A new approach for task managing in the fog-based medical cyber-physical systems using a hybrid algorithm

Circuit World ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jiuhong Yu ◽  
Mengfei Wang ◽  
Yu J.H. ◽  
Seyedeh Maryam Arefzadeh
Keyword(s):  
Local Search ◽  
High Efficiency ◽  
Fog Computing ◽  
Hybrid Genetic Algorithm ◽  
Task Mapping ◽  
Main Approach ◽  
Content Type ◽  
Cloud Data ◽  
Reliable Mechanism ◽  
Time Systems

Purpose This paper aims to offer a hybrid genetic algorithm and the ant colony optimization (GA-ACO) algorithm for task mapping and resource management. The paper aims to reduce the makespan and total response time in fog computing- medical cyber-physical system (FC-MCPS). Design/methodology/approach Swift progress in today’s medical technologies has resulted in a new kind of health-care tool and therapy techniques like the MCPS. The MCPS is a smart and reliable mechanism of entrenched clinical equipment applied to check and manage the patients’ physiological condition. However, the extensive-delay connections among cloud data centers and medical devices are so problematic. FC has been introduced to handle these problems. It includes a group of near-user edge tools named fog points that are collaborating until executing the processing tasks, such as running applications, reducing the utilization of a momentous bulk of data and distributing the messages. Task mapping is a challenging problem for managing fog-based MCPS. As mapping is an non-deterministic pol ynomial-time-hard optimization issue, this paper has proposed a procedure depending on the hybrid GA-ACO to solve this problem in FC-MCPS. ACO and GA, that is applied in their standard formulation and combined as hybrid meta-heuristics to solve the problem. As such ACO-GA is a hybrid meta-heuristic using ACO as the main approach and GA as the local search. GA-ACO is a memetic algorithm using GA as the main approach and ACO as local search. Findings MATLAB is used to simulate the proposed method and compare it to the ACO and MACO algorithms. The experimental results have validated the improvement in makespan, which makes the method a suitable one for use in medical and real-time systems. Research limitations/implications The proposed method can achieve task mapping in FC-MCPS by attaining high efficiency, which is very significant in practice. Practical implications The proposed approach can achieve the goal of task scheduling in FC-MCPS by attaining the highest total computational efficiency, which is very significant in practice. Originality/value This research proposes a GA-ACO algorithm to solve the task mapping in FC-MCPS. It is the most significant originality of the paper.

Hybrid metaheuristic to solve the “one-to-many-to-one” problem

2017 ◽  
Vol 55 (1) ◽  
pp. 136-155 ◽  
Author(s):  
Jalel Euchi ◽  
Sana Frifita
Keyword(s):  
Local Search ◽  
Optimization Problems ◽  
Soft Drink ◽  
Hybrid Genetic Algorithm ◽  
Real Case ◽  
Solution Quality ◽  
Routing Problem ◽  
Content Type ◽  
Delivery Problem ◽  
Combinatorial Optimization Problems

Purpose The purpose of this paper is to present a specific variant of vehicle routing problem with simultaneous full pickup and delivery problem (VRPSFPD) known as one-to-many-to-one (1-M-1) problem with several vehicles, where every customer can receive and send goods simultaneously, which has added the notion of the totality for the pickup goods. Currently, hybrid metaheuristics have become more popular because they offer the best solutions to several combinatorial optimization problems. Therefore, due to the complexity of 1-M-1 a hybrid genetic algorithm with variable neighborhood descent (HGAVND) local search is proposed. To improve the solution provided by the HGAVND the authors suggest applying a structure OR-Opt. To test the performance of the algorithm the authors have used a set of benchmarks from the literature and apply the HGAVND algorithm to solve the real case of distribution of soft drink in Tunisia. The experimental results indicate that the algorithm can outperform all other algorithms proposed in literature with regard to solution quality and processing time. Moreover, the authors improve the best known solution of the majority of benchmark instances taken from the literature. Design/methodology/approach Due to the complexity of 1-M-1 a HGAVND local search is proposed. Originality/value First, in the presence of full pickup constraints, the problem becomes more complex, this implies that the choice of a good metaheuristic can provide good results. Second, the best contribution consists in a specific variant of VRPSFPD problem as 1-M-1 which the paper present the first application of metaheuristics to solve the specific 1-M-1 and to apply it in real case of distribution of soft drink.

