Green Cloud Computing

2014 ◽  
pp. 202-214 ◽  
Author(s):  
Haibo Wang ◽  
Da Huo
Keyword(s):  
Cloud Computing ◽  
Site Selection ◽  
Social Issues ◽  
Multiple Criteria Decision Making ◽  
Neighborhood Search ◽  
Solution Approach ◽  
Proposed Model ◽  
Selection Decision ◽  
Decision Making Model ◽  
Solution Methodology

This chapter considers the data center site selection problem in cloud computing with extensive reviews on site selection decision models. The factors considered in the site selection include economic, environmental, and social issues. After discussing the environmental impact of data centers and its social implications, the authors present a nonlinear multiple criteria decision-making model with green computing criteria and solve the problem by using a variable neighborhood search heuristic. The proposed model and solution methodology can be applied to other site selection problems to address the environmental awareness, and the results illustrate both the robustness and attractiveness of this solution approach.

scholarly journals A Novel Vaccine Selection Decision-Making Model (VSDMM) for COVID-19

Vaccines ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 718
Author(s):  
Sayed F. Abdelwahab ◽  
Usama H. Issa ◽  
Hossam M. Ashour
Keyword(s):  
Decision Making ◽  
Cost Savings ◽  
Analytic Hierarchy ◽  
Related Factors ◽  
Proposed Model ◽  
Criteria Weights ◽  
Selection Decision ◽  
Vaccine Availability ◽  
Decision Making Model ◽  
Hierarchy Process

Selecting a vaccine for fighting a pandemic is one of the serious issues in healthcare. Novel decision models for vaccine selection need to be developed. In this study, a novel vaccine selection decision-making model (VSDMM) was proposed and developed, based on the analytic hierarchy process (AHP) technique, which assesses many alternatives (vaccines) using multi-criteria to support decision making. To feed data to the VSDMM, six coronavirus disease-19 (COVID-19) vaccines were selected in a case study to highlight the applicability of the proposed model. Each vaccine was compared to the others with respect to six criteria and all criteria were compared to calculate the relative weights. The proposed criteria include (1) vaccine availability; (2) vaccine formula; (3) vaccine efficacy; (4) vaccine-related side effects; (5) cost savings, and (6) host-related factors. Using the selected criteria, experts responded to questions and currently available COVID-19 vaccines were ranked according to their weight in the model. A sensitivity analysis was introduced to assess the model robustness and the impacts of changing criteria weights on the results. The VSDMM is flexible in terms of its ability to accept more vaccine alternatives and/or more criteria. It could also be applied to other current or future pandemics/epidemics in the world. In conclusion, this is the first report to propose a VSDMM for selecting the most suitable vaccines in pandemic/epidemic situations or any other situations in which vaccine selection and usage may be deemed necessary.

A Novel Integrated Strategic Portfolio Decision-Making Model

2017 ◽  
Vol 8 (3) ◽  
pp. 1-44 ◽  
Author(s):  
Darius Danesh ◽  
Michael J. Ryan ◽  
Alireza Abbasi
Keyword(s):  
Decision Making ◽  
Data Envelopment ◽  
Analytic Hierarchy ◽  
Expected Return ◽  
Proposed Model ◽  
Selection Decision ◽  
Portfolio Decision ◽  
Novel Method ◽  
Decision Making Model ◽  
Hierarchy Process

This study proposes a novel method for portfolio selection/decision making that combines the Portfolio Theory (PT), Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA) cross-efficiency technique. It takes into account the profits, risks and proficiency of a portfolio and is shown to be useful for selecting one with positive and negative data and subsequently measuring its efficiency using AHP, with a consistency test conducted to verify the objectivity of the results. To test the applicability of the proposed model, it is used to determine the efficiency levels of ten of the largest companies in Australia for the years 2014 and 2015. Two criteria, namely, the expected return and variance, are used to identify the preference status of each company. The results indicate that the proposed model is feasible and adoptable for the contemporary industrial scenario as it simultaneously analyses profits, risks and proficiency.

scholarly journals A Hybrid Mathematical and Decision-Making Model to Determine the Amount of Economic Order considering the Discount

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Hanif Hazrati ◽  
Abbas Barzegarinegad ◽  
Hamid Siaby-Serajehlo
Keyword(s):  
Analytic Hierarchy ◽  
Heuristic Solution ◽  
Solution Approach ◽  
Proposed Model ◽  
Comparison Results ◽  
Business Conditions ◽  
The Cost ◽  
Analytic Hierarchy Process Method ◽  
Ordering Systems ◽  
Decision Making Model

