloud server for processing, which requires a long transmission time and high costs for computing [ 5 ]. Therefore, the study of mobile edge and cloud collaboration has important reference value for promoting industrial development.…”

Section: Introductionmentioning

confidence: 99%

Relationship between employees’ career maturity and career planning of edge computing and cloud collaboration from the perspective of organizational behavior

Zhang

Song

2021

PLoS ONE

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A new IoT (Internet of Things) analysis platform is designed based on edge computing and cloud collaboration from the perspective of organizational behavior, to fundamentally understand the relationship between enterprise career maturity and career planning, and meet the actual needs of enterprises. The performance of the proposed model is further determined according to the characteristic of the edge near data sources, with the help of factor analysis, and through the study and analysis of relevant enterprise data. The model is finally used to analyze the relationship between enterprise career maturity and career planning through simulation experiments. The research results prove that career maturity positively affects career planning, and vocational delay of gratification plays a mediating role in career maturity and career planning. Besides, the content of career choice in career maturity is influenced by mental acuity, result acuity and loyalty. The experimental results indicate that when the load at both ends of the edge and cloud exceeds 80%, the edge delay of the IoT analysis platform based on edge computing and cloud collaboration is 10s faster than that of other models. Meanwhile, the system slowdown is reduced by 36% while the stability is increased when the IoT analysis platform analyzes data. The results of the edge-cloud collaboration scheduling scheme are similar to all scheduling to the edge end, which saves 19% of the time compared with cloud computing to the cloud end. In Optical Character Recognition and Aeneas, compared with the single edge-cloud coordination mode, the model with the Nesterov Accelerated Gradient algorithm achieves the optimal performance. Specifically, the communication delay is reduced by about 25% on average, and the communication time decreased by 61% compared with cloud computing to the edge end. This work has significant reference value for analyzing the relationship between enterprise psychology, behavior, and career planning.

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Section: Introductionmentioning

confidence: 99%

Relationship between employees’ career maturity and career planning of edge computing and cloud collaboration from the perspective of organizational behavior

Zhang

Song

2021

PLoS ONE

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“…A mobile crowdsensing system often consists of some collector users and several competing task publishers [2]. Collector users collect data and send it to interested publishers [3]. Publishers collect and process this information.…”

Section: Introductionmentioning

confidence: 99%

An Incentive Mechanism for Data Delivery in Mobile Crowdsensing Based on D2D Communications

Esmaeilyfard,

Gharechahi

2023

Journal of Sensors

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Mobile crowdsensing systems employ crowd smartphones to collect data using these device-embedded sensors. The increase in the number of users and the data volume has limited the possibility of using cellular networks. In this regard, collector users need to be able to send their data to the publishers with less delay using device-to-device (D2D) communication. This paper proposes an incentive mechanism for improving the transmission rate to multiple publishers in mobile crowdsensing networks based on device-to-device communication. Users exchange their data for delivering it to interested publishers in this mechanism. Users receive credits for their contributions to data delivery from collector users. Also, the cheque concept has been introduced to facilitate collector users’ payment of this credit. Communication between users is expressed as a cooperative two-player game. A heuristic approach finds the solution to this game. A cheque and credit exchange process is also planned as an online auction to increase credit circulation in the network. Finally, the performance of the proposed mechanism is evaluated using the simulator. The results show that this mechanism performs better than other methods in average delay and delivery rate and has a stable traffic overhead.

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“…Energy consumption of mobile crowd sensing in IoT has extremely growing affectedly through today by existing technologies including smart transportations, smart manufacturing, intelligent medical system, and, and so on, in contrast privacy and security should be mentioned comprehensively. 11 This paper presents analytical aspects of blockchain technology for energy efficient mobile crowd sensing approaches in IoT environments. Existing frameworks and architectures are compared among each other based on evaluation metrics, applied algorithms, principals, and others.…”

Section: Introductionmentioning

confidence: 99%

“…Authentication procedure in blockchain technology has played a key role to support a secured mobile devices that has stored all information about what did happened and what will be done in future. Energy consumption of mobile crowd sensing in IoT has extremely growing affectedly through today by existing technologies including smart transportations, smart manufacturing, intelligent medical system, and, and so on, in contrast privacy and security should be mentioned comprehensively 11 …”

Section: Introductionmentioning

confidence: 99%

Blockchain technology for energy‐aware mobile crowd sensing approaches in Internet of Things

Sisi

Souri

2021

Trans Emerging Tel Tech

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Today, Blockchain technology is emerging to support high secured performance computing. To improve privacy and security factors of allocate, storage, and manage resources in edge computing, blockchain technology can be used to guarantee safe data transmission and communications in Internet of Things (IoT). Due to heterogeneity of resources to cover a range number of IoT applications, resource allocation has a key role for increasing performance of the IoT systems in edge computing. Also, a blockchain‐based resource allocation model can support Quality of Service (QoS) for IoT applications to ensure a high secured communication environment in edge computing. This paper reviews different existing green energy strategies based on blockchain technology in mobile crowd sensing. Mobile crowd sensing refers to all computational aspects related to smart city, smart home‐care, smart grid, smart transportations, smart medical systems, smart industry, manufacturing, and smart farming in IoT environments. This review aims to classify principles and technical aspects of green energy strategies based on blockchain technology in mobile crowd sensing with respect to technical aspects, applied algorithms, evaluation factors, and evaluation environments. Based on Systematic Literature Review (SLR), we selected 37 high potential and key relevant research studies to consider in this review. Based on analytical results, 35% of them were considered as private‐based blockchain methods, 33% of them were applied to the public‐based blockchain methods, 24% of them were considered as consortium‐based blockchain methods, and 8% of them were as hybrid‐based blockchain methods.

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Incentive mechanism design for edge‐cloud collaboration in mobile crowd sensing

Cited by 4 publications

References 24 publications

Relationship between employees’ career maturity and career planning of edge computing and cloud collaboration from the perspective of organizational behavior

Relationship between employees’ career maturity and career planning of edge computing and cloud collaboration from the perspective of organizational behavior

An Incentive Mechanism for Data Delivery in Mobile Crowdsensing Based on D2D Communications

Blockchain technology for energy‐aware mobile crowd sensing approaches in Internet of Things

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