• Journal of Information Processing Systems
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• v.15 no.2
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• pp.440-448
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• 2019

The Internet of Things (IoT) is one of the main enablers for situation awareness needed in accomplishing smart cities. IoT devices, especially for monitoring purposes, have stringent timing requirements which may not be met by cloud computing. This deficiency of cloud computing can be overcome by fog computing for which fog nodes are placed close to IoT devices. Because of low capabilities of fog nodes compared to cloud data centers, fog nodes may not be deployed with all the services required by IoT devices. Thus, in this article, we focus on the issue of fog service placement and present the recent research trends in this issue. Most of the literature on fog service placement deals with determining an appropriate fog node satisfying the various requirements like delay from the perspective of one or more service requests. In this article, we aim to effectively place fog services in accordance with the pre-obtained service demands, which may have been collected during the prior time interval, instead of on-demand service placement for one or more service requests. The concept of the logical fog network is newly presented for the sake of the scalability of fog service placement in a large-scale smart city. The logical fog network is formed in a tree topology rooted at the cloud data center. Based on the logical fog network, a service placement approach is proposed so that services can be placed on fog nodes in a resource-effective way.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.636-641
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• 2018

In recent years, the Internet of things has grown rapidly and is being used in many fields. The function of an Internet device isto collect information in various environments and to provide useful information to users. Due to recent developments in technology, the kinds of Internet devices are increasing and the prices are getting cheaper. In addition, many open source platforms that are easy to use have been developed and are providing convenience to users. In this paper, wireless data transmission and cloud server system based on ESP-12E NodeMCU module was designed and sensor information collected from Internet devices was transmitted to cloud server through WiFi wireless communication. The collected sensor data was saved by creating channel and field in the cloud server and the data of each field was visualized as a graph.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.73-80
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• 2023

The recent growth in the use of mobile devices has contributed to increased computing and storage requirements. Cloud computing has been used over the past decade to cater to computational and storage needs over the internet. However, the use of various mobile applications like Augmented Reality (AR), M2M Communications, V2X Communications, and the Internet of Things (IoT) led to the emergence of mobile cloud computing (MCC). All data from mobile devices is offloaded and computed on the cloud, removing all limitations incorporated with mobile devices. However, delays induced by the location of data centers led to the birth of edge computing technologies. In this paper, we discuss one of the edge computing technologies, i.e., cloudlet. Cloudlet brings the cloud close to the end-user leading to reduced delay and response time. An algorithm is proposed for scheduling tasks on cloudlet by considering VM's load. Simulation results indicate that the proposed algorithm provides 12% and 29% improvement over EMACS and QRR while balancing the load.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.664-671
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• 2020

A Smart Building, one that uses automated processes to control its operations, refers in this study to one that uses both Internet of Things (IoT) devices and cloud services software. Cloud service providers (e.g. Amazon, Google, and Microsoft) have recently providedIoT cloud platform application services on IoT devices. According to Postscapes, there are now 152 IoT cloud platforms. Choosing one for a smart building is challenging. We selected Microsoft Azure IoT Hub and Amazon's AWS (Amazon Web Services) IoT. The two platforms were evaluated and selected from a smart building perspective. Each prototype was evaluated on two different IoTplatforms, assuming a typical smart building scenario. The selection was based on information and experience gained from developing the prototype system using the IoT cloud platform. The assessment made in this evaluation may be used to select an IoTcloud platform for smart buildings in the future.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.9
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• pp.27-35
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• 2016

Today, with the advance of Information and communication technology, 'Smart, connected' toys, which apply technologies related to IoT (Internet of Things) to traditional toys, are emerging and rapidly growing. This research aims to analyze the tendencies and limitations of smart, connected toys through exploring the representative cases of smart, connected toys based on characteristics of ICBM (Internet of Things, Cloud, Big-data, and Mobile) technology. For this study, we begin by understanding literature research about smart, connected toys and ICBM technology. Then, we extracted the characteristics of ICBM technology for connecting physical and digital environments through investigating cases to which ICBM technologies are applied. Based on the extracted characteristics, the case studies of smart, connected toys were conducted. In this research, we explore the level of ICBM technology application and limitation to smart, connected toys. We expect this research will contribute to providing guidelines for developing smart, connected toys based on the characteristics of the latest technology.