An energy-efficient VM placement method for cloud data centers using a hybrid genetic algorithm

2018 ◽  
Vol 20 (4) ◽  
pp. 430-445 ◽  
Author(s):  
Mohamed Amine Kaaouache ◽  
Sadok Bouamama
Keyword(s):  
Genetic Algorithm ◽  
Communication Network ◽  
Energy Consumption ◽  
Data Centers ◽  
Hybrid Genetic Algorithm ◽  
Vm Placement ◽  
Content Type ◽  
Cloud Data ◽  
Placement Method ◽  
Cloud Data Centers

Purpose This purpose of this paper is to propose a novel hybrid genetic algorithm based on a virtual machine (VM) placement method to improve energy efficiency in cloud data centers. How to place VMs on physical machines (PMs) to improve resource utilization and reduce energy consumption is one of the major concerns for cloud providers. Over the past few years, many approaches for VM placement (VMP) have been proposed; however, existing VM placement approaches only consider energy consumption by PMs, and do not consider the energy consumption of the communication network of a data center. Design/methodology/approach This paper attempts to solve the energy consumption problem using a VM placement method in cloud data centers. Our approach uses a repairing procedure based on a best-fit decreasing heuristic to resolve violations caused by infeasible solutions that exceed the capacity of the resources during the evolution process. Findings In addition, by reducing the energy consumption time with the proposed technique, the number of VM migrations was reduced compared with existing techniques. Moreover, the communication network caused less service level agreement violations (SLAV). Originality/value The proposed algorithm aims to minimize energy consumption in both PMs and communication networks of data centers. Our hybrid genetic algorithm is scalable because the computation time increases nearly linearly when the number of VMs increases.

A secure anonymous tracing fog-assisted method for the Internet of Robotic Things

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abdulrahman Alamer
Keyword(s):  
Elliptic Curve ◽  
Elliptic Curve Cryptography ◽  
High Efficiency ◽  
Fog Computing ◽  
Bloom Filter ◽  
The Internet ◽  
Network System ◽  
Content Type ◽  
Robotic Devices ◽  
Tracing Attacks

PurposeEmploying a fog computing (FC) network system in the robotic network system is an effective solution to support robotic application issues. The interconnection between robotic devices through an FC network can be referred as the Internet of Robotic Things (IoRT). Although the FC network system can provide number of services closer to IoRT devices, it still faces significant challenges including real-time tracing services and a secure tracing services. Therefore, this paper aims to provide a tracking mobile robot devices in a secure and private manner, with high efficiency performance, is considered essential to ensuring the success of IoRT network applications.Design/methodology/approachThis paper proposes a secure anonymous tracing (SAT) method to support the tracing of IoRT devices through a FC network system based on the Counting Bloom filter (CBF) and elliptic curve cryptography techniques. With the proposed SAT mechanism, a fog node can trace a particular robot device in a secure manner, which means that the fog node can provide a service to a particular robot device without revealing any private data such as the device's identity or location.FindingsAnalysis shows that the SAT mechanism is both efficient and resilient against tracing attacks. Simulation results are provided to show that the proposed mechanism is beneficial to support IoRT applications over an FC network system.Originality/valueThis paper represents a SAT method based on CBF and elliptic curve cryptography techniques as an efficient mechanism that is resilient against tracing attacks.

A hybrid genetic algorithm with local search

2001 ◽  
Vol 59 (1-2) ◽  
pp. 107-120 ◽  
Author(s):  
G Vivó-Truyols ◽  
J.R Torres-Lapasió ◽  
A Garrido-Frenich ◽  
M.C Garcı́a-Alvarez-Coque
Keyword(s):  
Genetic Algorithm ◽  
Local Search ◽  
Hybrid Genetic Algorithm

A systematic identification approach for biaxial piezoelectric stage with coupled Duhem-type hysteresis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Qun Chen ◽  
Zong-Xiao Yang ◽  
Zhumu Fu
Keyword(s):  
Parameter Identification ◽  
High Efficiency ◽  
Full Range ◽  
Unknown Parameters ◽  
Content Type ◽  
De Algorithm ◽  
Complicated Model ◽  
Identification Approach ◽  
Cross Axis ◽  
Systematic Identification

