The standardised IT paradigm pools services together as an internet network is cloud computing. So, management of the load by cloud providers at this point is difficult and hence manifests the existence of load balancing concept. The aim of proposed algorithm is to enhance the performance by minimizing results, which includes Execution time, Makespan time, and Processing Cost, and maximizing throughput, using ABC Optimization. R code is used to execute the algorithm, and dataset is processed using Microsoft Excel 2007. In the dataset, the MIPS of VMs range from 2000-9000 and bandwidth range from 10000-50000. Finally, it is concluded that, for 3 clusters, the efficiency rate of execution time, makespan time, and processing cost lies between 18%-20% and throughput and degree of imbalance are approximately 16% and 6%, respectively, when compared with the previous work; and for 10 clusters, the efficiency rate of execution time and makespan time raises to approximately 50% with processing cost, throughput, and degree of imbalance as approximately 72%, 33%, and 4%, respectively.
{"title":"Cloudlet and Virtual Machine Performance Enhancement With CLARA and Evolutionary Paradigm","authors":"Tanvi Gupta, Supriya P. Panda","doi":"10.4018/ijcac.298322","DOIUrl":"https://doi.org/10.4018/ijcac.298322","url":null,"abstract":"The standardised IT paradigm pools services together as an internet network is cloud computing. So, management of the load by cloud providers at this point is difficult and hence manifests the existence of load balancing concept. The aim of proposed algorithm is to enhance the performance by minimizing results, which includes Execution time, Makespan time, and Processing Cost, and maximizing throughput, using ABC Optimization. R code is used to execute the algorithm, and dataset is processed using Microsoft Excel 2007. In the dataset, the MIPS of VMs range from 2000-9000 and bandwidth range from 10000-50000. Finally, it is concluded that, for 3 clusters, the efficiency rate of execution time, makespan time, and processing cost lies between 18%-20% and throughput and degree of imbalance are approximately 16% and 6%, respectively, when compared with the previous work; and for 10 clusters, the efficiency rate of execution time and makespan time raises to approximately 50% with processing cost, throughput, and degree of imbalance as approximately 72%, 33%, and 4%, respectively.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127867634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nowadays, electric vehicles (e-vehicles) have a significant impact on the current intelligent transportation system, with the goal of establishing a smart environment in the near future. Furthermore, when an intelligent system is integrated with IoT technologies, it produces more efficient results to the society. This research work examines the impact of energy degradation on the wireless transmission to optimize power consumption using a passive-awake cloud-cluster communication system, thereby extending the lifetime of an energy-constrained electric vehicle. Wireless communication means that electromagnetic waves draining a steady amount of energy from the condenser, even if the device is not connected to the internet, which constitutes the main constraint for a long-distance electric vehicle. In this paper, a passive-awake assistant is proposed, which significantly reduces power consumption.
{"title":"Passive-Awake Energy Conscious Power Consumption in Smart Electric Vehicles Using Cluster Type Cloud Communication","authors":"P. Vijayakumar, S. Rajkumar, L. Deborah","doi":"10.4018/ijcac.297108","DOIUrl":"https://doi.org/10.4018/ijcac.297108","url":null,"abstract":"Nowadays, electric vehicles (e-vehicles) have a significant impact on the current intelligent transportation system, with the goal of establishing a smart environment in the near future. Furthermore, when an intelligent system is integrated with IoT technologies, it produces more efficient results to the society. This research work examines the impact of energy degradation on the wireless transmission to optimize power consumption using a passive-awake cloud-cluster communication system, thereby extending the lifetime of an energy-constrained electric vehicle. Wireless communication means that electromagnetic waves draining a steady amount of energy from the condenser, even if the device is not connected to the internet, which constitutes the main constraint for a long-distance electric vehicle. In this paper, a passive-awake assistant is proposed, which significantly reduces power consumption.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116642795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
B. Joshi, Bansidhar Joshi, Anupama Mishra, Varsha Arya, A. Gupta, D. Peraković
In cloud computing, a third party hosts a client's data, which raises privacy and security concerns. To maintain privacy, data should be encrypted by cryptographic techniques. However, encrypting the data makes it unsuitable for indexing and fast processing, as data needs to be decrypted to plain text before it can be further processed. Homomorphic encryption helps to overcome this shortcoming by allowing users to perform operations on encrypted data without decryption. Many academics have attempted to address the issue of data security, but none have addressed the issue of data privacy in cloud computing as thoroughly as this study has. This paper discusses the challenges involved in maintaining the privacy of cloud-based data and the techniques used to address these challenges. It was identified that homomorphic encryption is the best solution of all. This work also identified and compared the various homomorphic encryption schemes which are capable of ensuring the privacy of data in cloud storage and ways to implement them through libraries.
