A holistic low carbon city indicator framework for sustainable development

Tan, Sie Ting; Yang, Jin; Yan, Jinyue; Lee, Chew Tin; Hashim, Haslenda; Chen, Bin

doi:10.1016/j.apenergy.2016.03.041

Cited by 253 publications

(111 citation statements)

References 26 publications

(40 reference statements)

Supporting

Mentioning

102

Contrasting

Unclassified

Order By: Relevance

“…Besides, the consolidate certain-uncertain system is depicted from three aspects which are: identity, discrepancy, and contrary. Consequently, SPA has been successfully applied in many fields including smart cities' innovation ecosystem [83,84], forecasting [85], geology [86], and cloud computing [24], etc. However, they are not yet used in the mobile cloud offloading process.…”

Section: Uncertainty and Fuzzy Methodsmentioning

confidence: 99%

Multi-Criteria Decision Analysis Methods in the Mobile Cloud Offloading Paradigm

Bangui

Bühnová

et al. 2017

JSAN

View full text Add to dashboard Cite

Abstract:Mobile cloud computing (MCC) is becoming a popular mobile technology that aims to augment local resources of mobile devices, such as energy, computing, and storage, by using available cloud services and functionalities. The offloading process is one of the techniques used in MCC to enhance the capabilities of mobile devices by moving mobile data and computation-intensive operations to cloud platforms. Several techniques have been proposed to perform and improve the efficiency and effectiveness of the offloading process, such as multi-criteria decision analysis (MCDA). MCDA is a well-known concept that aims to select the best solution among several alternatives by evaluating multiple conflicting criteria, explicitly in decision making. However, as there are a variety of platforms and technologies in mobile cloud computing, it is still challenging for the offloading process to reach a satisfactory quality of service from the perspective of customers' computational service requests. Thus, in this paper, we conduct a literature review that leads to a better understanding of the usability of the MCDA methods in the offloading operation that is strongly reliant on the mobile environment, network operators, and cloud services. Furthermore, we discuss the challenges and opportunities of these MCDA techniques for offloading research in mobile cloud computing. Finally, we recommend a set of future research directions in MCDA used for the mobile cloud offloading process.

show abstract

Section: Uncertainty and Fuzzy Methodsmentioning

confidence: 99%

Multi-Criteria Decision Analysis Methods in the Mobile Cloud Offloading Paradigm

Bangui

Bühnová

et al. 2017

JSAN

View full text Add to dashboard Cite

show abstract

“…They argued that the innovation system presents a series of strengths as well. Some big cities are trying to reduce carbon emission and environmental protection [15].…”

Section: Review Of Related Workmentioning

confidence: 99%

“…But if China adopts the low carbon technology and strategy in its economic pattern, it is possible to reduce 20% GHG emission by 2030 [38]. A strategic vision should be taken by the authority of China for reducing carbon emission by adopting industrial restructuring, changing lifestyle, more efficiency in transport, industrial endues, building and electricity efficiency, and improving energy sector by using clean renewable energy [15].…”

Section: Current Status Of Low Carbon Economymentioning

confidence: 99%

“…Therefore, it creates vulnerability in the management of energy. China can easily take opportunities for energy saving and low carbon emission through technological innovation, management and restructuring of [15]. In case of innovation and cooperation of carbon emission technologies, China has a big potential.…”

Section: Opportunities For China's Low Carbon Economy Developmentmentioning

confidence: 99%

See 1 more Smart Citation

Practices of Low Carbon Economy in China: Challenges and Opportunities for Economic Development

Sarker¹,

Hossin²,

Anusara³

et al. 2018

LCE

View full text Add to dashboard Cite

Global warming is a major concern in the globalized world in the aspect of industrialization. Low carbon practices are the major strategies to control global warming. Low carbon economy is the fundamental pattern of the mainstream economy in the perspective of ecology. The aim of this study is to explore the status of low carbon economy of China through assessing low carbon practices. It also finds out the challenges and opportunities of low carbon practices for sustainable economic development. An extensive literature review with meta-analysis has been done considering various indicators of low carbon practices. The study explores that China already adopted some policy, strategy, and practices regarding low carbon economy. China already set its policy regarding control of carbon emission by 2030. Research and innovation in low carbon practices, low carbon industrial structure, low carbon technology adoption and emphasizes on environmental sustainability are the major initiatives of China for low carbon economy. Major challenges regarding low carbon practices are heavy pressure on carbon emission, heavy industrialization, extensive development stream, resource endowment, unplanned industrial structure and trade, and confusion regarding industrial transformation. This study suggests that vigorous and efficient planning in industrialization, improved technology adoption, ecological consideration in every project and sufficient finance are necessary to obtain better low carbon economy in China.

show abstract

“…Zhang et al [10] considered that the exploitation of residual coal can effectively delay China's coal depletion, inhibit the construction of new mines, redress the imbalance between supply and demand of coal in eastern China, improve the mining area environment and guarantee social stability. Tan et al [11] considered different development categories including economic, social and environmental factors with different indicators. Lin et al [12] aimed to integrate performance and importance levels using quantitative and qualitative information with a modified balanced scorecard model.…”

mentioning

confidence: 99%

Intelligent Urban Sustainable Development Plan

Ku¹,

Liao²

2017

JAMP

View full text Add to dashboard Cite

Based on the entropy weight method and the gray relational analysis method, we first calculate the weight of each index and the correlation coefficient between the indicators, get the urban intelligent growth index, and then calculate the annual growth rate of the composite index. We find the following results. First, Suzhou to improve its environment, the success rate of 109.67%. Saint Louis to improve its economy, the growth rate of 57.4%. Second, the sensitivity of the data analysis, each of the indicators is increased by 10%, 20%, 30%, other indicators remain unchanged. Recalculate the city's intelligent growth index, we find that the greater the volatility, the greater the potential. The total population of the city, built green area, the total length of the bus operating a greater potential, built-up area, the smallest regional GDP potential. Finally, we propose an improved model combining remote sensing with GIS to analyze urban expansion and farmland loss from time and space qualitatively and quantitatively.

show abstract

A holistic low carbon city indicator framework for sustainable development

Cited by 253 publications

References 26 publications

Multi-Criteria Decision Analysis Methods in the Mobile Cloud Offloading Paradigm

Multi-Criteria Decision Analysis Methods in the Mobile Cloud Offloading Paradigm

Practices of Low Carbon Economy in China: Challenges and Opportunities for Economic Development

Intelligent Urban Sustainable Development Plan

Contact Info

Product

Resources

About