• Journal of Convergence for Information Technology
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• v.12 no.2
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• pp.23-29
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• 2022

Recently, due to the increase in the use of Internet of Things (IoT) devices, the amount of data transmitted and processed to cloud computing servers has increased rapidly. As a result, network problems (delay, server overload and security threats) are emerging. In particular, edge computing with lower computational capabilities than cloud computing requires a lightweight authentication algorithm that can easily authenticate numerous IoT devices.In this paper, we proposed a key-agreement protocol of a lightweight algorithm that guarantees anonymity and forward and backward secrecy between IoT and edge devices. and the proposed algorithm is stable in MITM and replay attacks for edge device and IoT. As a result of comparing and analyzing the proposed key-agreement protocol with previous studies, it was shown that a lightweight protocol that can be efficiently used in IoT and edge devices.

• International Journal of Advanced Culture Technology
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• v.5 no.2
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• pp.90-97
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• 2017

The Internet of Things(IoT) market is expected to grow from 15.5billion to 75.4 billion by 2015-2025. As the number of IoT devices increases, the amount of data that is sent to the cloud is increasing. Today's Cloud Computing models are not suited to handle the vast amount of data generated by IoT devices. In this paper, we propose a Cooperation Coordinator System that reduces server load and improved real-time processing capability under specific circumstances by using Band-Cloud. The cooperation coordinator system dynamically forms the cloud when cooperation is needed between mobile devices located near. It is called Band-Cloud. Band-Cloud provides services entrusted by Central Cloud. This paper describes the proposed system and shows the cooperation process using the Android-based mobile devices and Wi-Fi Direct technology. Such a system can be applied to cases where real-time processing is required in a narrow area such as a hospital ward or a school classroom.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.37-47
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• 2018

The number of capabilities of Internet of Things (IoT) devices will exponentially grow over the next years. These devices may generate a vast amount of time-constrained data. In the context of IoT, data management should act as a layer between the objects and devices generating the data and the applications accessing the data for analysis purposes and services. In addition, most of IoT services will be content-centric rather than host centric to increase the data availability and the efficiency of data delivery. IoT will enable all the communication devices to be interconnected and make the data generated by or associated with devices or objects globally accessible. Also, fog computing keeps data and computation close to end users at the edge of network, and thus provides a new breed of applications and services to end users with low latency, high bandwidth, and geographically distributed. In this paper, we propose Edge-Fog cloud-based Hierarchical Data Delivery ($EFcHD^2$) method that effectively and reliably delivers IoT data to associated with IoT applications with ensuring time sensitivity. The proposed $EFcHD^2$ method stands on basis of fully decentralized hybrid of Edge and Fog compute cloud model, Edge-Fog cloud, and uses information-centric networking and bloom filters. In addition, it stores the replica of IoT data or the pre-processed feature data by edge node in the appropriate locations of Edge-Fog cloud considering the characteristic of IoT data: locality, size, time sensitivity and popularity. Then, the performance of $EFcHD^2$ method is evaluated through an analytical model, and is compared to fog server-based and Content-Centric Networking (CCN)-based data delivery methods.

• Journal of information and communication convergence engineering
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• v.19 no.3
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• pp.166-174
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• 2021

A large volume of patient data is generated from various devices used in healthcare applications. With increase in the volume of data generated in the healthcare industry, more wellness monitoring is required. A cloud-enabled analysis of healthcare data that predicts patient risk factors is required. Machine learning techniques have been developed to address these medical care problems. A novel technique called the radix-trie-based Tanimoto kernel regressive infomax boost classification (RT-TKRIBC) technique is introduced to analyze the heterogeneous health data in the cloud to predict the health risks and send alerts. The infomax boost ensemble technique improves the prediction accuracy by finding the maximum mutual information, thereby minimizing the mean square error. The performance evaluation of the proposed RT-TKRIBC technique is realized through extensive simulations in the cloud environment, which provides better prediction accuracy and less prediction time than those provided by the state-of-the-art methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.5
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• pp.1149-1155
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• 2017

In these days, cloud environments such as cloud platforms, cloud services like Amazon AWS, IBM Bluemix are used in the Internet of Things for providing efficient services. These cloud platform environments have various security threats according to increasing of use, so the recent research results on cloud security and privacy protection technologies and related regimes and legislations are written in this paper and we suggest prospect of research on cloud platform environment security and privacy preserving.