QoS and traffic aware greedy resource allocation in foggy internet of things

Mahini, Hamidreza; Hajisheykhi, Reza; Shahini, Mina

doi:10.1504/ijcnds.2020.108155

“…X X ✓ X [31] They propose a method to improve the resource allocation problem in IoT applications S ✓ ✓ X…”

Section: S1mentioning

confidence: 99%

“…Accordingly, they define expressive abstractions to specify applications as service compositions, while hiding the complexity of IoT infrastructures. In the work [31], Mahini et al propose a method to improve the resource allocation problem in IoT applications using fog computing. They consider two objectives: 1) reducing the internet core traffic; 2) serving subscribers with the appropriate quality of service level.…”

Section: S2mentioning

confidence: 99%

An Autonomic Management System for IoT Platforms based on Data Analysis Tasks

Ouedraogo¹,

Chassot²,

Medjiah³

et al. 2022

IJCNDS

0

View full text Add to dashboard Cite

In this work, we propose an Autonomic Management System (AMS) for the Internet of Things (IoT) platforms, which uses the concept of autonomic cycle of data analysis tasks to improve and maintain the performance in the IoT platforms. The concept of "Autonomic Cycle of Data Analysis Tasks" is a type of autonomous intelligent supervision that allows reaching strategic objectives around a given problem. In this paper, we propose the conceptualization of the architecture of an AMS composed by an autonomic cycle to optimize the Quality of Services (QoS), and to improve the Quality of Experiences (QoE), in IoT platforms. The autonomous cycle detects and discoveries the current operational state in the IoT platform, and determines the set of tasks to guarantee a given performance (QoS/QoE). This paper presents the details of the architecture of the AMS (components, knowledge models, etc.), and its utilization in two case studies: in a typical application in an IoT context, and in a Tactile Internet System.

show abstract

“…X X ✓ X [31] They propose a method to improve the resource allocation problem in IoT applications S ✓ ✓ X…”

Section: S1mentioning

confidence: 99%

“…Accordingly, they define expressive abstractions to specify applications as service compositions, while hiding the complexity of IoT infrastructures. In the work [31], Mahini et al propose a method to improve the resource allocation problem in IoT applications using fog computing. They consider two objectives: 1) reducing the internet core traffic; 2) serving subscribers with the appropriate quality of service level.…”

Section: S2mentioning

confidence: 99%

An autonomic management system for IoT platforms based on data analysis tasks

Ouedraogo

¹

,

Aguilar

²

,

Chassot

³

et al. 2022

IJCNDS

0

View full text Add to dashboard Cite

In this work, we propose an Autonomic Management System (AMS) for the Internet of Things (IoT) platforms, which uses the concept of autonomic cycle of data analysis tasks to improve and maintain the performance in the IoT platforms. The concept of "Autonomic Cycle of Data Analysis Tasks" is a type of autonomous intelligent supervision that allows reaching strategic objectives around a given problem. In this paper, we propose the conceptualization of the architecture of an AMS composed by an autonomic cycle to optimize the Quality of Services (QoS), and to improve the Quality of Experiences (QoE), in IoT platforms. The autonomous cycle detects and discoveries the current operational state in the IoT platform, and determines the set of tasks to guarantee a given performance (QoS/QoE). This paper presents the details of the architecture of the AMS (components, knowledge models, etc.), and its utilization in two case studies: in a typical application in an IoT context, and in a Tactile Internet System.

show abstract