• Journal of Internet Computing and Services
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• v.25 no.3
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• pp.1-8
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• 2024

As the Internet of Things (IoT) has gained significant prominence in our daily lives, most IoT devices rely on over-the-air technology to automatically update firmware or software remotely via the network connection to relieve the burden of manual updates by users. And preserving security for OTA interface is one of the main requirements to defend against potential threats. This paper presents a simulation of an attack scenario on the commoditized System-on-a-chip, ESP32 chip, utilized for drones during their OTA update process. We demonstrate three types of attacks, WiFi cracking, ARP spoofing, and TCP SYN flooding techniques and postpone the OTA update procedure on an ESP32 Drone. As in this scenario, unpatched IoT devices can be vulnerable to a variety of potential threats. Additionally, we review the chip to obtain traces of attacks from a forensics perspective and acquire memory forensic artifacts to indicate the SYN flooding attack.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.77-84
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• 2023

The utilization of GPUs on general-purpose computers is currently on the rise due to the increase in its programmability and performance requirements. The utility of tools like NVIDIA's CUDA have been designed to allow programmers to code algorithms by using C-like language for the execution process on the graphics processing units GPU. Unfortunately, many of the performance and correctness bugs will happen on parallel programs. The CUDA tool support for the parallel programs has not yet been actualized. The use of a dynamic analyzer to find performance and correctness bugs in CUDA programs facilitates the execution of sophisticated processes, especially in modern computing requirements. Any race conditions bug it will impact of program correctness and the share memory bank conflicts to improve the overall performance. The technique instruments the programs in a way that promotes accessibility of the memory locations accessed by different threads well as to check for any bugs in the code of a program. The instrumented source code will be used initiated directly in the device emulation code of CUDA to send report for the user about all errors. The current degree of automation helps programmers solve subtle bugs in highly complex programs or programs that cannot be analyzed manually.

• Journal of the HCI Society of Korea
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• v.1 no.1
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• pp.89-95
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• 2006

Prospective memory is memory for activities to be performed in the future, such as remembering to purchase a piece of fruit on the way home or remembering to give someone a telephone message. Due to the decrease in memory ability, the aged have difficulty in remembering the tasks they intended to perform in the future. Employing survey and experimental methods, we identified the UI requirements for enhancing prospective memory (PM) performance for the aged. The survey included subjective assessments of PM performance for the aged and their preferred usability components and PM-supporting systems in an ubiquitous computing environment. The experiment examined the effect of contextual cues on PM performance for the young and the aged. Practical implications of our results were discussed in the respects of PM-supporting UI design requirements for the aged.

• KIISE Transactions on Computing Practices
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• v.23 no.8
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• pp.466-472
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• 2017

Hardware Transactional Memory (HTM) has greatly changed the parallel programming paradigm for transaction processing. Since Intel has recently proposed Transactional Synchronization Extension (TSX), a number of studies based on HTM have been conducted. However, the existing studies support conflict prediction for a single cause of the transaction processing and provide a standardized TSX environment for all workloads. To solve the problems, we propose an efficient hardware transactional memory scheme for processing transactions in multi-core in-memory environment. First, the proposed scheme determines whether to use Software Transactional Memory (STM) or the serial execution as a fallback path of HTM by using a prediction matrix to collect the information of previously executed transactions. Second, the proposed scheme performs efficient transaction processing according to the characteristic of a given workload by providing a retry policy based on machine learning algorithms. Finally, through the experimental performance evaluation using Stanford transactional applications for multi-processing (STAMP), the proposed scheme shows 10~20% better performance than the existing schemes.

• The KIPS Transactions:PartD
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• v.14D no.7
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• pp.719-726
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• 2007

Recently, NAND flash memory has been used for a storage device in various mobile computing devices such as MP3 players, mobile phones and laptops because of its shock-resistant, low-power consumption, and none-volatile properties. However, due to the very distinct characteristics of flash memory, disk based systems and applications may result in severe performance degradation when directly adopting them on flash memory storage systems. Especially, when a B-tree is constructed, intensive overwrite operations may be caused by record inserting, deleting, and its reorganizing, This could result in severe performance degradation on NAND flash memory. In this paper, we propose an efficient buffer management scheme, called IBSF, which eliminates redundant index units in the index buffer and then delays the time that the index buffer is filled up. Consequently, IBSF significantly reduces the number of write operations to a flash memory when constructing a B-tree. We also show that IBSF yields a better performance on a flash memory by comparing it to the related technique called BFTL through various experiments.

