• KIISE Transactions on Computing Practices
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• v.23 no.2
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• pp.85-96
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• 2017

IoT-Cloud service, integration of Internet of Things (IoT) and Cloud, is becoming a critical model for realizing creative and futuristic application services. Since IoT machines have little computing capacity, it is effective to attaching public Cloud resources for realizing IoT-Cloud service. Furthermore, utilizing containers and adopting a microservice architecture for developing IoT-Cloud service are useful for effective realization. The quality of microservice based IoT-Cloud service is affected by service function chaining which inter-connects each functions. For example, an issue with some of the functions or a bottleneck of inter-connection can degrade the service quality. To ensure functionality of the entire service, various test procedures considering various service environments are required to improve the service continuously. Hence in this paper, we introduce experimental realization of continuous integration based on DevOps and employ application performance monitoring for Node.js based IoT-Cloud service. Then we discuss its effectiveness.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2450-2460
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• 2015

Recently, as interest in IoT (Internet of Things) increase, research and standardization of a new protocol which reflects the characteristics of IoT has progressed. Among them, RPL(IPv6 for Low-Power Lossy Network) is a standardized routing protocol for IoT. RPL utilizes DIO (DODAG Information Object) messages which is flooded from the sink node to the whole network for path establish and maintenance. However, in large scale networks, not only a long time is required to propagate the DIO message to the whole networks but also a bottleneck effect around the sink node is occurred. Multi-sink based approaches which take advantage of reducing routing overhead and bottleneck effect are widely used to solve these problems. In this paper, we define 'unnecessary path update problems' that may arise when applying the RPL protocol to the multi sink based IoT networks and propose two methods namely Routing Metric based Path Update Decision method and Immediate Successor based Path Update Decision method for selective routing update.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.107-110
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• 2017

According to researches, while the speed of processor and network in embedded devices is fast enough to meet user requirement, the IO speed is recognized as the main performance bottleneck. Meanwhile it is known that more than 70 percent of IOs are issued from SQLite database. Many researches related SQLite performance optimization is based on WAL mode because WAL mode optimized for write IO performance. In this paper, I propose to optimize SQLite with Atomic Write in the Rollback Journal Mode, which is mainly used in Android and Tizen. I have observed that Atomic Write have a significant write performance improvement(300%) by reducing write, file sync operation and memory usage improvement(80%). Additionally it can block JOJ(Journaling of Journal) and extend the life of the flash memory.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.300-306
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• 2021

Due to the development of IT technology, hardware technologies applied to IoT equipment have recently been developed, so smart systems using low-cost, high-performance RF and computing devices are being developed. However, in the infrastructure environment where a large amount of IoT devices are installed, big data collection causes a load on the collection server due to a bottleneck between the transmitted data. As a result, data transmitted to the data collection server causes packet loss and reduced data throughput. Therefore, there is a need for an efficient big data collection technique in an infrastructure environment where a large amount of IoT devices are installed. Therefore, in this paper, we propose an efficient big data collection technique in an infrastructure environment where a vast amount of IoT devices are installed. As a result of the performance evaluation, the packet loss and data throughput of the proposed technique are completed without loss of the transmitted file. In the future, the system needs to be implemented based on this design.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.151-157
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• 2021

Recently, IoT technology has been applied to various cloud environments, requiring accurate verification of various information generated by IoT devices. However, due to the convergence of IoT technologies and 5G technologies, accurate analysis is required as IoT information processing is rapidly processed. This paper proposes a blockchain-based multi-IoT verification model for overlay cloud environments. The proposed model multi-processes IoT information by further classifying IoT information two layers (layer and layer) into bits' blockchain to minimize the bottleneck of overlay networks while ensuring the integrity of information sent and received from embedded IoT devices within local IoT groups. Furthermore, the proposed model allows the layer to contain the weight information, allowing IoT information to be easily processed by the server. In particular, transmission and reception information between IoT devices facilitates server access by distributing IoT information from bits into blockchain to minimize bottlenecks in overlay networks and then weighting IoT information.

