scholarly journals New Application Task Offloading Algorithms for Edge, Fog, and Cloud Computing Paradigms

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Sungwook Kim
Keyword(s):  
Cloud Computing ◽  
Superior Performance ◽  
Bargaining Solution ◽  
Simulation Studies ◽  
Research Issues ◽  
Application Service ◽  
Primary Advantage ◽  
Strategic Solution ◽  
Future Work ◽  
Task Offloading

In the last few years, we have seen an exponential increase in the number of computation-intensive applications, which have resulted in the popularity of fog and cloud computing paradigms among smart-chip-embedded mobile devices. These devices can partially offload computation tasks either using the fog system or using the cloud system. In this study, we design a new task offloading scheme by considering the challenges of future edge, fog and cloud computing paradigms. To provide an effective solution toward an appropriate task offloading problem, we focus on two cooperative bargaining game solutions—Tempered Aspirations Bargaining Solution (TABS) and Gupta-Livne Bargaining Solution (GLBS). To maximize the application service quality, a proper bargaining solution should be properly selected. In the proposed scheme, the TABS method is used for time-sensitive offloading services, and the GLBS method is applied to ensure computation-oriented offloading services. The primary advantage of our bargaining-based approach is to provide an axiom-based strategic solution for the task offloading problem while dynamically responding to the current network environments. Extensive simulation studies are conducted to demonstrate the effectiveness of the proposed scheme, and the superior performance over existing schemes is observed. Finally, we show prime directions for future work and potential research issues.

scholarly journals Enhhanced and Efficient Memory Model For Hadoop Mapreduce

2019 ◽  
Vol 9 (1) ◽  
pp. 161-168
Keyword(s):  
Cloud Computing ◽  
Parallel Computing ◽  
High Performance ◽  
Superior Performance ◽  
Research Issues ◽  
Data Intensive ◽  
Hadoop Mapreduce ◽  
Virtual Computing ◽  
Computing Framework ◽  
Efficient Memory

Usage of high-performance computing (HPC) infrastructure adopting cloud-computing environment offers an efficient solution for executing data intensive application. MapReduce (MR) is the favored high performance parallel computing framework used in BigData study, scientific, and data intensive applications. Hadoop is one of the significantly used MR based parallel computing framework by various organization as it is freely available open source framework from Apache foundation. The existing Hadoop MapReduce (HMR) based makespan model incurs memory and I/O overhead. Thus, affecting makespan performance. For overcoming research issues and challenges, this manuscript presented an efficient parallel HMR (PHMR) makespan model. The PHMR includes a parallel execution scheme in virtual computing worker to reduce makespan times using cloud computing framework. The PHMR model provides efficient memory management design within the virtual computing workers to minimize memory allocation and transmission overheads. For evaluating performance of PHMR of over existing model experiment are conducted on public cloud environment using Azure HDInsight cloud platform. Different application such as bioinformatics, tex mining, stream, and nonstream application is considered. The overall result obtained shows superior performance is attained by PHMR over existing model in term of makespan time reduction and correlation among practical and theoretical makespan values.

scholarly journals Equivalence Testing for Regression Discontinuity Designs

2020 ◽  
pp. 1-17
Author(s):  
Erin Hartman
Keyword(s):  
Political Science ◽  
Current Practice ◽  
Regression Discontinuity ◽  
Regression Function ◽  
Superior Performance ◽  
Equivalence Testing ◽  
Simulation Studies ◽  
Equivalence Tests ◽  
Regression Discontinuity Designs ◽  
Testing Approach

Abstract Regression discontinuity (RD) designs are increasingly common in political science. They have many advantages, including a known and observable treatment assignment mechanism. The literature has emphasized the need for “falsification tests” and ways to assess the validity of the design. When implementing RD designs, researchers typically rely on two falsification tests, based on empirically testable implications of the identifying assumptions, to argue the design is credible. These tests, one for continuity in the regression function for a pretreatment covariate, and one for continuity in the density of the forcing variable, use a null of no difference in the parameter of interest at the discontinuity. Common practice can, incorrectly, conflate a failure to reject evidence of a flawed design with evidence that the design is credible. The well-known equivalence testing approach addresses these problems, but how to implement equivalence tests in the RD framework is not straightforward. This paper develops two equivalence tests tailored for RD designs that allow researchers to provide statistical evidence that the design is credible. Simulation studies show the superior performance of equivalence-based tests over tests-of-difference, as used in current practice. The tests are applied to the close elections RD data presented in Eggers et al. (2015b).

scholarly journals Past, present, and future of smart learning: a topic-based bibliometric analysis

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Xieling Chen ◽  
Di Zou ◽  
Haoran Xie ◽  
Fu Lee Wang
Keyword(s):  
Cloud Computing ◽  
Blended Learning ◽  
Information And Communication Technologies ◽  
Content Management ◽  
Research Field ◽  
Smart Devices ◽  
Major Research ◽  
Research Issues ◽  
Course Content ◽  
Smart Learning

AbstractInnovative information and communication technologies have reformed higher education from the traditional way to smart learning. Smart learning applies technological and social developments and facilitates effective personalized learning with innovative technologies, especially smart devices and online technologies. Smart learning has attracted increasing research interest from the academia. This study aims to comprehensively review the research field of smart learning by conducting a topic modeling analysis of 555 smart learning publications collected from the Scopus database. In particular, it seeks answers to (1) what the major research topics concerning smart learning were, and (2) how these topics evolved. Results demonstrate several major research issues, for example, Interactive and multimedia learning, STEM (science, technology, engineering, and mathematics) education, Attendance and attention recognition, Blended learning for smart learning, and Affective and biometric computing. Furthermore, several emerging topics were identified, for example, Smart learning analytics, Software engineering for e-learning systems, IoT (Internet of things) and cloud computing, and STEM education. Additionally, potential inter-topic directions were highlighted, for instance, Attendance and attention recognition and IoT and cloud computing, Semantics and ontology and Mobile learning, Feedback and assessment and MOOCs (massive open online courses) and course content management, as well as Blended learning for smart learning and Ecosystem and ambient intelligence.

