A foggy research future: Advances and future opportunities in fog computing research

Choo, Kim‐Kwang Raymond; Lu, Rongxing; Chen, Liqun; Xun, Yi

doi:10.1016/j.future.2017.09.014

Cited by 39 publications

(10 citation statements)

References 32 publications

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“…As the data increases day-by-day, the vast amount of data have to be collected, analyzed, managed, and stored, in the cloud which increases the complexity of cloud-based services. To address this issue, we introduce fog computing [25][26][27][28] at the edge of the cloud for pre-processing of generated data. Fog improve the efficiency by reducing the data transfer to the cloud transform from physical devices.…”

Section: Health Information Science and Systemsmentioning

confidence: 99%

A study on medical Internet of Things and Big Data in personalized healthcare system

Jagadeeswari

Subramaniyaswamy

Ravi

et al. 2018

Health Inf Sci Syst

265

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Personalized healthcare systems deliver e-health services to fulfill the medical and assistive needs of the aging population. Internet of Things (IoT) is a significant advancement in the Big Data era, which supports many real-time engineering applications through enhanced services. Analytics over data streams from IoT has become a source of user data for the healthcare systems to discover new information, predict early detection, and makes decision over the critical situation for the improvement of the quality of life. In this paper, we have made a detailed study on the recent emerging technologies in the personalized healthcare systems with the focus towards cloud computing, fog computing, Big Data analytics, IoT and mobile based applications. We have analyzed the challenges in designing a better healthcare system to make early detection and diagnosis of diseases and discussed the possible solutions while providing e-health services in secure manner. This paper poses a light on the rapidly growing needs of the better healthcare systems in real-time and provides possible future work guidelines.

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Section: Health Information Science and Systemsmentioning

confidence: 99%

A study on medical Internet of Things and Big Data in personalized healthcare system

Jagadeeswari

Subramaniyaswamy

Ravi

et al. 2018

Health Inf Sci Syst

265

View full text Add to dashboard Cite

show abstract

“…Hence, the load states of EDCs in various locations differ greatly. Furthermore, unbalanced problem emerges, as some EDCs in the region could be overloaded while some other EDCs are in idle state [4]. There exist several previous works that proposed different methods to address load balancing issues.…”

Section: Related Workmentioning

confidence: 99%

Secure and Sustainable Load Balancing of Edge Data Centers in Fog Computing

et al. 2018

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Fog computing is a recent research trend to bring cloud computing services to network edges. Edge datacenters (EDCs) are deployed to decrease the latency and networks congestion by processing data streams and user requests in near real-time. The EDCs deployment is distributed in nature and positioned between cloud datacenter and data sources. Load balancing is the process of redistributing the work load among EDCs to improve both resource utilization and job response time. Load balancing also avoids a situation where some EDCs are heavily loaded while others in idle state or doing small data processing. In such scenarios, load balancing between the EDCs plays a vital role for user response and real-time event detection. As the EDCs are deployed in the unattended environment, secure authentication of EDCs is an important issue to address before performing load balancing. This paper proposes a novel load balancing technique to authenticate the EDCs and find out less loaded EDC for task allocation. The proposed load balancing technique is more efficient than other existing approaches in finding less loaded EDC for task allocation. The proposed approach not only improves efficiency of load balancing, it also strengthens the security by authenticating the destination EDCs.

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“…To deal with limitations inherent in a cloud computing environment (e.g. privacy of users sourcing the data to the cloud, particularly hosted in an overseas jurisdiction, and performance issues such as latency), there has been attempts to 'push' the computing to the edge of the network via fog nodes (Choo et al, 2018;Osanaiye et al, 2017). Hence, the fog computing paradigm has been emerged to handle time/delay-sensitive IoE increase in the number of IoT devices while achieving a satisfactory QoE.…”

Section: Introductionmentioning

confidence: 99%

QoS-aware service provisioning in fog computing

Murtaza

Akhunzada

Islam

et al. 2020

Journal of Network and Computer Applications

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Fog computing has emerged as a complementary solution to address the issues faced in cloud computing. While fog computing allows us to better handle time/delay-sensitive Internet of Everything (IoE) applications (e.g. smart grids and adversarial environment), there are a number of operational challenges. For example, the resource-constrained nature of fog-nodes and heterogeneity of IoE jobs complicate efforts to schedule tasks efficiently. Thus, to better streamline time/delay-sensitive varied IoE requests, the authors contributes by introducing a smart layer between IoE devices and fog nodes to incorporate an intelligent and adaptive learning based task scheduling technique. Specifically, our approach analyzes the various service type of IoE requests and presents an optimal strategy to allocate the most suitable available fog resource accordingly. We rigorously evaluate the performance of the proposed approach using simulation, as well as its correctness using formal verification. The evaluation findings are promising, both in terms of energy consumption and Quality of Service (QoS).

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A foggy research future: Advances and future opportunities in fog computing research

Cited by 39 publications

References 32 publications

A study on medical Internet of Things and Big Data in personalized healthcare system

A study on medical Internet of Things and Big Data in personalized healthcare system

Secure and Sustainable Load Balancing of Edge Data Centers in Fog Computing

QoS-aware service provisioning in fog computing

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