Fog-Based Healthcare Architecture for Wearable Body Area Network

Tahir, Sabeen; Bakhsh, Sheikh Tahir; AlGhamdi, Rayed; Abulkhair, Maysoon F.

doi:10.1166/jmihi.2017.2152

Cited by 7 publications

(12 citation statements)

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“…Besides, the spiral movement of the moths around the flames in the solution space is modeled mathematically by a logarithmic spiral function and is expressed by Equation

(() M_{k}, F_{l}) = D_{k} . e^{bt} . \cos ((), 2 π t) + F_{l},

…”

Section: The Proposed Task Scheduling Approachmentioning

confidence: 99%

“…Cyber-physical system is a combination of sensing, communications, computation, and cyber-physical processes, which can prepare real-time services. 18 As a growing cyberspace trend, CPS provides intelligent interplay between the industrial equipment computational elements and networked systems of cyber-physical devices that are collectively involved in treating a critical manner. 4,19 It moves the computation and monitoring from a standalone system to a remotely located monitoring center.…”

Section: Figurementioning

confidence: 99%

“…where M k represents the kth moth, F l represents the lth flame, and S is the spiral function. Besides, the spiral movement of the moths around the flames in the solution space is modeled mathematically by a logarithmic spiral function 18 and is expressed by Equation 21…”

Section: Proposed Algorithmmentioning

confidence: 99%

“…To arrive at this, the appearing CPS has awakened important concern from academia. Cyber‐physical system is a combination of sensing, communications, computation, and cyber‐physical processes, which can prepare real‐time services . As a growing cyberspace trend, CPS provides intelligent interplay between the industrial equipment computational elements and networked systems of cyber‐physical devices that are collectively involved in treating a critical manner .…”

Section: Preliminary Conceptsmentioning

confidence: 99%

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An efficient task scheduling approach using moth‐flame optimization algorithm for cyber‐physical system applications in fog computing

Ghobaei‐Arani

Souri

Safara

et al. 2019

Trans Emerging Tel Tech

126

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With the rapid development of in modern technologies has led to a novel generation of cyberspace equipment and secure analysis methods such as cyber‐physical system (CPS). The CPS system refers to an intelligent dependable system of embedded smart devices used to monitor and control the cyberspace conditions in a fog computing environment. The fog computing environment connects resources even human beings together to enhance the quality of life through performing of CPS applications using computation resources at the network edge. The optimization of task scheduling for the CSP applications as a challenging issue has been considered as the NP‐hard problem in fog computing environment which is not trivial. On the one hand, reasonable tasks scheduling can increase resource utilization, which can avoid less idle resource. This paper presents a task scheduling algorithm based on moth‐flame optimization algorithm to assign an optimal set of tasks to fog nodes to meet the satisfaction of quality of service requirements of CPS applications in such a way that the total execution time of tasks is minimized. The minimization of task execution and transfer time in the proposed algorithm are considered as objective functions. The experimental testing of the proposed solution is carried out in iFogSim toolkit. As a result of the simulation based on proposed algorithm found, the optimal solution for the scheduling of tasks and equal distribution of tasks to fog nodes has been provided, and less total execution time consumption has been achieved compared with other algorithms.

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“…Besides, the spiral movement of the moths around the flames in the solution space is modeled mathematically by a logarithmic spiral function and is expressed by Equation

(() M_{k}, F_{l}) = D_{k} . e^{bt} . \cos ((), 2 π t) + F_{l},

…”

Section: The Proposed Task Scheduling Approachmentioning

confidence: 99%

Section: Figurementioning

confidence: 99%

Section: Proposed Algorithmmentioning

confidence: 99%

Section: Preliminary Conceptsmentioning

confidence: 99%

See 2 more Smart Citations

An efficient task scheduling approach using moth‐flame optimization algorithm for cyber‐physical system applications in fog computing

Ghobaei‐Arani

Souri

Safara

et al. 2019

Trans Emerging Tel Tech

126

View full text Add to dashboard Cite

show abstract

“…The authors [28,30] had proposed the mathematical model for flood forecasting in case of disaster circumstance. GIS-based flood forecasting Model is designed to calculate the flood series frequency [31][32][33][34][35][36][37][38][39][40][41][42]. The authors [10,35] had focused their research on designing the conceptual model for flood forecasting.…”

Section: The Critical Evaluation Of the Research Study In Tablementioning

confidence: 99%

A Flood Forecasting Model based on Wireless Sensor and Actor Networks

Bakhsh¹,

Ahmed²,

Shahzad³

et al. 2020

IJACSA

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Flood forecasting is a challenging area of research that can help to save precious lives by timely intimating about the flood possibilities. The role of advancements in computing and allied technologies has moved the research towards a new horizon. Researchers from all over the world are using Artificial Neural Networks (ANN), Global Information Systems (GIS), and Wireless Sensor Networks (WSN) based schemes for flash flood forecasting and hydrological risk analysis. ANN and GIS-based solutions are much costly whereas the analysis and prediction using WSN require much less cost for infrastructure deployment. It will enable the use of flood prediction mechanisms in the third world and poor countries. New variation in storage capacity can be a vital source to eliminate or reduce the chance of flood. By considering this observation, it is proposed to develop a generic flood prediction scheme that can manage the system as per resources and environmental conditions. A heterogeneous WSN has considered where powerful Collector Nodes (CN) continuously takes values from member sensor nodes in the region. CN transmits the alerts to Administration Unit (AU) when threshold values are crossed. It is proposed to save the threshold values from all water sources like storage capacity, water inflow, and outflow in the repository for decision making. Moreover, environmental parameters including water level, humidity, temperature, air pressure, rainfall, soil moisture, etc. are considered for the analysis of flood prediction. We have also considered the evaluation of these parameters in specified boundary values that were not considered in existing schemes. In this research study, we have used Arc GIS and NS2 simulation tools to analyze the parameters and predict the probability of the occurrence of a flood.

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