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Full-Text Articles in Computer Engineering
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 …
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 …
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 …
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 …
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 …