Edge User Allocation with Dynamic Quality of Service

Lai, Phu; He, Qiang; Cui, Guangming; Xia, Xiaoyu; Abdelrazek, Mohamed; Chen, Feifei; Hosking, John; Grundy, John; Yang, Yun

doi:10.1007/978-3-030-33702-5_8

Cited by 67 publications

(20 citation statements)

References 19 publications

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“…And the architecture can combine the system that supply energy and edge services, which can make full use of renewable energy and provide better QoS. Lai et al [30] proposed an optimized allocation method for edge users. e method can not only maximize the amount of resources allocated to users but also consider the dynamic QoS level of users.…”

Section: Edge Computingmentioning

confidence: 99%

Study QoS Optimization and Energy Saving Techniques in Cloud, Fog, Edge, and IoT

Wang

Sun

et al. 2020

Complexity

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With an increase of service users’ demands on high quality of services (QoS), more and more efficient service computing models are proposed. The development of cloud computing, fog computing, and edge computing brings a number of challenges, e.g., QoS optimization and energy saving. We do a comprehensive survey on QoS optimization and energy saving in cloud computing, fog computing, edge computing, and IoT environments. We summarize the main challenges and analyze corresponding solutions proposed by existing works. This survey aims to help readers have a deeper understanding on the concepts of different computing models and study the techniques of QoS optimization and energy saving in these models.

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Section: Edge Computingmentioning

confidence: 99%

Study QoS Optimization and Energy Saving Techniques in Cloud, Fog, Edge, and IoT

Wang

Sun

et al. 2020

Complexity

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“…Lai et al [42] took into consideration the dynamic Quality of service (QoS) levels for mobile users and turn it into a dynamic QoS edge user allocation problem. Correspondingly, an optimal approach is proposed to find solutions which maximizes mobile users' overall Quality of Experience.…”

Section: Related Workmentioning

confidence: 99%

A New Cloudlet Placement Method Based on Affinity Propagation for Cyber-Physical-Social Systems in Wireless Metropolitan Area Networks

Peng¹,

Qian²,

Zhao³

et al. 2020

IEEE Access

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Cyber-Physical-Social Systems (CPSS) integrates the cyber, physical and social spaces together. There are a large number of mobile users in CPSS that need low latency services. Fortunately, mobile edge computing (MEC) is a novel technology which can provide such services. The edge server plays a key role in MEC, but how to manage the edge server is an important challenge. For one thing, the number of cloudlets and the resource are limited. For another, the number of mobile devices (MDs) is very large and randomly distributed. And thus, how to determine the suitable number of cloudlets while serving the maximum number of MDs is significant. To this end, a new cloudlet placement method based on improved Affinity Propagation (AP) algorithm is proposed to solve the above problems. More specially, the improved AP algorithm can obtain the least number of cloudlets while covering the largest number of MDs. In addition, the load balancing strategy is used to ensure that the load of each cloudlet maintains a balanced state. Last but not the least, our proposed method can be used in scenarios where users move. INDEX TERMS Mobile edge computing, cloudlet placement, affinity propagation algorithm, load balancing.

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“…CA is divided into two parts by structure: server and client. The server can be deployed as a cluster, including Root CA Server (RCAS) and Intermediate CA Server (ICAS) [1][2][3][4][5][6][7]. The CA of the blockchain network also needs a certificate.…”

Section: Framework Of the Cdmbs And Security Certificationmentioning

confidence: 99%

Security Control Components for Epidemic Prevention Donation Management Blockchain

Wang

Hou

et al. 2020

Proceedings of the 2nd ACM International Symposium on Blockchain and Secure Critical Infrastructure

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After the outbreak of the new coronavirus pneumonia, it has been broadcasting soon. Medical supplies are out of used. Chinese people have provided medical supplies and raised donations to help Hubei Province, China. While, Red Cross Society of Hubei Branch and Wuhan Branch were suspected for unfair distribution of donated materials, the backlog of donated items, and inefficient assignment. These problems exposed public welfare organizations to the public sights. For information sharing, Jiangsu Province developed a new COVID-19 Donation Management Blockchain System (CDMBS). The system improves the transparency and credibility of donation information with the blockchain. Based on the overall architecture of Jiangsu's new coronavirus charity donation management blockchain, this paper designs various types of security control components. The components include the middleware for secure connection to protect the user certificate security. We designed CA certificate user management middleware to realize more secure registration and query functions for users with extended attributes. There is also a blockchain query middle with access control Software to ensure that important blockchain information is viewed securely. Experiments have verified the effectiveness and applicability of these security control components. It can be applied into a variety of scenarios in the CDMBS.

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Edge User Allocation with Dynamic Quality of Service

Cited by 67 publications

References 19 publications

Study QoS Optimization and Energy Saving Techniques in Cloud, Fog, Edge, and IoT

Study QoS Optimization and Energy Saving Techniques in Cloud, Fog, Edge, and IoT

A New Cloudlet Placement Method Based on Affinity Propagation for Cyber-Physical-Social Systems in Wireless Metropolitan Area Networks

Security Control Components for Epidemic Prevention Donation Management Blockchain

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