• Journal of KIISE
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• v.42 no.4
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• pp.427-433
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• 2015

The rapid advancement of computing technology has triggered the need for fast data I/O processing and high-performance storage technology. Next generation memory technology, which we refer to as new memory, is anticipated to be used for high-performance storage as they have excellent characteristics as a storage device with non-volatility and latency close to DRAM. This research proposes NTL (New memory Translation layer) as a technology to make use of new memory as storage. With the addition of NTL, conventional I/O is served with existing mature disk-based file systems providing compatibility, while new memory I/O is serviced through the NTL to take advantage of the byte-addressability feature of new memory. In this paper, we describe the design of NTL and provide experiment measurement results that show that our design will bring performance benefits.

• Journal of Platform Technology
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• v.11 no.4
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• pp.71-79
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• 2023

In this paper, we analyze the characteristics of machine learning workloads and, based on them, propose a distributed in-memory caching technique to improve the performance of machine learning workloads. The core of machine learning workload is model training, and model training is a computationally intensive task. Performing machine learning workloads in a Kubernetes-based cloud environment in which the computing framework and storage are separated can effectively allocate resources, but delays can occur because IO must be performed through network communication. In this paper, we propose a distributed in-memory caching technique to improve the performance of machine learning workloads performed in such an environment. In particular, we propose a new method of precaching data required for machine learning workloads into the distributed in-memory cache by considering Kubflow pipelines, a Kubernetes-based machine learning pipeline management tool.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.2
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• pp.103-111
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• 2019

The IoT-driven large-scaled systems consist of connected things with on-chip executable embedded software. These light-weighted embedded things have limited hardware space, especially small size of on-chip flash memory. In addition, on-chip embedded software in flash memory is not easy to update in runtime to equip with latest services in IoT-driven applications. It is becoming important to develop light-weighted IoT devices with various software in the limited on-chip flash memory. The remote instruction execution in cloud via IoT connectivity enables to provide high performance software execution with unlimited software instruction in cloud and low-power streaming of instruction execution in IoT edge devices. In this paper, we propose a Cloud-IoT asymmetric structure for providing high performance instruction execution in cloud, still low power code executable thing in light-weighted IoT edge environment using remote instruction execution. We propose a simulated approach to determine efficient partitioning of software runtime in cloud and IoT edge. We evaluated the instruction cloudification using remote instruction by determining the execution time by the proposed structure. The cloud-connected instruction set simulator is newly introduced to emulate the behavior of the processor. Experimental results of the cloud-IoT connected software execution using remote instruction showed the feasibility of cloudification of on-chip code flash memory. The simulation environment for cloud-connected code execution successfully emulates architectural operations of on-chip flash memory in cloud so that the various software services in IoT can be accelerated and performed in low-power by cloudification of remote instruction execution. The execution time of the program is reduced by 50% and the memory space is reduced by 24% when the cloud-connected code execution is used.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.958-962
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• 2009

Flash memory, which replaces hard disk recently, has different physical characteristics with hard disk. For the performance of flash memory based storage system, many researches over OS and file system layers has been doing. In this paper, we propose the architecture of flash memory based storage which uses information of page invalidation when file deletion occurs from upper layer. Also, we evaluate the performance of proposed system. Proposed system effectively increases IO performance by using page invalidation information to block merge and wear leveling algorithms.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.9
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• pp.461-468
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• 2001

Though shared virtual memory (SVM) system promise low cost solutions for high performance computing they suffer from long memory latencies. These latencies are usually caused by repetitive invalidations on shared data. Since shared data are accessed through synchronization and the patterns by which threads synchronizes are repetitive, a prefetching scheme bases on such repetitiveness would reduce memory latencies. Based on this observation, we propose a prefetching technique which predicts future access behavior by analyzing access history per synchronization variable. Our technique was evaluated on an 8-node SVM system using the SPLASH-2 benchmark. The results show the our technique could achieve 34%~45% reduction in memory access latencies.