scholarly journals A Study on Strategic Provisioning of Cloud Computing Services

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Md Whaiduzzaman ◽  
Mohammad Nazmul Haque ◽  
Md Rejaul Karim Chowdhury ◽  
Abdullah Gani
Keyword(s):  
Cloud Computing ◽  
Cloud Service ◽  
Future Research ◽  
User Requirements ◽  
Service Provisioning ◽  
Research Issues ◽  
Computing Services ◽  
Cloud Computing Service ◽  
Essential Services ◽  
Cloud Providers

Cloud computing is currently emerging as an ever-changing, growing paradigm that models “everything-as-a-service.” Virtualised physical resources, infrastructure, and applications are supplied by service provisioning in the cloud. The evolution in the adoption of cloud computing is driven by clear and distinct promising features for both cloud users and cloud providers. However, the increasing number of cloud providers and the variety of service offerings have made it difficult for the customers to choose the best services. By employing successful service provisioning, the essential services required by customers, such as agility and availability, pricing, security and trust, and user metrics can be guaranteed by service provisioning. Hence, continuous service provisioning that satisfies the user requirements is a mandatory feature for the cloud user and vitally important in cloud computing service offerings. Therefore, we aim to review the state-of-the-art service provisioning objectives, essential services, topologies, user requirements, necessary metrics, and pricing mechanisms. We synthesize and summarize different provision techniques, approaches, and models through a comprehensive literature review. A thematic taxonomy of cloud service provisioning is presented after the systematic review. Finally, future research directions and open research issues are identified.

Data center network architecture in cloud computing: review, taxonomy, and open research issues

2014 ◽  
Vol 15 (9) ◽  
pp. 776-793 ◽  
Author(s):  
Han Qi ◽  
Muhammad Shiraz ◽  
Jie-yao Liu ◽  
Abdullah Gani ◽  
Zulkanain Abdul Rahman ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Center ◽  
Network Architecture ◽  
Data Center Network ◽  
Research Issues ◽  
Open Research

scholarly journals Experimental Study of SaaS, Its Categories and Contribution in Cloud Computing

2022 ◽  
Vol 71 (1) ◽  
Author(s):  
Dr Anand Sharma
Keyword(s):  
Experimental Study ◽  
Cloud Computing ◽  
Distributed System ◽  
Service Provider ◽  
Software As A Service ◽  
Application Service Provider ◽  
Client Server ◽  
Application Service

SaaS is software as a service. In previous days when the concept of providing the facility of distributed system from where information can be shared was introduced then the concept of Application service provider came into the picture. The idea was to provide application-based services to the companies using client server techniques. It became popular. SaaS is introduced to provide software also as a service which is upgraded version of the ASP. In this paper SaaS will be discussed in detail. There are two main types of SaaS. The challenges in implementation of SaaS will also be discussed.

Cloud Security

2015 ◽  
pp. 236-250
Author(s):  
Natasha Csicsmann ◽  
Victoria McIntyre ◽  
Patrick Shea ◽  
Syed S. Rizvi
Keyword(s):  
Cloud Computing ◽  
Performance Analysis ◽  
Large Scale ◽  
Research Issues ◽  
Biometric Technology ◽  
Cloud Computing Security ◽  
Security Technologies ◽  
Encryption Schemes ◽  
Computing Platforms ◽  
Cloud Auditing

Strong authentication and encryption schemes help cloud stakeholders in performing the robust and accurate cloud auditing of a potential service provider. All security-related issues and challenges, therefore, need to be addressed before a ubiquitous adoption of cloud computing. In this chapter, the authors provide an overview of existing biometrics-based security technologies and discuss some of the open research issues that need to be addressed for making biometric technology an effective tool for cloud computing security. Finally, this chapter provides a performance analysis on the use of large-scale biometrics-based authentication systems for different cloud computing platforms.

Unit of Analysis in Digitally-Enabled Electronic Procurement Research

2020 ◽  
pp. 83-103
Author(s):  
Md Mahbubur Rahim ◽  
Maryam Jabberzadeh ◽  
Nergiz Ilhan
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Critical Issue ◽  
Future Research ◽  
Research Directions ◽  
Research Issues ◽  
Unit Of Analysis ◽  
Electronic Procurement ◽  
Future Research Directions ◽  
Methodological Concern

E-procurement systems that have been in place for over a decade have begun incorporating digital tools like big data, cloud computing, internet of things, and data mining. Hence, there exists a rich literature on earlier e-procurement systems and advanced digitally-enabled e-procurement systems. Existing literature on these systems addresses many research issues (e.g., adoption) associated with e-procurement. However, one critical issue that has so far received no rigorous attention is about “unit of analysis,” a methodological concern of importance, for e-procurement research context. Hence, the aim of this chapter is twofold: 1) to discuss how the notion of “unit of analysis” has been conceptualised in the e-procurement literature and 2) to discuss how its use has been justified by e-procurement scholars to address the research issues under investigation. Finally, the chapter provides several interesting findings and outlines future research directions.

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