Purpose The problem of parameter identification for biaxial piezoelectric stages is still a challenging task because of the existing hysteresis, dynamics and cross-axis coupling. This study aims to find an accurate and systematic approach to tackle this problem. Design/methodology/approach First, a dual-input and dual-output (DIDO) model with Duhem-type hysteresis is proposed to depict the dynamic behavior of the biaxial piezoelectric stage. Then, a systematic identification approach based on a modified differential evolution (DE) algorithm is proposed to identify the unknown parameters of the Duhem-type DIDO model for a biaxial piezostage. The randomness and parallelism of the modified DE algorithm guarantee its high efficiency. Findings The experimental results show that the characteristics of the biaxial piezoelectric stage can be identified with adequate accuracy based on the input–output data, and the peak-valley errors account for 2.8% of the full range in the X direction and 1.5% in the Y direction. The attained results validated the correctness and effectiveness of the presented identification method. Originality/value The classical DE algorithm has many adjustment parameters, which increases the inconvenience and difficulty of using in practice. The parameter identification of Duhem-type DIDO piezoelectric model is rarely studied in detail and its successful application based on DE algorithm on a biaxial piezostage is hitherto unexplored. To close this gap, this work proposed a modified DE-based systematic identification approach. It not only can identify this complicated model with more parameters, but also has little tuning parameters and thus is easy to use.

A framework for near real-time ROM stockpile modelling to improve blending efficiency

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shi Zhao ◽  
Tien-Fu Lu ◽  
Larissa Statsenko ◽  
Benjamin Koch ◽  
Chris Garcia
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Laser Scanning ◽  
High Efficiency ◽  
Reference Model ◽  
Geometric Model ◽  
Mining Industry ◽  
Management Systems ◽  
Content Type ◽  
Ore Grade

Purpose In the mining industry, a run-of-mine (ROM) stockpile is a temporary storage unit, but it is also widely accepted as an effective method to reduce the short-term variations of ore grade. However, tracing ore grade at ROM stockpiles accurately using most current fleet management systems is challenging, due to insufficient information available in real time. This study aims to build a three-dimensional (3D) model for ROM stockpiles continuously based on fine-grained grade information through integrating data from a number of ore grade tracking sources. Design/methodology/approach Following a literature review, a framework for a new stockpile management system is proposed. In this system, near real-time high-resolution 3D ROM stockpile models are created based on dump/load locations measured from global positioning system sensors. Each stockpile model contains a group of layers which are separated by different qualities. Findings Acquiring the geometric shapes of all the layers in a stockpile and cuts made by front wheel loaders provides a better understanding about the quality and quality distribution within a stockpile when it is stacked/reclaimed. Such a ROM stockpile model can provide information on predicating ore blend quality with high accuracy and high efficiency. Furthermore, a 3D stockyard model created based on such ROM stockpile models can help organisations optimise material flow and reduce the cost. Research limitations/implications The modelling algorithm is evaluated using a laboratory scaled stockpile at this stage. The authors expect to scan a real stockpile and create a reference model from it. Meanwhile, the geometric model cannot represent slump or collapse during reclaiming faithfully. Therefore, the model is expected to be reconcile monthly using laser scanning data. Practical implications The proposed model is currently translated to the operations at OZ Minerals. The use of such model will reduce the handling costs and improve the efficiency of existing grade management systems in the mining industry. Originality/value This study provides a solution to build a near real-time high-resolution multi-layered 3D stockpile model through using currently available information and resources. Such novel and low-cost stockpile model will improve the production rates with good output product quality control.

Differential quadrature method for nonlinear fractional partial differential equations

2018 ◽  
Vol 35 (6) ◽  
pp. 2349-2366 ◽  
Author(s):  
Umer Saeed ◽  
Mujeeb ur Rehman ◽  
Qamar Din
Keyword(s):  
Partial Differential Equations ◽  
Differential Equations ◽  
High Efficiency ◽  
Differential Quadrature Method ◽  
Differential Quadrature ◽  
Operational Matrices ◽  
Fractional Partial Differential Equations ◽  
Infinite Domain ◽  
Partial Differential ◽  
Content Type

Purpose The purpose of this paper is to propose a method for solving nonlinear fractional partial differential equations on the semi-infinite domain and to get better and more accurate results. Design/methodology/approach The authors proposed a method by using the Chebyshev wavelets in conjunction with differential quadrature technique. The operational matrices for the method are derived, constructed and used for the solution of nonlinear fractional partial differential equations. Findings The operational matrices contain many zero entries, which lead to the high efficiency of the method and reasonable accuracy is achieved even with less number of grid points. The results are in good agreement with exact solutions and more accurate as compared to Haar wavelet method. Originality/value Many engineers can use the presented method for solving their nonlinear fractional models.

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