{"title":"A Comparative Study of Privacy-Preserving Homomorphic Encryption Techniques in Cloud Computing","authors":"B. Joshi, Bansidhar Joshi, Anupama Mishra, Varsha Arya, A. Gupta, D. Peraković","doi":"10.4018/ijcac.309936","DOIUrl":"https://doi.org/10.4018/ijcac.309936","url":null,"abstract":"In cloud computing, a third party hosts a client's data, which raises privacy and security concerns. To maintain privacy, data should be encrypted by cryptographic techniques. However, encrypting the data makes it unsuitable for indexing and fast processing, as data needs to be decrypted to plain text before it can be further processed. Homomorphic encryption helps to overcome this shortcoming by allowing users to perform operations on encrypted data without decryption. Many academics have attempted to address the issue of data security, but none have addressed the issue of data privacy in cloud computing as thoroughly as this study has. This paper discusses the challenges involved in maintaining the privacy of cloud-based data and the techniques used to address these challenges. It was identified that homomorphic encryption is the best solution of all. This work also identified and compared the various homomorphic encryption schemes which are capable of ensuring the privacy of data in cloud storage and ways to implement them through libraries.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"829 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116422295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To save money on maintenance and administrative costs, cloud computing aims to move high-end computer equipment to the internet and put it online. Both victims and attackers may reap the advantages of cloud computing. On the other side, attacks on cloud components might lead to massive losses for cloud service providers and users. Numerous cyber-attacks have been launched as a consequence of this readily available resource. One of the most significant hazards to communication networks and applications has long been DoS and DDoS attacks. Operations, availability, and security for companies are becoming a nightmare because of these attacks. Since cloud computing resources are scalable, these resources may be dynamically scaled to recognise the attack components and immediately withstand the attack. For this cyber-attack against cloud computing, fast exploitation of the attack data is necessary. This article addresses the majority of the previously published strategies for DDoS attack avoidance, early identification, and remediation.
{"title":"A Review on Detection and Mitigation Analysis of Distributed Denial of Service Attacks and Their Effects on the Cloud","authors":"S. Devi, Tarannam Bharti","doi":"10.4018/ijcac.311036","DOIUrl":"https://doi.org/10.4018/ijcac.311036","url":null,"abstract":"To save money on maintenance and administrative costs, cloud computing aims to move high-end computer equipment to the internet and put it online. Both victims and attackers may reap the advantages of cloud computing. On the other side, attacks on cloud components might lead to massive losses for cloud service providers and users. Numerous cyber-attacks have been launched as a consequence of this readily available resource. One of the most significant hazards to communication networks and applications has long been DoS and DDoS attacks. Operations, availability, and security for companies are becoming a nightmare because of these attacks. Since cloud computing resources are scalable, these resources may be dynamically scaled to recognise the attack components and immediately withstand the attack. For this cyber-attack against cloud computing, fast exploitation of the attack data is necessary. This article addresses the majority of the previously published strategies for DDoS attack avoidance, early identification, and remediation.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"165 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125968756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The challenge in cloud services is scheduling and allocating resources due to the exponential growth in demand and diversity of cloud resources. Scheduling is to allocate tasks across cloud resources so that scheduling algorithms reduce power consumption and offer cloud providers maximum return by reducing execution time. Various QoS parameters (such as makespan, load balancing, costs, etc.) are considered for efficient scheduling to reduce workload and enhance performance. Through this framework, multi-objective scheduling is a decision-making problem with multiple attributes considering the trade-off between the conflicting and competing parameters mentioned in the SLA between users and providers. This paper summarizes various multi-objective scheduling algorithms that consider contradictory and competing parameters or constraints to be optimized simultaneously. These algorithms are finally tabulated, presenting their advantages and disadvantages with cloud simulation tools and other QoS related parameters.
