Mobile Cloud Computing Model and Big Data Analysis for Healthcare Applications

Tawalbeh, Lo’ai; Mehmood, Rashid; Benkhlifa, Elhadj; Song, Houbing

doi:10.1109/access.2016.2613278

Cited by 231 publications

(87 citation statements)

References 45 publications

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“…Moreover, as background operation is possible, many mobile resources are likely to be utilized in accompanying smartphone applications [25,26]. Web Workers make JavaScript processing effective in terms of function, but the results of the test conducted in this research revealed that the browser on a desktop PC displays lower performance due to limitations in mobile resources [27]. A cloud framework is proposed to improve the functions of smart terminal application programs that demand complicated implementations in limited mobile environment.…”

Section: Javascript Multi-threadmentioning

confidence: 99%

Cloud Computing to Improve JavaScript Processing Efficiency of Mobile Applications

Kim¹

2017

J Inf Process Syst

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The burgeoning distribution of smartphone web applications based on various mobile environments is increasingly focusing on the performance of mobile applications implemented by JavaScript and HTML5 (Hyper Text Markup Language 5). If application software has a simple functional processing structure, then the problem is benign. However, browser loads are becoming more burdensome as the amount of JavaScript processing continues to increase. Processing time and capacity of the JavaScript in current mobile browsers are limited. As a solution, the Web Worker is designed to implement multi-threading. However, it cannot guarantee the computing ability as a native application on mobile devices, and is not sufficient to improve processing speed. The method proposed in this research overcomes the limitation of resources as a mobile client and guarantees performance by native application software by providing high computing service. It shifts the JavaScript process of a mobile device on to a cloud-based computer server. A performance evaluation experiment revealed the proposed algorithm to be up to 6 times faster in computing speed compared to the existing mobile browser's JavaScript process, and 3 to 6 times faster than Web Worker. In addition, memory usage was also less than the existing technology.

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Section: Javascript Multi-threadmentioning

confidence: 99%

Cloud Computing to Improve JavaScript Processing Efficiency of Mobile Applications

Kim¹

2017

J Inf Process Syst

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“…Loai A. et al [36] proposed the design of networked healthcare systems using big data and mobile cloud computing technologies. Wan et al [37] studied a cloud-enabled WBAN architecture and its applications in pervasive healthcare systems.…”

Section: Cloud Computingmentioning

confidence: 99%

Intelligent Healthcare Systems Assisted by Data Analytics and Mobile Computing

Wang

Zhou

et al. 2018

Wireless Communications and Mobile Computing

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It is entering an era of big data, which facilitated great improvement in various sectors. Particularly, assisted by wireless communications and mobile computing, mobile devices have emerged with a great potential to renovate the healthcare industry. Although the advanced techniques will make it possible to understand what is happening in our body more deeply, it is extremely difficult to handle and process the big health data anytime and anywhere. Therefore, data analytics and mobile computing are significant for the healthcare systems to meet many technical challenges and problems that need to be addressed to realize this potential. Furthermore, the advanced healthcare systems have to be upgraded with new capabilities such as machine learning, data analytics, and cognitive power for providing human with more intelligent and professional healthcare services. To explore recent advances and disseminate state-of-the-art techniques related to data analytics and mobile computing on designing, building, and deploying novel technologies, to enable intelligent healthcare services and applications, this paper presents the detailed design for developing intelligent healthcare systems assisted by data analytics and mobile computing. Moreover, some representative intelligent healthcare applications are discussed to show that data analytics and mobile computing are available to enhance the performance of the healthcare services.

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“…Thus, a destination will receive incorrect data and treat it as correct. In CPS, Integrity is ensured by catching all possible attacks that seek to ruin the CPS's physical goals and change data that are collected and sent by sensors [17].…”

Section: Safety and Security Objectives In Cpsmentioning

confidence: 99%

Security and Privacy Challenges in Cyber-Physical Systems

Aldosari¹

2017

JIS

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Cyber-Physical Systems, or Smart-Embedded Systems, are co-engineered for the integration of physical, computational and networking resources. These resources are used to develop an efficient base for enhancing the quality of services in all areas of life and achieving a classier lifestyle in terms of a required service's functionality and timing. Cyber-Physical Systems (CPSs) complement the need to have smart products (e.g., homes, hospitals, airports, cities). In other words, regulate the three kinds of resources available: physical, computational, and networking. This regulation supports communication and interaction between the human word and digital word to find the required intelligence in all scopes of life, including Telecommunication, Power Generation and Distribution, and Manufacturing. Data Security is among the most important issues to be considered in recent technologies. Because Cyber-Physical Systems consist of interacting complex components and middle-ware, they face real challenges in being secure against cyber-attacks while functioning efficiently and without affecting or degrading their performance. This study gives a detailed description of CPSs, their challenges (including cyber-security attacks), characteristics, and related technologies. We also focus on the tradeoff between security and performance in CPS, and we present the most common Side Channel Attacks on the implementations of cryptographic algorithms (symmetric: AES and asymmetric: RSA) with the countermeasures against these attacks.

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Mobile Cloud Computing Model and Big Data Analysis for Healthcare Applications

Cited by 231 publications

References 45 publications

Cloud Computing to Improve JavaScript Processing Efficiency of Mobile Applications

Cloud Computing to Improve JavaScript Processing Efficiency of Mobile Applications

Intelligent Healthcare Systems Assisted by Data Analytics and Mobile Computing

Security and Privacy Challenges in Cyber-Physical Systems

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