• Journal of Communications and Networks
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• v.18 no.2
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• pp.135-149
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• 2016

Cloud radio access network (C-RAN) refers to the virtualization of base station functionalities by means of cloud computing. This results in a novel cellular architecture in which low-cost wireless access points, known as radio units or remote radio heads, are centrally managed by a reconfigurable centralized "cloud", or central, unit. C-RAN allows operators to reduce the capital and operating expenses needed to deploy and maintain dense heterogeneous networks. This critical advantage, along with spectral efficiency, statistical multiplexing and load balancing gains, make C-RAN well positioned to be one of the key technologies in the development of 5G systems. In this paper, a succinct overview is presented regarding the state of the art on the research on C-RAN with emphasis on fronthaul compression, baseband processing, medium access control, resource allocation, system-level considerations and standardization efforts.

• IE interfaces
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• v.13 no.4
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• pp.572-583
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• 2000

In this research we have developed a prototype which manages a product structure and configuration of a product under distributed heterogeneous computing environments. First, the data schema for product structure and configuration which can represent options and effectivity is proposed. Second, a technique to use JAVA and CORBA is suggested for the exchange of product structure among multiple servers in CITIS environments. Functions of the prototype related to option-based product structure are described to help readers' understanding.

• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.9-16
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• 2021

Recently, the traffic volume of mobile communications increases rapidly and the small-cell is one of the solutions using two offload schemes, i.e., local IP access (LIPA) and selected IP traffic offload (SIPTO), to reduce the end-to-end delay and amount of mobile data traffic in the core network (CN). However, 3GPP describes the concept of LIPA and SIPTO and there is no decision algorithm to decide the path from source nodes (SNs) to destination nodes (DNs). Therefore, this paper proposes a dynamic mobile data traffic offload scheme using small-cells to decide the path based on the SN and DN, i.e., macro user equipment, small-cell user equipment (SUE), and multimedia server, and type of the mobile data traffic for the real-time and non-real-time. Through analytical models, it is shown that the proposed offload scheme outperforms the conventional small-cell network in terms of the delay of end-to-end mobile data communications and probability of the mobile data traffic in the CN for the heterogeneous networks.

• Electronics and Telecommunications Trends
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• v.36 no.2
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• pp.56-64
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• 2021

Many computer vision algorithms are computationally expensive and require a lot of computing resources. Recently, owing to machine learning technology and high-performance embedded systems, vision processing applications, such as object detection, face recognition, and visual inspection, are widely used. However, on-devices need to use their resources to handle powerful vision works with low power consumption in heterogeneous environments. Consequently, global manufacturers are trying to lock many developers into their ecosystem, providing integrated low-power chips and dedicated vision libraries. Khronos Group-an international standard organization-has released the OpenVX standard for high-performance/low-power vision processing in heterogeneous on-device systems. This paper describes vision libraries for the embedded systems and presents the OpenVX standard along with related trends for on-device vision system.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.2
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• pp.81-90
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• 2013

During the past decade, many changes and attempts have been tried and are continued developing new technologies in the computing area. The brick wall in computing area, especially power wall, changes computing paradigm from computing hardwares including processor and system architecture to programming environment and application usage. The high performance computing (HPC) area, especially, has been experienced catastrophic changes, and it is now considered as a key to the national competitiveness. In the late 2000's, many leading countries rushed to develop Exascale supercomputing systems, and as a results tens of PetaFLOPS system are prevalent now. In Korea, ICT is well developed and Korea is considered as a one of leading countries in the world, but not for supercomputing area. In this paper, we describe architecture design of MAHA supercomputing system which is aimed to develop 300 TeraFLOPS system for bio-informatics applications like human genome analysis and protein-protein docking. MAHA supercomputing system is consists of four major parts - computing hardware, file system, system software and bio-applications. MAHA supercomputing system is designed to utilize heterogeneous computing accelerators (co-processors like GPGPUs and MICs) to get more performance/$, performance/area, and performance/power. To provide high speed data movement and large capacity, MAHA file system is designed to have asymmetric cluster architecture, and consists of metadata server, data server, and client file system on top of SSD and MAID storage servers. MAHA system softwares are designed to provide user-friendliness and easy-to-use based on integrated system management component - like Bio Workflow management, Integrated Cluster management and Heterogeneous Resource management. MAHA supercomputing system was first installed in Dec., 2011. The theoretical performance of MAHA system was 50 TeraFLOPS and measured performance of 30.3 TeraFLOPS with 32 computing nodes. MAHA system will be upgraded to have 100 TeraFLOPS performance at Jan., 2013.