{"title":"A Survey on Multi-Objective Tasks and Workflow Scheduling Algorithms in Cloud Computing","authors":"Rajeshwari Sissodia, M. Rauthan, Kanchan Naithani","doi":"10.4018/ijcac.297100","DOIUrl":"https://doi.org/10.4018/ijcac.297100","url":null,"abstract":"The challenge in cloud services is scheduling and allocating resources due to the exponential growth in demand and diversity of cloud resources. Scheduling is to allocate tasks across cloud resources so that scheduling algorithms reduce power consumption and offer cloud providers maximum return by reducing execution time. Various QoS parameters (such as makespan, load balancing, costs, etc.) are considered for efficient scheduling to reduce workload and enhance performance. Through this framework, multi-objective scheduling is a decision-making problem with multiple attributes considering the trade-off between the conflicting and competing parameters mentioned in the SLA between users and providers. This paper summarizes various multi-objective scheduling algorithms that consider contradictory and competing parameters or constraints to be optimized simultaneously. These algorithms are finally tabulated, presenting their advantages and disadvantages with cloud simulation tools and other QoS related parameters.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127240275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The most valuable asset for any organization and individual is data and the information it holds. This is the main reason for Information Security to be the top concern in boardrooms and executive meetings. Security failures and data breaches now can impact an organization or a country's budget economy. To reduce Cybersecurity risks and improve data protection, there is an urgent need to implement a standard Framework for Cybersecurity. This framework utilizes AI and ML by including Policies, Guidelines, Standards and Practices, and data sources from Cloud Infrastructure systems like networks, servers, security systems, and end-user devices. Combining the data set gathered and risk governance information with Artificial Intelligence and Machine Learning. This research presents a framework that collects datasets, enriches and validates logs and datasets, then correlates them to analyze and predict the response to Cyber attack with high level of accuracy using ML model.
{"title":"Predictive Analytics-Based Cybersecurity Framework for Cloud Infrastructure","authors":"Akashdeep Bhardwaj, Keshav Kaushik","doi":"10.4018/ijcac.297106","DOIUrl":"https://doi.org/10.4018/ijcac.297106","url":null,"abstract":"The most valuable asset for any organization and individual is data and the information it holds. This is the main reason for Information Security to be the top concern in boardrooms and executive meetings. Security failures and data breaches now can impact an organization or a country's budget economy. To reduce Cybersecurity risks and improve data protection, there is an urgent need to implement a standard Framework for Cybersecurity. This framework utilizes AI and ML by including Policies, Guidelines, Standards and Practices, and data sources from Cloud Infrastructure systems like networks, servers, security systems, and end-user devices. Combining the data set gathered and risk governance information with Artificial Intelligence and Machine Learning. This research presents a framework that collects datasets, enriches and validates logs and datasets, then correlates them to analyze and predict the response to Cyber attack with high level of accuracy using ML model.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131246256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cloud and fog computing are modern technologies that handle multiple dynamic user requests. Cloud provides demand-based services to users over the internet on pay-as-you-go basis. Fog handles real-time requests that are received from smart devices. Millions of requests arrive at the cloud-fog layer, often leading to overloaded virtual machines (VMs). Load balancing (LB) is an important issue for cloud-fog systems and has been proved to be an NP-hard problem. It is essential as it distributes the load equally among VMs to properly utilize resources and improve quality of service (QoS). Therefore, this paper presents a complete classification of LB algorithms and also a comprehensive study using heuristic, meta-heuristic, and hybrid approaches in cloud and fog computing environments. The main goal of this paper is to highlight the importance of LB to overcome the challenges of the systems. This study reviews papers of the last seven years and systematically discusses them using various tables and pie charts. Finally, the paper concludes with the research gaps and future insights.
{"title":"Load Balancing Approaches in Cloud and Fog Computing Environments: A Framework, Classification, and Systematic Review","authors":"Hiba Shakeel, M.Aftab Alam","doi":"10.4018/ijcac.311503","DOIUrl":"https://doi.org/10.4018/ijcac.311503","url":null,"abstract":"Cloud and fog computing are modern technologies that handle multiple dynamic user requests. Cloud provides demand-based services to users over the internet on pay-as-you-go basis. Fog handles real-time requests that are received from smart devices. Millions of requests arrive at the cloud-fog layer, often leading to overloaded virtual machines (VMs). Load balancing (LB) is an important issue for cloud-fog systems and has been proved to be an NP-hard problem. It is essential as it distributes the load equally among VMs to properly utilize resources and improve quality of service (QoS). Therefore, this paper presents a complete classification of LB algorithms and also a comprehensive study using heuristic, meta-heuristic, and hybrid approaches in cloud and fog computing environments. The main goal of this paper is to highlight the importance of LB to overcome the challenges of the systems. This study reviews papers of the last seven years and systematically discusses them using various tables and pie charts. Finally, the paper concludes with the research gaps and future insights.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131269123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To manage all the operations of data centers resources, virtualization is the effective technique. In virtualization the virtual machine migration is the way by which data center operator can easily adapt the replacement of virtual machine, improves the resource provisioning and any other maintenance function of data center. Despite of this the virtual machine migration scheme is the major challenge to improve the efficiency of data center. This paper proposed a virtual machine migration process which will be responsible to minimize the migration which leads to reduce the execution time.
