Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Computer Engineering (22)
- Computer Sciences (20)
- Physical Sciences and Mathematics (20)
- Operations Research, Systems Engineering and Industrial Engineering (11)
- Electrical and Computer Engineering (10)
-
- Artificial Intelligence and Robotics (9)
- Numerical Analysis and Scientific Computing (9)
- Systems Science (9)
- Social and Behavioral Sciences (3)
- Computer Law (2)
- Digital Communications and Networking (2)
- Forensic Science and Technology (2)
- Information Security (2)
- Law (2)
- Legal Studies (2)
- Operational Research (2)
- Business (1)
- Business Intelligence (1)
- Communication (1)
- Communication Technology and New Media (1)
- Computer and Systems Architecture (1)
- Data Science (1)
- Data Storage Systems (1)
- E-Commerce (1)
- Information Literacy (1)
- Library and Information Science (1)
- Management Information Systems (1)
- Management Sciences and Quantitative Methods (1)
- Science and Technology Studies (1)
- Institution
Articles 1 - 24 of 24
Full-Text Articles in Engineering
Calculation Of Optimal Vocs Emission Reduction Based On Improved Seirs Model In Cloud Environment, Guangqiu Huang, Xixuan Zhao, Qiuqin Lu
Calculation Of Optimal Vocs Emission Reduction Based On Improved Seirs Model In Cloud Environment, Guangqiu Huang, Xixuan Zhao, Qiuqin Lu
Journal of System Simulation
Abstract: Volatile organic compounds (VOCs) emissions in different regions are correlated and influenced. In order to minimize the impact of VOCs on the atmospheric environment and achieve synergistic governance of VOCs regions, an optimal emission reduction model is established with the maximum VOCs emission reduction as the primary goal. An improved SEIRS infectious disease dynamics optimization algorithm considering environmental pollution(SEIRS-CE) is proposed and the model is solved in cloud environment. Taking Xi'an city as an example, the SEIRS-CE algorithm is used in Ali cloud server to calculate the emission reduction of VOCs associated with 13 meteorological monitoring stations in Xi …
Development Opportunities And Application Prospects Of Aero-Engine Simulation Technology Under Digital Transformation, Jianguo Cao
Development Opportunities And Application Prospects Of Aero-Engine Simulation Technology Under Digital Transformation, Jianguo Cao
Journal of System Simulation
Abstract: The development of China's social economy and the improvement of its national defense capability in the new era put forward higher requirements for the development of aero-engines. It is urgent to promote the digital transformation of aero-engines in order to achieve coordinated, agile and efficient aero-engine development. Based on the current research and development of aero-engine in China, this paper clarifies the new connotation of "speediness and efficiency, accurate mapping, comprehensive coverage, and dynamic prediction" given by the development of emerging cutting-edge technologies to aero-engine simulation technology, as well as the new technical features of "spatio-temporal ubiquity, data driven, …
Enhanced Load Balancing Based On Hybrid Artificial Bee Colony With Enhanced Β-Hill Climbing In Cloud, Maha Zeedan, Gamal Attiya, Nawal El-Fishawy
Enhanced Load Balancing Based On Hybrid Artificial Bee Colony With Enhanced Β-Hill Climbing In Cloud, Maha Zeedan, Gamal Attiya, Nawal El-Fishawy
Mansoura Engineering Journal
This paper proposes enhanced load balancer based artificial bee colony and β-Hill climbing for improving the performance metrics such as response time, processing cost, and utilization to avoid overloaded or under loaded situations of virtual machines. In this study, the suggested load balancer is called enhanced load balancing based on hybrid artificial bee colony with enhanced β-Hill climbing (ELBABCEβHC) to improve the response time, processing cost and the resource utilization. Our proposed approach starts by ranking the task then the greedy randomized adaptive search procedure (GRASP) is used in initializing populations. Further, the binary artificial bee colony (BABC) enhanced with …
Blmdp: A New Bi-Level Markov Decision Process Approach To Joint Bidding Andtask-Scheduling In Cloud Spot Market, Mona Naghdehforoushha, Mehdi Dehghan Takht Fooladi, Mohammad Hossein Rezvani, Mohammad Mehdi Gilanian Sadeghi
Blmdp: A New Bi-Level Markov Decision Process Approach To Joint Bidding Andtask-Scheduling In Cloud Spot Market, Mona Naghdehforoushha, Mehdi Dehghan Takht Fooladi, Mohammad Hossein Rezvani, Mohammad Mehdi Gilanian Sadeghi
Turkish Journal of Electrical Engineering and Computer Sciences
