Towards energy efficient service composition in green energy powered Cyber–Physical Fog Systems

Zeng, Deze; Gu, Lin; Yao, Hong

doi:10.1016/j.future.2018.01.060

Cited by 55 publications

(29 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Finally, Zeng et al introduced a heuristic method in order to exploit energy by applying service composition in the FC platform. Using green energy in fog nodes, this method is proposed for CPSs.…”

Section: Classification Of the Selected Approachesmentioning

confidence: 99%

Quality of service‐aware approaches in fog computing

Kashani

Rahmani

Navimipour

2020

Int J Communication

View full text Add to dashboard Cite

Summary In recent years, fog computing, a novel paradigm, has emerged for location and latency‐sensitive applications. It is a powerful complement for cloud computing that enables provisioning services and resources outside the cloud near the end devices. In a fog system, the existence of several nonhomogenous devices, which are potentially mobile, led to quality of service (QoS) worries. QoS‐aware approaches are presented in various parts of the fog system, and several different QoS factors are taken into account. In spite of the importance of QoS in fog computing, no comprehensive study on QoS‐aware approaches exists in fog computing. Hence, this paper reviews the current research used to guarantee QoS in fog computing. This paper investigates the QoS‐ensuring techniques that fall into three categories: service/resource management, communication management, and application management (published between 2013 and October 2018). Regarding the selected approaches, this paper represents merits, demerits, tools, evaluation types, and QoS factors. Finally, on the basis of the reviewed studies, we suggest some open issues and challenges which are worth further studying and researching in QoS‐aware approaches in fog computing.

show abstract

Section: Classification Of the Selected Approachesmentioning

confidence: 99%

Quality of service‐aware approaches in fog computing

Kashani

Rahmani

Navimipour

2020

Int J Communication

View full text Add to dashboard Cite

show abstract

“…In 2018, Zeng et al [19] investigated the effect of different power types on fog computing to achieve an efficient structure for providing power services. They designed a CPS-based fog network with green energy and developed this system with a focus on resource rate control, load balancer, and services.…”

Section: Related Workmentioning

confidence: 99%

Energy‐efficient workload allocation in fog‐cloud based services of intelligent transportation systems using a learning classifier system

Abbasi

Yaghoobikia

Rafiee

et al. 2020

IET Intelligent Trans Sys

View full text Add to dashboard Cite

Nowadays, renewable energies have been considered as one of the important sources of energy supply in delaysensitive fog computations in intelligent transportation systems due to their cheapness and availability. This study addresses the challenges of using renewable power supplies in delay-sensitive fogs and proposes an efficient workload allocation method based on a learning classifier system. The system dynamically learns the workload allocation policies between the cloud and the fog servers and then converges on the optimal allocation that fulfils the energy and delay requirements in the overall transportation system. Simulation results confirm that the proposed algorithm reduces the long-term costs of the system including service delay and operating costs. Also, compared to some other techniques, when the proposed method presents the most successful solution for reducing the average delay of the workloads and converging on the minimum value as well as retaining or even increasing the battery levels of fog nodes up to 100%. The lowest cost of the delay is 5 among other available methods, whereas in the proposed method, this value approaches 4.5.

show abstract

“…Their proposed model integrated IoT sensors, cloud computing and fog computing with the CPS for assimilating, analysing and sharing medical information among patients and health-care service providers. Zeng et al [30] developed a cyber-physical fog system model that achieved energy-efficient service composition in load balancing. They proposed a heuristic algorithm to solve a mixed-integer linear programming and proved as NP-hard energy efficiency problem.…”

Section: Cyber-physical System In Present Computing Paradigmmentioning

confidence: 99%