{"title":"An Adaptive Mechanism for Virtual Machine Migration in the Cloud Environment","authors":"Gurpreet Singh, M. Malhotra, A. Sharma","doi":"10.4018/ijcac.297095","DOIUrl":"https://doi.org/10.4018/ijcac.297095","url":null,"abstract":"To manage all the operations of data centers resources, virtualization is the effective technique. In virtualization the virtual machine migration is the way by which data center operator can easily adapt the replacement of virtual machine, improves the resource provisioning and any other maintenance function of data center. Despite of this the virtual machine migration scheme is the major challenge to improve the efficiency of data center. This paper proposed a virtual machine migration process which will be responsible to minimize the migration which leads to reduce the execution time.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134071092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. G. Peñalvo, Akash Sharma, Anureet Chhabra, S. K. Singh, Sudhakar Kumar, Varsha Arya, Akshat Gaurav
The number of smartphone users has increased from 3.6 billion in 2016 to 6.25 billion by 2021, which shows that mobile phone usage has increased dramatically over the past few years. This is due to the development of mobile computing applications like commerce, healthcare, e-learning, etc. The use of mobile devices has resulted in an exponential rise in the amount of data generated and as a result the amount of energy consumed has increased. This is where cloud computing plays a major role. Cloud computing has transformed traditional mobile computing. The new mobile cloud not only provides on-demand services but also data storage and increased energy efficiency. Through mobile computing based on cloud computing, mobile device functions can be virtualized, reducing power consumption. In this paper, the authors survey application and potential of mobile cloud computing and present the energy-efficient ways. Also, the paper discusses development opportunities of mobile cloud computing. The research also mentions some of the major challenges in current mobile computing technology.
{"title":"Mobile Cloud Computing and Sustainable Development: Opportunities, Challenges, and Future Directions","authors":"F. G. Peñalvo, Akash Sharma, Anureet Chhabra, S. K. Singh, Sudhakar Kumar, Varsha Arya, Akshat Gaurav","doi":"10.4018/ijcac.312583","DOIUrl":"https://doi.org/10.4018/ijcac.312583","url":null,"abstract":"The number of smartphone users has increased from 3.6 billion in 2016 to 6.25 billion by 2021, which shows that mobile phone usage has increased dramatically over the past few years. This is due to the development of mobile computing applications like commerce, healthcare, e-learning, etc. The use of mobile devices has resulted in an exponential rise in the amount of data generated and as a result the amount of energy consumed has increased. This is where cloud computing plays a major role. Cloud computing has transformed traditional mobile computing. The new mobile cloud not only provides on-demand services but also data storage and increased energy efficiency. Through mobile computing based on cloud computing, mobile device functions can be virtualized, reducing power consumption. In this paper, the authors survey application and potential of mobile cloud computing and present the energy-efficient ways. Also, the paper discusses development opportunities of mobile cloud computing. The research also mentions some of the major challenges in current mobile computing technology.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132936222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In today's world, it is appallingly hard to run a global business, spread over multiple continents without adopting cloud computing technology. Cloud computing makes it easy, saves bucks, reduces IT burden, and helps organisations to focus on customer requirements, market strategy, growth, revenue, and profit, etc. While the organisations are busy planning, selecting, migrating their core business data and applications to the cloud, at the same time it is pertinent to evaluate the service quality of cloud service providers. This will help organisations to adopt the right cloud service provider as per their business requirements. Eleven cloud service quality factors have been explored through an extensive review of the literature and then interpretive structural modelling (ISM) has been used to find out the driving and dependent factors of the cloud service quality and contextual relations among them. This study reveals six driving factors of the cloud service quality namely availability, reliability, scalability, security, service responsiveness, and usability.
{"title":"Modelling of the Cloud Service Quality Factors Using ISM","authors":"R. Agarwal, Sanjay Dhingra","doi":"10.4018/ijcac.295241","DOIUrl":"https://doi.org/10.4018/ijcac.295241","url":null,"abstract":"In today's world, it is appallingly hard to run a global business, spread over multiple continents without adopting cloud computing technology. Cloud computing makes it easy, saves bucks, reduces IT burden, and helps organisations to focus on customer requirements, market strategy, growth, revenue, and profit, etc. While the organisations are busy planning, selecting, migrating their core business data and applications to the cloud, at the same time it is pertinent to evaluate the service quality of cloud service providers. This will help organisations to adopt the right cloud service provider as per their business requirements. Eleven cloud service quality factors have been explored through an extensive review of the literature and then interpretive structural modelling (ISM) has been used to find out the driving and dependent factors of the cloud service quality and contextual relations among them. This study reveals six driving factors of the cloud service quality namely availability, reliability, scalability, security, service responsiveness, and usability.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128720875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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