scholarly journals Mobile cloud computing in smart healthcare Applications

2021 ◽  
Vol I (I) ◽  
Author(s):  
Kavitha N
Keyword(s):  
Cloud Computing ◽  
Mobile Cloud Computing ◽  
Critical Role ◽  
Cost Effective ◽  
Mobile Cloud ◽  
Healthcare Applications ◽  
Related Data ◽  
Healthcare Data ◽  
Smart Healthcare ◽  
Effective Manner

For urban residents, the Smart Healthcare idea is increasingly prevalent. This service's primary purpose is to provide patients with healthcare data. Using mobile communication and sharing in real time is necessary. Data processing and analysis are all part of this. As a result, cloud computing allows individuals to connect and access healthcare-related data. Data-related tasks like as sharing, processing, and analysis may be offloaded to mobile users for patients via mobile cloud devices, which can play a critical role in mobile cloud computing. Using this service, hospitals and clinics will be able to provide smart healthcare to their patients in a cost-effective manner. The usage of cloud computing will guarantee that patients get high-quality service.

Bring Out Your Data

2012 ◽  
pp. 126-145
Author(s):  
Thomas E. Grissom ◽  
Andrew DuKatz ◽  
Hubert A. Kordylewski ◽  
Richard P. Dutton
Keyword(s):  
Cost Effective ◽  
Regulatory Oversight ◽  
Measurement Quality ◽  
Related Data ◽  
Healthcare Data ◽  
Effective Manner ◽  
Wide Range ◽  
Automated Process ◽  
User Friendly ◽  
Quality Institute

Recent healthcare legislation, financial pressures, and regulatory oversight have increased the need to create improved mechanisms for performance measurement, quality management tracking, and outcomes-based research. The Anesthesia Quality Institute (AQI) has established the National Anesthesia Clinical Outcomes Registry (NACOR) to support these requirements for a wide-range of customers including individual anesthesiologists, anesthesia practices, hospitals, and credentialing agencies. Concurrently, the availability of increased digital sources of healthcare data make it possible to capture massive quantities of data in a more efficient and cost-effective manner than ever before. With NACOR, AQI has established a user-friendly, automated process to effectively and efficiently collect a wide-range of anesthesia-related data directly from anesthesia practices. This review will examine the issues guiding the evolution of NACOR as well as some potential pitfalls in its growth and usage.

scholarly journals A Comprehensive Review on Adaptability of Network Forensics Frameworks for Mobile Cloud Computing

2014 ◽  
Vol 2014 ◽  
pp. 1-27 ◽  
Author(s):  
Suleman Khan ◽  
Muhammad Shiraz ◽  
Ainuddin Wahid Abdul Wahab ◽  
Abdullah Gani ◽  
Qi Han ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Mobile Cloud Computing ◽  
Cost Effective ◽  
Data Access ◽  
Digital Content ◽  
Mobile Cloud ◽  
Network Attacks ◽  
Network Forensics ◽  
Network Forensic ◽  
The Cost

Network forensics enables investigation and identification of network attacks through the retrieved digital content. The proliferation of smartphones and the cost-effective universal data access through cloud has made Mobile Cloud Computing (MCC) a congenital target for network attacks. However, confines in carrying out forensics in MCC is interrelated with the autonomous cloud hosting companies and their policies for restricted access to the digital content in the back-end cloud platforms. It implies that existing Network Forensic Frameworks (NFFs) have limited impact in the MCC paradigm. To this end, we qualitatively analyze the adaptability of existing NFFs when applied to the MCC. Explicitly, the fundamental mechanisms of NFFs are highlighted and then analyzed using the most relevant parameters. A classification is proposed to help understand the anatomy of existing NFFs. Subsequently, a comparison is given that explores the functional similarities and deviations among NFFs. The paper concludes by discussing research challenges for progressive network forensics in MCC.

scholarly journals Mobile Cloud Computing Model and Big Data Analysis for Healthcare Applications

IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 6171-6180 ◽  
Author(s):  
Lo'ai A. Tawalbeh ◽  
Rashid Mehmood ◽  
Elhadj Benkhlifa ◽  
Houbing Song
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Analysis ◽  
Mobile Cloud Computing ◽  
Big Data Analysis ◽  
Mobile Cloud ◽  
Healthcare Applications ◽  
Computing Model

scholarly journals Mobile Cloud Computing: Taxonomy and Challenges

2020 ◽  
Vol 2020 ◽  
pp. 1-23
Author(s):  
Ahmed Aliyu ◽  
Abdul Hanan Abdullah ◽  
Omprakash Kaiwartya ◽  
Syed Hamid Hussain Madni ◽  
Usman Mohammed Joda ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Mobile Cloud Computing ◽  
Cost Effective ◽  
Qualitative Assessment ◽  
The Internet ◽  
Mobile Cloud ◽  
Energy Aware ◽  
Research Issues ◽  
Delivery Platform ◽  
Cloud Users

Mobile cloud computing (MCC) holds a new dawn of computing, where the cloud users are attracted to multiple services through the Internet. MCC has a qualitative, flexible, and cost-effective delivery platform for providing services to mobile cloud users with the aid of the Internet. Due to the advantage of the delivery platform, several studies have been conducted on how to address different issues in MCC. The issues include energy efficiency in MCC, secured MCC, user-satisfied applications and Quality of Service-aware MCC (QoS). In this context, this paper qualitatively reviews different proposed MCC solutions. Therefore, taxonomy for MCC is presented considering major themes of research including energy-aware, security, applications, and QoS-aware developments. Each of these themes is critically investigated with comparative assessments considering recent advancements. Analysis of metrics and implementation environments used for evaluating the performance of existing techniques are presented. Finally, some open research issues and future challenges are identified based on the critical and qualitative assessment of literature for researchers in this field.

Opportunistic Edge Computing Architecture for Smart Healthcare Systems

2021 ◽  
pp. 289-306
Author(s):  
Nivethitha V. ◽  
Aghila G.
Keyword(s):  
Cloud Computing ◽  
Healthcare Systems ◽  
Edge Computing ◽  
Healthcare Applications ◽  
Sensitive Data ◽  
Network Resource ◽  
Computing Architecture ◽  
Healthcare Data ◽  
Smart Healthcare ◽  
Network Response Time

Some of the largest global industries that is driving smart city environments are anywhere and anytime health monitoring applications. Smart healthcare systems need to be more preventive and responsive as they deal with sensitive data. Even though cloud computing provides solutions to the smart healthcare applications, the major challenge imposed on cloud computing is how could the centralized traditional cloud computing handle voluminous data. The existing models may encounter problems related to network resource utilization, overheads in network response time, and communication latency. As a solution to these problems, edge-oriented computing has emerged as a new computing paradigm through localized computing. Edge computing expands the compute, storage, and networking capabilities to the edge of the network which will respond to the above-mentioned issues. Based on cloud computing and edge computing, in this chapter an opportunistic edge computing architecture is introduced for smart provisioning of healthcare data.

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