Quality of Experience Framework for Cloud Computing (QoC)

Laghari, Asif Ali; He, Hui; Khan, Asiya; Kumar, Neetesh; Kharel, Rupak

doi:10.1109/access.2018.2865967

Cited by 69 publications

(39 citation statements)

References 24 publications

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“…Though the system around a server center is frequently high limit and speed that close to the client devices may have fluid properties (Regarding flexibility, transmission capacity, idleness, and so forth). Cloud and network management are important for service providers to provide QoS to end users, so they can evaluate their services via subjective feedback of users, sometimes which contains inaccurate and negative responses [62,63]. Therefore, for proper management accurate and positive QoE is required, leading to further work in QoE monitoring and management.…”

Section: Open Research Issuesmentioning

confidence: 99%

Comparison of Fog Computing & Cloud Computing

Kumar¹,

Laghari²,

Karim³

et al. 2019

IJMSC

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Fog computing is extending cloud computing by transferring computation on the edge of networks such as mobile collaborative devices or fixed nodes with built-in data storage, computing, and communication devices. Fog gives focal points of enhanced proficiency, better security, organize data transfer capacity sparing and versatility. With a specific end goal to give imperative subtle elements of Fog registering, we propose attributes of this region and separate from cloud computing research. Cloud computing is developing innovation which gives figuring assets to a specific assignment on pay per utilize. Cloud computing gives benefit three unique models and the cloud gives shoddy; midway oversaw assets for dependable registering for performing required errands. This paper gives correlation and attributes both Fog and cloud computing differs by outline, arrangement, administrations and devices for associations and clients. This comparison shows that Fog provides more flexible infrastructure and better service of data processing by consuming low network bandwidth instead of shifting whole data to the cloud.

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Section: Open Research Issuesmentioning

confidence: 99%

Comparison of Fog Computing & Cloud Computing

Kumar¹,

Laghari²,

Karim³

et al. 2019

IJMSC

Self Cite

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“…It enables the user to create Virtual Machines (VMs) on physical servers [6], which leads to reducing the required hardware equipment and improving physical resources utilization in cloud computing. There are several advantages provided by clouds to cloud users and the service providers, the major advantages of cloud computing are described in [5,[7][8][9][10] and listed below:…”

Section: Introductionmentioning

confidence: 99%

Task scheduling in cloud computing based on metaheuristic techniques: A review paper

Al-Arasi¹,

Saif²

2020

EAI Endorsed Transactions on Cloud Systems

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Cloud computing delivers computing resources like software and hardware as a service to the users through a network. Due to the scale of the modern datacentres and their dynamic resources provisioning nature, we need efficient scheduling techniques to manage these resources. The main objective of scheduling is to assign tasks to adequate resources in order to achieve one or more optimization criteria. Scheduling is a challenging issue in the cloud environment, therefore many researchers have attempted to explore an optimal solution for task scheduling in the cloud environment. They have shown that traditional scheduling is not efficient in solving this problem and produce an optimal solution with polynomial time in the cloud environment. However, they introduced sub-optimal solutions within a short period of time. Meta-heuristic techniques have provided near-optimal or optimal solutions within an acceptable time for such problems. In this work, we have introduced the major concepts of resource scheduling and provided a comparative analysis of many task scheduling techniques based on different optimization criteria.

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“…Fog computing is an extension of cloud computing. Cloud services are available on the pay per use, but the distance of end-user from cloud increase the network latency, which degrades the service perception and increase energy usage [2,3]. Fog computing (FC) is a promising paradigm that offers cloud services with lower end-to-end latency at the edge of the Internet [4,5] as illustrated in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Application-Partitioning Algorithm with Improved Offloading Mechanism for Fog Cloud Networks

et al. 2019

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This paper aims to propose a new fog cloud architecture that performs a joint energy-efficient task assignment (JEETA). The proposed JEETA architecture utilizes the dynamic application-partitioning algorithm (DAPTS), a novel algorithm that efficiently decides and switches the task to be offloaded or not in heterogeneous environments with minimal energy consumption. The proposed scheme outperforms baseline approaches such as MAUI, Think Air and Clone Cloud in many performance aspects. Results show that for the execution of 1000 Tasks on fog, mobile offloaded nodes, JEETA consumes the leas, i.e., 23% of the total energy whereas other baseline approaches consume in between 50%–100% of the total energy. Results are validated via real test-bed experiments and trice are driven efficient simulations.

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Quality of Experience Framework for Cloud Computing (QoC)

Cited by 69 publications

References 24 publications

Comparison of Fog Computing & Cloud Computing

Comparison of Fog Computing & Cloud Computing

Task scheduling in cloud computing based on metaheuristic techniques: A review paper

A Dynamic Application-Partitioning Algorithm with Improved Offloading Mechanism for Fog Cloud Networks

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