• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.1-7
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• 2019

The latest mobile applications such as augmented reality, virtual reality, and deep learning can be used efficiently in various fields such as emergency management and game. Accordingly the corresponding applications have been developed for these purposes. However modern mobile applications such as augmented reality and virtual reality increase the energy burden on mobile devices. In order for mobile devices to focus their energy on the latest mobile applications, energy consumption should be minimized for communication and networking, such as cognitive radio. In this paper, we propose a method to reduce the energy consumption of Centralized Cooperative Spectrum Sensing (CCSS) scheme in cognitive radio by devising Stop Reporting Algorithm (SRA). Simulation results show that SRA can reduce energy consumption of mobile devices using cognitive radio.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.1-7
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• 2022

IoT technology that utilizes wireless body area networks (WBAN) and biosensors is an important field in the health industry to minimize resources and monitor patients. In order to integrate IoT and WBAN, a cooperative protocol that constitutes WBAN's limited sensor nodes and rapid routing for efficient data transmission is required. In this paper we propose an we propose an energy efficient and cooperative link energy-efficient routing strategy(LEERS) to solve the problems of redundant data transmission detection and limited network sensor lifetime extention. The proposed scheme considers the hop count node congestion level towards the residual energy sink and bandwidth and parameters. In addition, by determining the path cost function and providing effective multi-hop routing, it is shown that the existing method is improved in terms of residual energy and throughput

• The KIPS Transactions:PartA
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• v.10A no.6
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• pp.635-642
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• 2003

The radical development of recent network technology provides the basic foundation which can establish a high speed and cheap cluster system. It is a general trend that conventional cluster systems are built as the system over a fixed level based on stabilized and high speed local networks. A multi-distributed web cluster group is a web cluster model which can obtain high performance, high efficiency and high availability through mutual cooperative works between effective job division and system nodes through parallel performance of a given work and shared memory of SC-Server with low price and low speed system nodes on networks. For this, multi-distributed web cluster group builds a sub-cluster group bound with single imaginary networks of multiple system nodes and uses the web distributed shared memory of system nodes for the effective data transmission within sub-cluster groups. Since the presented model uses a load balancing and parallel computing method of large-scale work required from users, it can maximize the processing efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4268-4290
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• 2015

Future mobile communications face enormous challenges as traditional voice services are replaced with increasing mobile multimedia and data services. To address the vast data traffic volume and the requirement of user Quality of Experience (QoE) in the next generation mobile networks, it is imperative to develop efficient content distribution technique, aiming at significantly reducing redundant data transmissions and improving content delivery performance. On the other hand, in recent years cloud computing as a promising new content-centric paradigm is exploited to fulfil the multimedia requirements by provisioning data and computing resources on demand. In this paper, we propose a cooperative caching framework which implements State based Content Distribution (SCD) algorithm for future mobile networks. In our proposed framework, cloud service providers deploy a plurality of cloudlets in the network forming a Distributed Cloud Service Network (DCSN), and pre-allocate content services in local cloudlets to avoid redundant content transmissions. We use content popularity and content state which is determined by content requests, editorial updates and new arrivals to formulate a content distribution optimization model. Data contents are deployed in local cloudlets according to the optimal solution to achieve the lowest average content delivery latency. We use simulation experiments to validate the effectiveness of our proposed framework. Numerical results show that the proposed framework can significantly improve content cache hit rate, reduce content delivery latency and outbound traffic volume in comparison with known existing caching strategies.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.4
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• pp.321-330
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• 1999

Automation of observation and positioning of fiducial marks is made possible with the application of image matching technique, developed through the cooperative research effort of computer vision and digital photogrammetry. The major problem in such automation effort is to minimize the computing time and to increase the positional accuracy. Except for scanning and ground control surveying, the interior orientation process was automated in this study, through the development of an algorithm which applies the image matching and image processing techniques. The developed system was applied to close-range photogrammetry and the analysis of the results showed 54% improvement in processing time. For fiducial mark observation during interior orientation, the Laplacian of Gaussian transformation and the Hough transformation were applied to determine the accurate position of the center point, and the correlation matching and the least squares matching method were then applied to improve the accuracy of automated observation of fiducial marks. Image pyramid concept was applied to reduce the computing time of automated positioning of fiducial mark.