Suppliers are one of the most important parts of the supply chain, whose performance indirectly has a significant impact on customer satisfaction. Because customer demands are different from organizations, organizations have to consider different criteria for selecting their suppliers. In recent years, many studies in this field have been conducted using various criteria and methods. The main purpose defined in this research is to develop a model for simultaneous item ordering systems in real business conditions. In this research, a model is developed by considering the two objectives of minimizing overall costs and maximizing the amount of products ordered from different suppliers based on their weight value. Weights are calculated based on different criteria using the fuzzy analytic hierarchy process method for each supplier in different periods. Then, due to the multiobjective nature of the model, the proposed model has been solved by using the epsilon constraint in GAMS and nondominated sorting genetic algorithm II in MATLAB software. Considering the simultaneous order of inventory of multiproduct with several suppliers in several periods of time in discrete space with discount is one of the contributions of this research. To validate the proposed model, the results of the exact solution are compared with the meta-heuristic solution. Comparison results and assessment metrics indicate that the results of the proposed solution approach with an error of less than 1% had good performance. The results show that the system cost increases, by increasing the amount of discount, because of the increase in the amount of demand. Therefore, with a 30% increase in the discount, the system costs will increase to 36,496 units. Also, with a 20% reduction, the cost reduction will be reduced to 14,170 units.

A Circular Business Model for Cloud Computing Services Providers

10.31355/33 ◽  
2018 ◽  
Vol 2 ◽  
pp. 105-120
Author(s):  
Hamed Motaghi ◽  
Saeed Nosratabadi ◽  
Thabit Qasem Atobishi
Keyword(s):  
Cloud Computing ◽  
Business Model ◽  
Circular Economy ◽  
Service Providers ◽  
Sustainable Consumption ◽  
Future Research ◽  
Extensive Literature ◽  
Computing Services ◽  
Proposed Model ◽  
Cloud Computing Service

NOTE: THIS ARTICLE WAS PUBLISHED WITH THE INFORMING SCIENCE INSTITUTE. Aim/Purpose................................................................................................................................................................................................. The main objective of the current study is to develop a business model for service providers of cloud computing which is designed based on circular economy principles and can ensure the sustainable consumption. Background Even though the demand for cloud computing technology is increasing day by day in all over the world, the current the linear economy principles are incapable to ensure society development needs. To consider the benefit of the society and the vendors at the same time, the principles of circular economy can address this issue. Methodology................................................................................................................................................................................................. An extensive literature review on consumption, sustainable consumption, circular economic, business model, and cloud computing were conducted. the proposed model of Osterwalder, Pigneur and Tucci (2005) is admitted designing the circular business model. Contribution................................................................................................................................................................................................. The proposed model of the study is the contribution of this study where provides the guidelines for the cloud computing service providers to achieve both their economic profits and the society’ needs. Findings Finding reveals that if the cloud computing service providers design their business model based on the “access” principle of circular economy, they can meet their economic profits and the society’ needs at a same time. Recommendations for Practitioners.............................................................................................................................................................. It is recommended to the startup and the existing businesses to utilize the proposed model of this study to reach a sustainable development. Recommendation for Researchers................................................................................................................................................................ It proposes a new circular business model and its linkages with community building. Impact on Society............................................................................................................................................................................................ The proposed model of the study provides guidelines to the cloud computing service providers to design a business model which is able not only to meet their economic profit, but also to meet the society’s and customers’ benefits. Future Research............................................................................................................................................................................................... Future researches can build on this research model which proposed in this study to examine the limitations of this model by using empirical researches.

scholarly journals Evaluating the Application of CSR in the High-Tech Industry during the COVID-19 Pandemic

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1715
Author(s):  
Shih-Chia Chang ◽  
Ming-Tsang Lu ◽  
Mei-Jen Chen ◽  
Li-Hua Huang
Keyword(s):  
Management Practices ◽  
Social Issues ◽  
Empirical Studies ◽  
Multiple Criteria Decision Making ◽  
Sustainable Growth ◽  
High Tech ◽  
High Tech Industry ◽  
Continuous Growth ◽  
Csr Strategies ◽  
Corporate Social

Since its conception, corporate social responsibility (CSR) has seen continuous growth and become a highly discussed issue. In this paper, we propose an evaluation of how the COVID-19 pandemic could impact CSR applications. The pandemic has provided an opportunity for commerce to move on to being more authentic, to offer genuine CSR applications and to contribute toward dealing with pressing environmental and social issues. Hence, this purpose of the research is to obtain a better understanding of whether the integration of environment, social, corporate governance and economic (ESGE) aspects into CSR strategies can support sustainable development toward more sustainable growth during the COVID-19 pandemic. To meet this challenge, we offer a mixture multiple-criteria decision making (MCDM) model. Very few empirical studies have discussed CSR in the high-tech industry and proposed strategies and planning for ESGE efficiency. Using interviews with experts and a literature review, we identify the elements related to actual practices of the high-tech industry’s appraisal and the integrated MCDM techniques to suggest efficient enhancement models. The best worst method (BWM) and modified VIKOR are implemented to estimate the strategic weights and the gaps of the aspiration value. The results are valuable for classifying the priorities of CSR and are therefore helpful for those who are associated with high-tech industry management, practices and implementation.

