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A Digital Forensic Process for Ext4 File System in the Flash Memory of IoT Devices
Junho Jeong, Beomseok Kim, Jinsung Cho
http://doi.org/10.5626/JOK.2021.48.8.865
With the recent rapid advances in digital communication technology, the spread of IoT(Internet of Things) has accelerated and IoT devices can be utilized to investigate crimes and accidents due to the close connection between human society and IoT devices. Accordingly, with the increasing importance of digital forensics, numerous studies have been conducted. However, most digital forensics research proposed only abstract methodologies due to the various types of IoT devices. In addition, binwalk, which is actively used as a firmware analysis tool, does not adequately analyze and extract the ext4 file system. To solve these problems, this paper proposes a proper extraction and analysis method and a practical process that could extract the ext4 file system from the flash memory of IoT devices using the binwalk with the proposed method. This study also verifies the proposed process with DJI Phantom 4 Pro V2.0 drone.
A Study on the Intelligent Delivery Management System Using UAV-Edge Computing Technology
Chu Myaet Thwal, Minkyung Lee, Choong Seon Hong
http://doi.org/10.5626/JOK.2020.47.12.1208
With the recent advancement of the digital and Internet-of-Things (IoT) technologies, cities globally are rapidly transforming into smart cities. In a parallel to the IoT technology, another technology that has substantially improved in recent years is the Unmanned Aerial Vehicle (UAV) technology, resulting in cheaper, more powerful and reliable UAVs. In this paper, we integrate the aid of the IoT and propose an intelligent delivery management system in coordination with edge computing and UAV technology. The proposed system is an innovative system that facilitates in reducing the operational delay of the delivery services and provides greater and faster facilities to customers. The whole procedure of the delivery process is managed by the edge-based control stations serving as the media between the retailers and UAVs. These stations are distributed across urban areas and are responsible for assigning tasks to the UAVs by performing crucial calculations and communications between the retailers and UAVs. By applying the proposed intelligent delivery scheme in smart city applications, it can be expected to reduce delays in delivery services because of the shortage of manual labor and traffic conditions, thus providing greater and faster facilities to the customers.
Automatic Convolution Neural Network Model Compression Framework for Resource-Constrained Embedded Systems
Jonghun Jeong, Dasom Lee, Hyeonseok Jung, Hoeseok Yang
http://doi.org/10.5626/JOK.2020.47.2.136
Recently, attempts have been made to directly execute various convolutional neural network applications in resource-constrained embedded systems such as IoT. However, since embedded systems have limited computational capability and memory, the size of the neural network model that can be executed is restricted and may not satisfy real-time constraints. Therefore, in this paper, we propose a framework that automatically compresses a given neural network model to satisfy memory and execution time requirements and automatically generates code that can be executed on the target embedded system. Using the proposed framework, we demonstrate that the given neural network models can be automatically optimized for two STM32 Nucleo series boards with different HW specifications for various execution time and memory requirements.
Enhancing Throughput of Sensor Data Acquisition using Mobile Device Information in Internet of Things
Cheonyong Kim, Sangdae Kim, Seungmin Oh, Kwansoo Jung
http://doi.org/10.5626/JOK.2020.47.1.109
Internet of Things (IoT) is a technology to provide emerging applications, such as remote data collection. Recently, the active deployment of wireless sensors and the explosive increase in the number of mobile devices has enabled opportunistic data collection (ODC), in which mobile devices collect data from distributed sensors. In ODC, the sensor data can be collected without the additional overhead of installing and operating a network infrastructure. However, the time duration for data transfer cannot be guaranteed due to the unpredictable mobility of mobile devices in ODC. Therefore, existing studies have used a conservative flow control mechanism focusing on reliable data transfer. However, the conservative flow control degrades the data collection performance when the time duration for data transfer is sufficiently long. In this paper, an efficient flow control scheme was proposed for enhancing the data collection performance of ODC. The proposed scheme is based on the communication time between a mobile device and a sensor. The efficiency-oriented flow control mechanism is applied with a long communication time, while a short communication time leads to the reliability-oriented flow control mechanism. By using the proposed scheme, the data collection performance can be enhanced without degrading the reliability of data transfer.
Semantic Web-based Gateway System for Providing Autonomous Context-Aware Service in IoT Environment
http://doi.org/10.5626/JOK.2019.46.7.706
With the rapid growth of the IoT (Internet of Things) market, seamless connection between independently developed platforms has become an important issue. In addition, research is underway on auto-configuration to minimize human interference while configuring devices for users to utilize IoT applications. However, to realize fully autonomous systems, the machine should be able to perform autonomous interaction between devices by recognizing the context as well as autoconfiguration. In this paper, we propose a semantic Web-based gateway system for providing autonomous context-aware service in IoT environment. The proposed system autonomously performs inter-device interaction by recognizing the state of the device and user-defined rules. Through the real-world implementation, we verify the feasibility of the proposed system.