In the cloud computing market (CCM), computing services are traded between cloud providers and consumers in the form of the computing capacity of virtual machines (VMs). The Amazon spot market is one of the most well-known markets in which the surplus capacity of data centers is auctioned off in the form of VMs at relatively low prices. For each submitted task, the user can offer a price that is higher than the current price. However, uncertainty in the market environment confronts the user with challenges such as the variable price of VMs and the variable number of users. An appropriate …
Big Data With Cloud Computing: Discussions And Challenges, Amanpreet Kaur Sandhu
Big Data With Cloud Computing: Discussions And Challenges, Amanpreet Kaur Sandhu
Big Data Mining and Analytics
With the recent advancements in computer technologies, the amount of data available is increasing day by day. However, excessive amounts of data create great challenges for users. Meanwhile, cloud computing services provide a powerful environment to store large volumes of data. They eliminate various requirements, such as dedicated space and maintenance of expensive computer hardware and software. Handling big data is a time-consuming task that requires large computational clusters to ensure successful data storage and processing. In this work, the definition, classification, and characteristics of big data are discussed, along with various cloud services, such as Microsoft Azure, Google Cloud, …
Job Scheduling And Simulation In Cloud Based On Deep Reinforcement Learning, Qirui Li, Xinyi Peng
Job Scheduling And Simulation In Cloud Based On Deep Reinforcement Learning, Qirui Li, Xinyi Peng
Journal of System Simulation
Abstract: To solve the difficulty in job scheduling in the complex and transient multi-user, multi-queue, and multi-data-center cloud computing environment, this paper proposed a job scheduling method based on deep reinforcement learning. A system model of cloud job scheduling and its mathematical model were built, and an optimization goal consisting of transmission time, waiting time, and execution time was obtained. A job scheduling algorithm based on deep reinforcement learning was designed, and its state space, action space, and reward function were given. A simulated cloud job scheduler was designed and developed, and simulated scheduling experiments were conducted on it. The …
A Novel Data Placement Strategy To Reduce Data Traffic During Run-Time, Sridevi Sridhar, Rhymend Uthariaraj Vaidyanathan
A Novel Data Placement Strategy To Reduce Data Traffic During Run-Time, Sridevi Sridhar, Rhymend Uthariaraj Vaidyanathan
Turkish Journal of Electrical Engineering and Computer Sciences
High impact scientific applications processed in distributed data centers often involve big data. To avoid the intolerable delays due to huge data movements across data centers during processing, the concept of moving tasks to data was introduced in the last decade. Even after the realization of this concept termed as data locality, the expected quality of service was not achieved. Later, data colocality was introduced where data groupings were identified and then data chunks were placed wisely. However, the aspect of the expected data traffic during run time is generally not considered while placing data. To identify the expected data …
Distributed Denial Of Service Attack Detection In Cloud Computing Using Hybridextreme Learning Machine, Gopal Singh Kushwah, Virender Ranga
Distributed Denial Of Service Attack Detection In Cloud Computing Using Hybridextreme Learning Machine, Gopal Singh Kushwah, Virender Ranga
Turkish Journal of Electrical Engineering and Computer Sciences
One of the major security challenges in cloud computing is distributed denial of service (DDoS) attacks. In these attacks, multiple nodes are used to attack the cloud by sending huge traffic. This results in the unavailability of cloud services to legitimate users. In this research paper, a hybrid machine learning-based technique has been proposed to detect these attacks. The proposed technique is implemented by combining the extreme learning machine (ELM) model and the blackhole optimization algorithm. Various experiments have been performed with the help of four benchmark datasets namely, NSL KDD, ISCX IDS 2012, CICIDS2017, and CICDDoS2019, to evaluate the …
Qos-Aware Scheduling For Data Intensive Workflow, Wan Cong, Cuirong Wang, Wang Cong
Qos-Aware Scheduling For Data Intensive Workflow, Wan Cong, Cuirong Wang, Wang Cong
Journal of System Simulation
Abstract: The development of technology enables people to access resources from different data centers. Resource management and scheduling of applications, such as workflow, that are deployed on the cloud computing environment have already become a hot spot. A QoS-aware scheduling algorithm for data intensive workflow on multiple data center environment was proposed. Scheduling data intensive workflow on multiple data center environment has two characteristics: A large amount of data is distributed in different geographical locations, the process of data migration will consume a large amount of time and bandwidth; secondly, the data centers have different price and resources. Data migration …