• The KIPS Transactions:PartC
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• v.8C no.6
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• pp.731-740
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• 2001

Multi-distributed web cluster model expanding conventional cluster system is the cluster system which processes large-scaled work demanded from users with parallel computing method by building a number of system nodes on open network into a single imaginary network. Multi-distributed web cluster model on the structured characteristics exposes internal system nodes by an illegal third party and has a potential that normal job performance is impossible by the intentional prevention and attack in cooperative work among system nodes. This paper presents the mutual authentication protocol of system nodes through key division method for the authentication of system nodes concerned in the registration, requirement and cooperation of service code block of system nodes and collecting the results and then designs SNKDC which controls and divides symmetrical keys of the whole system nodes safely and effectively. SNKDC divides symmetrical keys required for performing the work of system nodes and the system nodes transmit encoded packet based on the key provided. Encryption packet given and taken between system nodes is decoded by a third party or can prevent the outflow of information through false message.

• The KIPS Transactions:PartA
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• v.9A no.1
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• pp.29-36
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• 2002

For the efficient collaboration awareness, the CSCW (Computer-Supported Cooperative Work) systems provide functions such as telepointing, snap-shot, and document/project tracking. Among these, telepointing allows an event occurrence on the shared window of a local computing system to be presented in remote computing systems. Although telepointing has been mentioned in the literature, few research papers deal with the functional requirements and protocols for telepointing. This parer describes the functional requirements and payload format for RTP (Real-Time Transport Protocol)-based telepointing. In order to evaluate the performance of the proposed RTP-barred telepointing, we have implemented a whiteboard and compared it with that of the Microsoft Netmeeting. The evaluation results show that the proposed telepointing performs better in terms of CPU usage and the amount of network traffic.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.268-282
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• 2022

One of the most important technologies today is augmented reality technology, it allows users to experience the real world using virtual objects that are combined with the real world. This technology is interesting and has become applied in many sectors such as the shopping and medicine, also it has been included in the sector of education. In the field of education, AR technology has become widely used due to its effectiveness. It has many benefits, such as arousing students' interest in learning imaginative concepts that are difficult to understand. On the other hand, studies have proven that collaborative between students increases learning opportunities by exchanging information, and this is known as Collaborative Learning. The use of multimodal creates a distinctive and interesting experience, especially for students, as it increases the interaction of users with the technologies. The research aims at developing collaborative framework for developing achievement of 6th graders through designing a framework that integrated a collaborative framework with a multimodal input "hand-gesture and touch", considering the development of an effective, fun and easy to use framework with a multimodal interaction in AR technology that was applied to reformulate the genetics and traits lesson from the science textbook for the 6th grade, the first semester, the second lesson, in an interactive manner by creating a video based on the science teachers' consultations and a puzzle game in which the game images were inserted. As well, the framework adopted the cooperative between students to solve the questions. The finding showed a significant difference between post-test and pre-test of the experimental group on the mean scores of the science course at the level of remembering, understanding, and applying. Which indicates the success of the framework, in addition to the fact that 43 students preferred to use the framework over traditional education.

• Journal of Internet Computing and Services
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• v.6 no.2
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• pp.141-152
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• 2005

Many organizations have been recognizing the necessity of workflow automation technologies according to the rapid expansion of business process oriented applications, such as enterprise resource pianning, customer relationship management, electronic approval management, and so on, Thus, they have started adopting workflow management systems as an essential technological solution for their workflow processes, However, we need some technological extensions and improvements on them in order to accommodate a new type of workflow processes, which is called cross-organizational global workflow processes that require a certain level of collaborations between the organizations engaged in the global workflow processes, Fragment-driven workflow modeling methodology is a Bottom-Up methodology composing a global workflow by defining each organization's own activities, which is called a fragment through a realtime cooperative system. The approach is able to not only simplify the modeling work but also keep each organization's independence in modeling a global workflow, In this paper, we describe the fragment-driven workflow modeling methodology and realize the methodology through the implementation of a cooperative swimlane workflow modeling system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1951-1975
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• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.