Fruit Fly Optimization Algorithm for Network-Aware Web Service Composition in the Cloud

Shehu, Umar Galadima; Safdar, Ghazanfar Ali; Epiphaniou, Gregory

doi:10.14569/ijacsa.2016.070201

Cited by 6 publications

(2 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to the SW-GRNN forecasting result, the smell concentration Smelli can be calculated and be employed by root mean square error (RMSE), which is shown in equation (8). FOA was performed by Matlab R2010b (MathWorks, Natick, USA) and the detailed steps 35 are as follows:…”

Section: Methodsmentioning

confidence: 99%

Prediction of microfibril angle in Dahurian larch wood using visible–near infrared spectroscopy and chemometric techniques

Via

Cheng

et al. 2019

Journal of Near Infrared Spectroscopy

View full text Add to dashboard Cite

The microfibril angle of the S2 layer in the secondary cell wall of the tracheid is important for molecular and microscopic properties that influence collapse resistance, longitudinal modulus of elasticity and other lateral properties of conifers at the macroscopic level. This research aimed to investigate the feasibility of using a fruit fly optimization algorithm for visible and near infrared modeling optimization of Dahurian larch wood microfibril angle prediction. Originally, the linear relationship between microfibril angle and their raw spectra and visible and near infrared spectra pretreated by wavelet transform was established. Then, a nonlinear coupled model was built by combining the stepwise regression analysis and generalized regression neural network methods. As a final point, fruit fly optimization algorithm was used for optimizing stepwise regression analysis–generalized regression neural network coupled model. It was found that stepwise regression analysis–generalized regression neural network coupled model coupled model based on the optimization of fruit fly optimization algorithm simplify visible and near infrared spectral data and its prediction results ([Formula: see text] = 0.90, RMSEP = 0.75, mean average percentage error ([Formula: see text]) = 0.05) outperforms original partial least squares model ([Formula: see text] = 0.86, RMSEP = 0.88, [Formula: see text] = 0.06). This work demonstrated the feasibility of using improved chemometric techniques for improving the precision of visible and near infrared spectra in the prediction of microfibril angle.

show abstract

Section: Methodsmentioning

confidence: 99%

Prediction of microfibril angle in Dahurian larch wood using visible–near infrared spectroscopy and chemometric techniques

Via

Cheng

et al. 2019

Journal of Near Infrared Spectroscopy

View full text Add to dashboard Cite

show abstract

“…First, newly updated velocity calculation formulas are used [33]. Second, the distance and smell operator from the FOA optimization algorithm is used to enhance the position of the particle to avoid the local optimum [34]. For the first step of newly updated formulas, it is based mainly on two cases.…”

Section: Map( ) Functionmentioning

confidence: 99%

Towards Service Composition based on Hybrid Bio-Inspired Cloud-based QoS Provisioning Approach.

Bahgat¹,

Salam²,

Atwan³

et al. 2020

Preprint

View full text Add to dashboard Cite

It has recently become a critical issue to provide software development in a service-based conceptual style for business companies . As a powerful technology for service-oriented computing, the composition of web services is investigated. This offered great opportunities to improve IT industries and business processes by forming new value-added services that satisfy the user’s complex requirements. Unfortunately, many challenges are facing the service composition process. These include the difficulties to satisfy the user’s complex demands, maintaining the performance to be matched with the quality of service (QoS) requirements, and search space reduction for QoS missing or changeable values. Accordingly, this paper proposes a cloud-based QoS provisioning service composition (CQPC) framework to address these challenges. To prove the concept and the applicability of the CQPC framework, a Hybrid Bio-Inspired QoS provisioning (HBIQP) technique is presented for the operation of the CQPC framework modules. The solution space is reduced via utilizing skyline concepts to have faster execution time and keep only reliable and most interesting services. The CQPC framework is equipped with two proposed algorithms: (i) the modified highly accurate prediction (MHAP) algorithm to enhance the prediction of QoS values of the services participating in the composition process, (ii) the MapReduce fruit fly Particle swarm Optimization (MR-FPSO) algorithm to handle composing web services for large scale of data in the cloud environment. The experimental results demonstrate the worthiness of the HBIQP technique to meet the performance metrics more than other state-of-the-art techniques in terms of average fitness value, accuracy, and execution time.

show abstract

Applying Zero Trust Security Principles to Defence Mechanisms Against Data Exfiltration Attacks

Egerton

Hammoudeh

Ünal

et al. 2021

Security and Privacy in the Internet of Things

View full text Add to dashboard Cite

Fruit Fly Optimization Algorithm for Network-Aware Web Service Composition in the Cloud

Cited by 6 publications

References 35 publications

Prediction of microfibril angle in Dahurian larch wood using visible–near infrared spectroscopy and chemometric techniques

Prediction of microfibril angle in Dahurian larch wood using visible–near infrared spectroscopy and chemometric techniques

Towards Service Composition based on Hybrid Bio-Inspired Cloud-based QoS Provisioning Approach.

Applying Zero Trust Security Principles to Defence Mechanisms Against Data Exfiltration Attacks

Contact Info

Product

Resources

About