Information Collaboration Model Of Cloud Computing Supply Chain Based On Multi-Agent, Wuxue Jiang, Xuanzi Hu, Minxia Liu, Yuqiang Chen
Information Collaboration Model Of Cloud Computing Supply Chain Based On Multi-Agent, Wuxue Jiang, Xuanzi Hu, Minxia Liu, Yuqiang Chen
Journal of System Simulation
Abstract: In order to improve the work efficiency of supply chain in cloud computing and avoid the risks of cloud computing, a cloud-based supply chain information coordination model was proposed. The model has two basic states which are online status and offline status, at online state the cloud computing center is responsible for coordination of the entire supply chain information, and at offline state each node continues to complete the transaction order through the history record and each node information in the cloud data center. Simulation based on Multi-agent shows that the order completion rate in offline status is …
A Novel Greedy Based Algorithm For Resource Allocation In Cloud Computing Environment, Vijendra Pratap Singh
A Novel Greedy Based Algorithm For Resource Allocation In Cloud Computing Environment, Vijendra Pratap Singh
Manipal Journal of Science and Technology
Resource allocation in a cloud computing environment means a mechanism to allocate different cloudlets to the available cloud resources on the basis of some criteria like cloudlets’ characteristics and/or requirements. It is one of the major challenges for cloud providers. Cloud providers have introduced many models for resource allocation. In this paper, we have proposed a greedy-based resource allocation algorithm. Here, first of all, the given cloudlets are classified into two categories: computational cloudlets and interactive cloudlets on the basis of some parameters. Next according to their category, they are allocated differently. The performance metrics of this newly proposed algorithm …
Performance Modeling Of Cryptographic Service System Virtualization Based On Issm, Songhui Guo, Qingbao Li, Sun Lei, Xuerong Gong, Tianchi Yang
Performance Modeling Of Cryptographic Service System Virtualization Based On Issm, Songhui Guo, Qingbao Li, Sun Lei, Xuerong Gong, Tianchi Yang
Journal of System Simulation
Abstract: The complicated architecture of cryptographic service system virtualization raised the difficulty of performance modeling. A performance modeling approach based on ISSMs was proposed. The approach divided the execution process into two stages, host preprocessing and arithmetic-module calculating, and built two sub-models based on queuing theory. On this basis, the effectiveness of this approach was verified. The results show that this method can analyze the impacts on system performance caused by task arrival rates, host and cryptographic card configurations quantitatively, and also be helpful for providing reasonable solutions to deploy virtualized cryptographic service system on cloud computing platforms.
Modeling And Simulation Of Complex Equipment Health Management System Based On Cloud Computing, Tianrui Zhang, Chuansheng Qu, Baoku Wu, Jianan Xu
Modeling And Simulation Of Complex Equipment Health Management System Based On Cloud Computing, Tianrui Zhang, Chuansheng Qu, Baoku Wu, Jianan Xu
Journal of System Simulation
Abstract: For complex equipment operation safely, the health management problems of complex equipment life cycle is analyzed. In order to realize remote service, complex equipment health management mode based on cloud computing is proposed. Aiming at the accuracy problem in the process of extracting and recognizing complex equipment characteristic data, the feature knowledge acquisition method based on ontology is researched, and the expression and acquisition algorithm of state characteristic knowledge is proposed. A task sequencing algorithm faults based on fuzzy comprehensive evaluation method is proposed, an appropriate task assignment model is selected for scheduling health management technicians. …
A Cloud Service Composition Optimization Based On Hnn, Huili Zhang, Zhihe Li
A Cloud Service Composition Optimization Based On Hnn, Huili Zhang, Zhihe Li
Journal of System Simulation
Abstract: With the rapid development of Cloud service application, how to effectively optimize the composition of Cloud services on cloud platform and improve the overall performance of cloud platform system have become an urgent research issue. In order to improve the efficiency of Cloud services, a combined optimization model based on Hopfield neural network is proposed. The problem of Cloud services is modeled. The problem is expressed as Hopfield Neural Network energy model for optimization, and a PSO group algorithm with Cauchy disturbance is designed to improve the Hopfield model. The experimental comparison shows that the method can improve …