scholarly journals Evaluating the E-Health Cloud Computing Systems Adoption in Taiwan’s Healthcare Industry

Life ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 310
Author(s):  
Shih-Chia Chang ◽  
Ming-Tsang Lu ◽  
Tzu-Hui Pan ◽  
Chiao-Shan Chen
Keyword(s):  
Decision Making ◽  
Cloud Computing ◽  
Multiple Criteria Decision Making ◽  
Cloud Service ◽  
Computing System ◽  
Healthcare Industry ◽  
Computing Systems ◽  
Factors Affecting ◽  
Cloud Computing System ◽  
Health Cloud

Although the electronic health (e-health) cloud computing system is a promising innovation, its adoption in the healthcare industry has been slow. This study investigated the adoption of e-health cloud computing systems in the healthcare industry and considered security functions, management, cloud service delivery, and cloud software for e-health cloud computing systems. Although numerous studies have determined factors affecting e-health cloud computing systems, few comprehensive reviews of factors and their relations have been conducted. Therefore, this study investigated the relations between the factors affecting e-health cloud computing systems by using a multiple criteria decision-making technique, in which decision-making trial and evaluation laboratory (DEMATEL), DANP (DEMATEL-based Analytic Network Process), and modified VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) approaches were combined. The intended level of adoption of an e-health cloud computing system could be determined by using the proposed approach. The results of a case study performed on the Taiwanese healthcare industry indicated that the cloud management function must be primarily enhanced and that cost effectiveness is the most significant factor in the adoption of e-health cloud computing. This result is valuable for allocating resources to decrease performance gaps in the Taiwanese healthcare industry.

scholarly journals Cloud-based intelligent self-diagnosis and department recommendation service using Chinese medical BERT

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Junshu Wang ◽  
Guoming Zhang ◽  
Wei Wang ◽  
Ka Zhang ◽  
Yehua Sheng
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Medical Service ◽  
Rapid Development ◽  
Medical Knowledge ◽  
Language Models ◽  
Computing Environment ◽  
Computing Power ◽  
Cloud Computing Environment ◽  
Proposed Model

AbstractWith the rapid development of hospital informatization and Internet medical service in recent years, most hospitals have launched online hospital appointment registration systems to remove patient queues and improve the efficiency of medical services. However, most of the patients lack professional medical knowledge and have no idea of how to choose department when registering. To instruct the patients to seek medical care and register effectively, we proposed CIDRS, an intelligent self-diagnosis and department recommendation framework based on Chinese medical Bidirectional Encoder Representations from Transformers (BERT) in the cloud computing environment. We also established a Chinese BERT model (CHMBERT) trained on a large-scale Chinese medical text corpus. This model was used to optimize self-diagnosis and department recommendation tasks. To solve the limited computing power of terminals, we deployed the proposed framework in a cloud computing environment based on container and micro-service technologies. Real-world medical datasets from hospitals were used in the experiments, and results showed that the proposed model was superior to the traditional deep learning models and other pre-trained language models in terms of performance.

Proposed Back Propagation Deep Neural Network for Intrusion Detection in Internet of Things Fog Computing

2021 ◽  
Vol 9 (4) ◽  
pp. 464-469
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Fog Computing ◽  
Denial Of Service ◽  
Back Propagation ◽  
Security And Privacy ◽  
Brute Force ◽  
Iot Platform ◽  
Proposed Model

Internet of things (IoT) is an emerging concept which aims to connect billions of devices with each other anytime regardless of their location. Sadly, these IoT devices do not have enough computing resources to process huge amount of data. Therefore, Cloud computing is relied on to provide these resources. However, cloud computing based architecture fails in applications that demand very low and predictable latency, therefore the need for fog computing which is a new paradigm that is regarded as an extension of cloud computing to provide services between end users and the cloud user. Unfortunately, Fog-IoT is confronted with various security and privacy risks and prone to several cyberattacks which is a serious challenge. The purpose of this work is to present security and privacy threats towards Fog-IoT platform and discuss the security and privacy requirements in fog computing. We then proceed to propose an Intrusion Detection System (IDS) model using Standard Deep Neural Network's Back Propagation algorithm (BPDNN) to mitigate intrusions that attack Fog-IoT platform. The experimental Dataset for the proposed model is obtained from the Canadian Institute for Cybersecurity 2017 Dataset. Each instance of the attack in the dataset is separated into separate files, which are DoS (Denial of Service), DDoS (Distributed Denial of Service), Web Attack, Brute Force FTP, Brute Force SSH, Heartbleed, Infiltration and Botnet (Bot Network) Attack. The proposed model is trained using a 3-layer BP-DNN

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