• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.387-390
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• 2017

With the advent of high-resolution sensors in the embedded field, the demand for heterogeneous computing continues to increase. Logic Module is an embedded system for controlling LADAR system components and for real-time 3D imaging of laser radar image data. In this paper, we discuss the design of Logic Module and the signal processing using CPU-GPU heterogeneous computing.

• Journal of Information Processing Systems
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• v.19 no.2
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• pp.240-257
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• 2023

The industrial Internet of Things (IIoT) is characterized by intelligent connection, real-time data processing, collaborative monitoring, and automatic information processing. The heterogeneous IIoT devices require a high data rate, high reliability, high coverage, and low delay, thus posing a significant challenge to information security. High-performance edge and cloud servers are a good backup solution for IIoT devices with limited capabilities. However, privacy leakage and network attack cases may occur in heterogeneous IIoT environments. Cloud-based multi-party computing is a reliable privacy-protecting technology that encourages multiparty participation in joint computing without privacy disclosure. However, the default cloud selection method does not meet the heterogeneous IIoT requirements. The server can be dishonest, significantly increasing the probability of multi-party computation failure or inefficiency. This paper proposes a blockchain and smart contract-based optimized cloud node selection framework. Different participants choose the best server that meets their performance demands, considering the communication delay. Smart contracts provide a progressive request mechanism to increase participation. The simulation results show that our framework improves overall multi-party computing efficiency by up to 44.73%.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.4
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• pp.289-293
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• 2016

As more mobile devices are equipped with multi-core CPUs and are required to execute many compute-intensive multimedia applications, it is important to optimize the systems, considering the underlying parallel hardware architecture. In this paper, we implement and optimize ray-tracing application tailored to a given mobile computing platform with multiple heterogeneous processing elements. In this paper, a lightweight ray-tracing application is specified and implemented in Kahn process network (KPN) model-of-computation, which is known to be suitable for the description of real-time applications. We take an open-source C/C++ implementation of ray-tracing and adapt it to KPN description in the Distributed Application Layer framework. Then, several possible configurations are evaluated in the target mobile computing platform (Exynos 5422), where eight heterogeneous ARM cores are integrated. We derive the optimal degree of parallelism and a suitable distribution of the replicated tasks tailored to the target architecture.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.86-95
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• 2009

Efficient DAG scheduling is critical for achieving high performance in heterogeneous computing environments. Finding an optimal solution to the problem of scheduling an application modeled by a directed acyclic graph(DAG) onto a set of heterogeneous machines is known to be an NP-complete problem. In this paper we propose a new list scheduling algorithm, called the Heterogeneous Rank-Path Scheduling(HRPS) algorithm, to exploit all of a program's available parallelism in distributed heterogeneous computing system. The primary goal of HRPS is to minimize the schedule length of applications. The performance of the algorithm has been observed by its application to some practical DAGs, and by comparing it with other existing scheduling algorithm such as CPOP, HCPT and FLB in term of the schedule length. The comparison studies show that HRPS significantly outperform CPOP, HCPT and FLB in schedule length.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.3
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• pp.163-171
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• 2013

Recently, the requirement of processing High Definition (HD) video or 3D application on low, mobile devices has been expanded and content data has been increased as well. It is becoming a major issue in Cloud computing where a Virtual Desktop Infrastructure (VDI) Service needs efficient data processing ability to provide Quality of Experience (QoE) in Cloud computing. In this paper, we propose three kind of Thick-Thin VDI Service which can share and delegate VDI service based on Thick Client using CPU and GPU. Furthermore, we propose and discuss the VDI Service Optimization Method in mixed CPU and GPU Heterogeneous Environment using CPU Parallel Processing OpenMP and GPU Parallel Processing CUDA.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4742-4770
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• 2019

Cloud computing provides a broad range of services like operating systems, hardware, software and resources. Availability of these services encourages data owners to outsource their intensive computations and massive data to the cloud. However, considering the untrusted nature of cloud server, it is essential to encrypt the data before outsourcing it to the cloud. Unfortunately, this leads to a challenge when it comes to providing search functionality for encrypted data located in the cloud. To address this challenge, this paper presents a public key encryption with equality test for heterogeneous systems (PKE-ET-HS). The PKE-ET-HS scheme simulates certificateless public encryption with equality test (CLE-ET) with the identity-based encryption with equality test (IBE-ET). This scheme provides the authorized cloud server the right to actuate the equivalence of two messages having their encryptions performed under heterogeneous systems. Basing on the random oracle model, we construct the security of our proposed scheme under the bilinear Diffie-Hellman (BDH) assumption. Eventually, we evaluate the size of storage, computation complexities, and properties with other related works and illustrations indicate good performance from our scheme.

• Smart Media Journal
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• v.11 no.3
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• pp.18-25
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• 2022

Neuromorphic computing generally shows significantly better power, area, and speed performance than neural network computation using CPU and GPU. These characteristics are suitable for resource-constrained IoT environments where energy consumption is important. However, there is a problem in that it is necessary to modify the source code for environment setting and application operation according to heterogeneous IoT devices that support neuromorphic computing. To solve these problems, NAAL was proposed and implemented in this paper. NAAL provides functions necessary for IoT device control and neuromorphic architecture abstraction and inference model operation in various heterogeneous IoT device environments based on common APIs of NAAL. NAAL has the advantage of enabling additional support for new heterogeneous IoT devices and neuromorphic architectures and computing devices in the future.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.6
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• pp.315-321
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• 2014

Mobile computing devices such as smartphones, tablet computers have become the dominant personal computing platforms. Energy efficiency is a prime design requirement for smart devices. In order to reduce the energy consumption of the smart devices, analysis of performance and energy consumption has become important. However, so far, there is no framework for the analysis and systematic approach to improve the power consumption of the heterogeneous multi-core system. In this paper, we describe a new framework for the analysis of heterogeneous multi-core systems. Also, by use of an analysis tool, can be provide reliability and productivity of development results.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.78-86
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• 2017

In this paper, we propose an energy-efficient scheduling scheme for real-time periodic tasks on a heterogeneous Grid computing system. The Grid system consists of heterogeneous processors providing the DVFS mechanism with a finite set of discrete clock frequencies. In order to save energy consumption, the proposed scheduling scheme assigns each real-time task to a processor with the least energy increment. Also the scheme activates a part of all available processors with unused processors powered off. Evaluation shows that the proposed scheme saves up to 70% energy consumption of the previous method.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.2845-2862
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• 1999

As the technical advances in portable computers and wireless communication technologies, mobile computing environment has been rapidly expanded. The mobile users on mobile host can access information via wireless communication from the distributed heterogeneous multidatabase system in which pre-existing independent local information systems are integrated into one logical system to support mobile applications. Hence, mobile transaction model should include not only the features for heterogeneous multidatabase systems but also the ones for mobile computing environment. In this paper, we proposed a mobile flex transaction model which extends the flexible transaction model that previously proposed for heterogeneous multidatabase systems is extended to support the requirements of mobile heterogeneous multidatabase systems. We also presented the execution control mechanism of the mobile flex transaction model. The proposed mobile flex transaction model allows the definition of location-dependent subtransactions, the effective support of hand-over, and the flexibility of transaction executions. Hence, the proposed mobile flex transaction model can be suit to mobile heterogeneous multidatabase systems that have low power capability, low bandwidth, and high communication failure possibility.