An Optimization Method for Perceived Quality of Services in Service-oriented V2X Software Environments
HyeongCheol Moon, KyeongDeok Baek, In-Young Ko
http://doi.org/10.5626/JOK.2019.46.7.664
Recent advancements in computing technologies have led to researches on large-scale Cyber Physical System (CPS) applications such as Vehicle-to-Everything (V2X) applications. Numerous researchers have attempted to apply service computing technologies to V2X environments to make them more flexible and reliable. In a service-oriented V2X environment, users receive services through the Internet of Things (IoT) devices. Most of the existing V2X environments estimate or evaluate service quality from the network point of view. Apparently, the users" perceived Quality of Service (QoS), which is affected by various factors in V2X environments, especially by the users’ mobility, cannot be guaranteed. In the present work, we investigate the mobility-related factors that affect the users’ perceived QoS with an aim to optimize the users’ perceived QoS in V2X environments and propose an algorithm that considers the effectiveness of delivering service effects and the overhead of service handover among different IoT devices. We conducted a series of experiments, and it was observed that our QoS optimization approach outperforms the existing methods that consider only the quality factors in the network"s perspective.
Weather Ontology System in IoT Middleware
Yujin Kim, Soobin Jeon, Inbum Jung
http://doi.org/10.5626/JOK.2019.46.1.97
With the growing importance of weather information, the number of weather information application systems has been increased. Unfortunately, the weather application systems that currently exist neither efficiently store nor manage the vast amount of weather data obtained from various weather sensors. Additionally, they do not utilize the properties contained in the weather data making it difficult to perform intelligent searches using the semantic information present in the weather data. In this paper as a solution to the challenges mentioned, an ontology system for weather information management is constructed using IoT middleware MinT. Based on weather ontology, it is possible to efficiently and easily manage large amounts of weather sensing data by applying ontology in the Internet of Things middleware. Moreover, since inference engine and rule-base information are used, semantic properties are applied to the sensing data collected. The implemented weather ontology uses sensing data and easily provides search results to users through a UI. The usability to search results is selected as the metric for performance evaluation. In the experiments, the proposed weather ontology system exhibited high usability to search results.
Web-based Integrated Management System Using oneM2M Platform in IoT Environment
Manseong Lee, Geonwoo Kim, Jiwoo Park, Kwangsue Chung
http://doi.org/10.5626/JOK.2018.45.10.1104
Today, the Internet of Things (IoT) is increasingly utilized to connect between devices as Machine to Machine (M2M) technology develops. A standardized communication protocol is required for device-to-device connections. The oneM2M standard is being used in IoT devices as a standardization method for stable communication between two devices. oneM2M controls resources by requesting resources through Create, Retrieve, Update, Delete, Notify (CRUDN) operations. Since the existing system checks the status information of the device through the application, a problem arises whereby the user has no accessibility and the real-time information cannot be served. The proposed system manages the IoT device as a oneM2M resource and advises the user to check the real-time resource information and log in the web environment.
SDN based Mobility Management in IoT Networks
BoYeong Mun, SungChol Cho, Shimin SUN, Jin Xinan Shu, Cheongbin Kim, JunHyuk Kim, Sunyoung Han
http://doi.org/10.5626/JOK.2018.45.7.733
IoT environments are constrained by various factors, including object address, battery, network bandwidth, and computing power. We propose a system to manage mobility by applying an SDN (Software Defined Networking) centralized management method to effectively solve the problems caused by moving IoT terminals. The SDN used in this paper is programmable, which facilitates its scalability as well as its ability to manage various IoT terminals. in this paper, we propose a mobility architecture using SDN for IoT, and design as well as implement a system based on it.
Smart Agent based Dynamic Data Aggregation for Delay Sensitive Smart City Services
Md. Shirajum Munir, Sarder Fakhrul Abedin, Md. Golam Rabiul Alam, Do Hyeon Kim, Choong Seon Hong
http://doi.org/10.5626/JOK.2018.45.4.395
Smart city is the vision of modern intelligent technology toward the sustainable development of green technology and social development. Smart services e.g. smart transportation, smart health, smart home, smart grid, smart security, and IoT based applications are the key enablers of smart city, that ensure the quality life and well-being. In a bid to ensure the functionalities of those services, the IoT applications gather data from numerous IoT nodes. In such a case, it becomes more challenging to managing huge network traffic in the centralized network of smart city. Therefore, in this research, we have focused on the resolution of this problem through the introduction of of smart agent-based dynamic data aggregation (DDA) from distributed dense smart city network for city service fulfillment. In this research study, we purposed to model a peer to peer fully distributed system using distributed hash table chord protocol. We also proposed an algorithm for the IoT network and designed smart agent based IoT node searching algorithm for crowd sourcing. Finally, we simulated the result of the proposed smart agent based dynamic data aggregation model in an effort to achieve a higher performance gain for the proposed approach in respect to service fulfillment time and convergence.
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