Cloud Job Scheduling Model Based On Improved Plant Growth Algorithm, Li Qiang, Xiaofeng Liu
Cloud Job Scheduling Model Based On Improved Plant Growth Algorithm, Li Qiang, Xiaofeng Liu
Journal of System Simulation
Abstract: The performance of cloud job scheduling algorithm has a great importance to the whole cloud system. The key factors that affect cloud operation scheduling are found out, and a resource constraint model is established. The existing simulation plant growth algorithm is improved based on the Logistic model of plant growth law, so that the plant growth way was made to change according to the energy power. The comparison of four different plant models was carried out and their different features were analyzed. Compared with 6 typical cloud job scheduling algorithms, it is concluded that the improved simulation plant growth …
Cloud-Supported Machine Learning System For Context-Aware Adaptive M-Learning, Muhammad Adnan, Asad Habib, Jawad Ashraf, Shafaq Mussadiq
Cloud-Supported Machine Learning System For Context-Aware Adaptive M-Learning, Muhammad Adnan, Asad Habib, Jawad Ashraf, Shafaq Mussadiq
Turkish Journal of Electrical Engineering and Computer Sciences
It is a knotty task to amicably identify the sporadically changing real-world context information of a learner during M-learning processes. Contextual information varies greatly during the learning process. Contextual information that affects the learner during a learning process includes background knowledge, learning time, learning location, and environmental situation. The computer programming skills of learners improve rapidly if they are encouraged to solve real-world programming problems. It is important to guide learners based on their contextual information in order to maximize their learning performance. In this paper, we proposed a cloud-supported machine learning system (CSMLS), which assists learners in learning practical …
A Novel Resource Clustering Model To Develop An Efficient Wireless Personal Cloud Environment, Kowsigan Mohan, Balasubramanie Palanisamy
A Novel Resource Clustering Model To Develop An Efficient Wireless Personal Cloud Environment, Kowsigan Mohan, Balasubramanie Palanisamy
Turkish Journal of Electrical Engineering and Computer Sciences
In the current era, cloud computing is the major focus of distributed computing and it helps in satisfying the requirements of the business world. It provides facilities on demand under all the parameters of the computing, such as infrastructure, platform, and software, across the globe. One of the major challenges in the cloud environment is to cluster the resources and schedule the jobs among the resource clusters. Many existing approaches failed to provide an optimal solution for job scheduling due to inefficient clustering of resources. In the proposed system, a novel algorithm called resource differentiation based on equivalence node potential …
Understanding The Determinants Affecting The Continuance Intention To Use Cloud Computing, Shailja Tripathi Dr.
Understanding The Determinants Affecting The Continuance Intention To Use Cloud Computing, Shailja Tripathi Dr.
Journal of International Technology and Information Management
Cloud computing has been progressively implemented in the organizations. The purpose of the paper is to understand the fundamental factors influencing the senior manager’s continuance intention to use cloud computing in organizations. A conceptual framework was developed by using the Technology Acceptance Model (TAM) as a base theoretical model. A questionnaire was used to collect the data from several companies in IT, manufacturing, finance, pharmaceutical and retail sectors in India. The data analysis was done using structural equation modeling technique. Perceived usefulness and perceived ubiquity are identified as important factors that affect continuance intention to use cloud computing. In addition, …
Hadoop Framework Implementation And Performance Analysis On A Cloud, Göksu Zeki̇ye Özen, Mehmet Tekerek, Rayi̇mbek Sultanov
Hadoop Framework Implementation And Performance Analysis On A Cloud, Göksu Zeki̇ye Özen, Mehmet Tekerek, Rayi̇mbek Sultanov
Turkish Journal of Electrical Engineering and Computer Sciences
The Hadoop framework uses the MapReduce programming paradigm to process big data by distributing data across a cluster and aggregating. MapReduce is one of the methods used to process big data hosted on large clusters. In this method, jobs are processed by dividing into small pieces and distributing over nodes. Parameters such as distributing method over nodes, the number of jobs held in a parallel fashion, and the number of nodes in the cluster affect the execution time of jobs. The aim of this paper is to determine how the numbers of nodes, maps, and reduces affect the performance of …
Designing A Vm-Level Vertical Scalability Service In Current Cloud Platforms: A New Hope For Wearable Computers, Mustafa Kaiiali