• Journal of Korea Multimedia Society
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• v.19 no.7
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• pp.1166-1178
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• 2016

In Internet of Things (IoT) environments, billions of interconnected devices and multimedia sensors generate a huge amount of multimedia traffic. Since the environment are in general deployed as a server-centric architecture wireless sensor networks could be bottlenecks between IoT gateways and IoT devices. The bottleneck causes high power consumption of the device and triggers very heavy network overload by transmission of sensing data. The deterioration could decrease the quality of multimedia streaming service due to delay, loss, and waste of device power. Thus, in this paper, we propose a context-based adaptive multimedia streaming scheme to support enhanced QoS and low power consumption in IoT environments. The goal of the scheme is to increase quality score per voltage of the streaming service, given an adaptation algorithm with context that are classified network and hardware such as throughput, RTT, and CPU usage. From the both context, the quality score per voltage is used in the comparison of a only network context-based adaptive multimedia streaming scheme, a fixed multimedia streaming and our scheme. As a result, we achieves a high improvement that means the quality score per voltage is increased up to about 4, especially in case of resolution change.

• Journal of KIISE
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• v.42 no.10
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• pp.1268-1279
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• 2015

In order to manage a large number of devices connected to the Internet of Things (IoT), the Internet Engineering Task Force (IETF) proposed the IPv6 Routing Protocol for Low Power and Lossy Networks (RPL). The route of the RPL network is generated through the use of an Objective Function (OF) that is suitable for the service that is required for the IoT network. Since the route of the RPL network is conventionally simply chosen only by considering the link quality between the nodes, it is sensible to seek an OF that can also provide better Quality of Service (QoS). In previous studies, the end-to-end delay might possibly be sub-optimal because they only deal with problems related to the reduction of energy consumption and not to the link quality on the path to the sink node. In this study, we propose a scheme that reduces the end-to-end delay but also gives full consideration to both the quality on the entire route to the destination and to the expected lifetime of nodes with bottlenecks from heaped traffic. Weighting factors for the proposed scheme are chosen by experiments and the proposed scheme can reduce the end-to-end delay and the energy consumption of previous studies by 20.8% and 10.5%, respectively.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.476-477
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• 2013

Gadget-2 is a scientific simulation code has been used for many different types of simulations like, Colliding Galaxies, Cluster Formation and the popular Millennium Simulation. The code is parallelized with Message Passing Interface (MPI) and is written in C language. There is also a Java adaptation of the original code written using MPJ Express called Java Gadget. Java Gadget writes a lot of checkpoint data which may or may not use the HDF-5 file format. Since, HDF-5 is MPI-IO compliant, we can use our MPJ-IO library to perform parallel reading and writing of the checkpoint files and improve I/O performance. Additionally, to add reliability to the code execution, we propose the usage of Hadoop Distributed File System (HDFS) for writing the intermediate (checkpoint files) and final data (output files). The current code writes and reads the input, output and checkpoint files sequentially which can easily become bottleneck for large scale simulations. In this paper, we propose Sim-Hadoop, a framework to leverage HDFS and MPJ-IO for improving the I/O performance of Java Gadget code.

• Smart Media Journal
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• v.11 no.3
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• pp.39-53
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• 2022

Cloud of Things (CoT) can provide IoT applications with unlimited storage functions and processing power supported by cloud services. However, in a centralized cloud of things, it can create a single point of failure that can lead to bottleneck problems, outages of the CoT network. In this paper, to solve the problem of centralized cloud of things and interoperate between different service domains, we propose an IoT service interoperability system using distributed fog computing and blockchain technology. Distributed fog is used to provide real-time data processing and services in fog systems located at a geographically close distance to IoT devices, and to enable service interoperability between each fog using smart contracts and distributed ledgers of the blockchain. The proposed system provides services within a region close to the distributed fog entrusted with the service from the cloud, and it is possible to access the services of other fogs without going through the cloud even between fogs. In addition, by sharing a service right token issuance information between the cloud and fog nodes using a blockchain network, the integrity of the token can be guaranteed and reliable service interoperability between fog nodes can be performed.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.1-7
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• 2022

Machine learning (ML) algorithms have been intended to seamlessly collaborate for enabling intelligent networking in terms of massive service differentiation, prediction, and provides high-accuracy recommendation systems. Mobile edge computing (MEC) servers are located close to the edge networks to overcome the responsibility for massive requests from user devices and perform local service offloading. Moreover, there are required lightweight methods for handling real-time Internet of Things (IoT) communication perspectives, especially for ultra-reliable low-latency communication (URLLC) and optimal resource utilization. To overcome the abovementioned issues, this paper proposed an intelligent scheme for traffic steering based on the integration of MEC and lightweight ML, namely support vector machine (SVM) for effectively routing for lightweight and resource constraint networks. The scheme provides dynamic resource handling for the real-time IoT user systems based on the awareness of obvious network statues. The system evaluations were conducted by utillizing computer software simulations, and the proposed approach is remarkably outperformed the conventional schemes in terms of significant QoS metrics, including communication latency, reliability, and communication throughput.