Designing A Vm-Level Vertical Scalability Service In Current Cloud Platforms: A New Hope For Wearable Computers, Mustafa Kaiiali
Turkish Journal of Electrical Engineering and Computer Sciences
Public clouds are becoming ripe for enterprise adoption. Many companies, including large enterprises, are increasingly relying on public clouds as a substitute for, or a supplement to, their own computing infrastructures. On the other hand, cloud storage service has attracted over 625 million users. However, apart from the storage service, other cloud services, such as the computing service, have not yet attracted the end users' interest for economic and technical reasons. Cloud service providers offers horizontal scalability to make their services scalable and economical for enterprises while it is still not economical for the individual users to use their computing …
The Kriging Cloud Computing Framework: Interpolation Of Topography By Cloud Computing With The Kriging Algorithm, Cheng-Tsan Lai, Sung-Shan Hsiao, Hui-Ming Fang, Edward H. Wang
The Kriging Cloud Computing Framework: Interpolation Of Topography By Cloud Computing With The Kriging Algorithm, Cheng-Tsan Lai, Sung-Shan Hsiao, Hui-Ming Fang, Edward H. Wang
Journal of Marine Science and Technology
Spatial information surveyed by photogrammetry, airborne LiDAR and Mobile Measurement System (MMS) above ground level can be analyzed by scientists using standard geostatistical methodologies such as ordinary Kriging and sequential Gaussian simulation to interpolate heterogeneities of profiles from sparse sample data. Proven effective by researchers, the Kriging algorithm model is used by commercial data analysis packages for instant interpolation. However, meaningful and reliable results only come with a comprehensive understanding of the variogram associated with valid mathematical functions. To capture spatial landscape variations from massive sample grids of satellite images, this paper presents a cloud computing-based automation approach to improve …
Synthesis Of Real-Time Cloud Applications For Internet Of Things, Slawomir Bak, Radoslaw Czarnecki, Stanislaw Deniziak
Synthesis Of Real-Time Cloud Applications For Internet Of Things, Slawomir Bak, Radoslaw Czarnecki, Stanislaw Deniziak
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents the methodology for the synthesis of real-time applications working in the ``Internet of Things'' environment. We propose the client-server architecture, where embedded systems act as smart clients and the Internet application is a server of the system. The architecture of the application conforms to the cloud computing model. Since centralized systems are prone to bottlenecks caused by accumulation of transmissions or computations, we propose the distributed architecture of the server and the methodology that constructs this architecture using Internet resources supported by a cloud provider. We assume that the function of the server is specified as a …
A State-Of-The-Art Review Of Cloud Forensics, Sameera Almulla, Youssef Iraqi, Andrew Jones
A State-Of-The-Art Review Of Cloud Forensics, Sameera Almulla, Youssef Iraqi, Andrew Jones
Journal of Digital Forensics, Security and Law
Cloud computing and digital forensics are emerging fields of technology. Unlike traditional digital forensics where the target environment can be almost completely isolated, acquired and can be under the investigators control; in cloud environments, the distribution of computation and storage poses unique and complex challenges to the investigators. Recently, the term “cloud forensics” has an increasing presence in the field of digital forensics. In this state-of-the-art review, we included the most recent research efforts that used “cloud forensics” as a keyword and then classify the literature into three dimensions: (1) survey-based, (2) technology-based and (3) forensics-procedural-based. We discuss widely accepted …
Applying The Acpo Principles In Public Cloud Forensic Investigations, Harjinder S. Lallie, Lee Pimlott
Applying The Acpo Principles In Public Cloud Forensic Investigations, Harjinder S. Lallie, Lee Pimlott
Journal of Digital Forensics, Security and Law
The numerous advantages offered by cloud computing has fuelled its growth and has made it one of the most significant of current computing trends. The same advantages have created complex issues for those conducting digital forensic investigations. Digital forensic investigators rely on the ACPO (Association of Chief Police Officers) or similar guidelines when conducting an investigation, however the guidelines make no reference to some of the issues presented by cloud investigations. This study investigates the impact of cloud computing on ACPO’s core principles and asks whether these principles can still be applied in a cloud investigation and the challenges presented …