• The KIPS Transactions:PartA
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• v.14A no.2
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• pp.99-106
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• 2007

Grid computing, a mechanism which uses heterogeneous systems that are geographically distributed, draws attention as a new paradigm for the next generation operation of parallel and distributed computing. The importance of grid computing concerning communication cost is very huge because grid computing furnishes uses with integrated virtual computing service, in which a number of computer systems are connected by a high-speed network. Therefore, to reduce the execution time, the scheduling algorithm in grid environment should take communication cost into consideration as well as computing ability of resources. However, most scheduling algorithms have not only ignored the communication cost by assuming that all tasks were dealt in one cluster, but also did not consider the overhead of communication cost when the tasks were processed in a number of clusters. In this paper, the functions of original scheduling algorithms are analyzed. More importantly, the functions of algorithms are compared and analyzed with consideration of communication cost within the co allocation environment, in which a task is performed separately in many clusters.

• Journal of Advanced Navigation Technology
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• v.15 no.1
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• pp.124-129
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• 2011

In the process of cooperation which can be the best proposals for resolving complex problems in computing domain, the way of team organizing is one of the most important aspects for succeeding the goal. Especially in ubiquitous computing environment, where the participants of a team are selected from the heterogeneous computing objects which are deployed by other providers for their own goals, finding the relevant teammate can be regarded as the most important factor for determining the success or failure of the given problem. In this paper, we propose a method of finding teammate and assigning a role, which is a sub task of cooperation, by comparing the attributes of the computing object and the requirement of the role such as capability of functions, loyalty for the given team, and harmony with other teammates. By considering the situationally changing weights of each attributes, this method can be suited for dynamic computing environment where the cooperation should be executed with dynamically in/out computing objects and satisfy the dynamically chaining constraints.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.283-290
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• 2016

As the development of recent science and technology, high-performance computing resources is needed to solve complex problems. To reach these requirements, it has been actively studied about grid computing that consist of a huge system which bind a heterogeneous high performance computing resources into on which are geographically dispersed. However, The current research situation which are the process to obtain the best results in the limited resources and the scheduling policy to accurately predict the total execution time of the real-time task are very poor. In this paper, in order to overcome these problems, we suggested a grid computing-based risk management system which derived from the system structure and the process for improving the efficiency of the system, grid computing-based working methodology, risk policy module which can manage efficiently the problem of the work of resources(Agent), scheduling technique and allocation method which can re-allocate the resource allocation and the resources in problem, and monitoring which can manage resources(Agent).

• Journal of Service Research and Studies
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• v.2 no.2
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• pp.91-98
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• 2012

The emergence of new types of embedded computing devices and developments in wireless networking are broadening the domain of computing from the work place and home office to other facets of everyday life. This trend is expected to lead to a proliferation of Internet of Things (IoT) environments, in which inexpensive and interconnected computing devices are capable of supporting users in a range of tasks. Context-aware computing is a key source to develop such smart services. However, there are many challenges to enable services to be smart; Heterogeneous Computing Environments, Resource Limitations, Large Amount of Data Produced, and Different Requirements for Context Interpretation. Because of these challenges, there are difficulties in providing smart service by utilizing IoT devices. Currently, many researchers are conducting researches on mobile-computing based smart service development and provisioning and network infrastructure for interconnected IoT devices. Still, there are some limitations on developing core technologies for IoT computing based smart service development. In order to remedy this situation, this thesis presents a reusable framework that provides unique and noble features which are required in developing advanced context-aware IoT applications.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.116-126
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• 2015

In a distributed heterogeneous computing system, the performance of a parallel application greatly depends on its task scheduling algorithm. Therefore, in order to improve the performance, it is essential to consider some factors that can have effect on the performance of the parallel application in a given environment. One of the most important factors that affects the total execution time is a critical path. In this paper, we propose the CLTS algorithm for a task scheduling. The CLTS sets the priorities of all nodes to improve overall performance by applying leveling method to improve parallelism of task execution and by reducing the delay caused by waiting for execution of critical nodes in priority phase. After that, it conditionally uses insertion based policy or duplication based policy in processor allocation phase to reduce total schedule time. To evaluate the performance of the CLTS, we compared the CLTS with the DCPD and the HCPFD in our simulation. The results of the simulations show that the CLTS is better than the HCPFD by 7.29% and the DCPD by 8.93%. with respect to the average SLR, and also better than the HCPFD by 9.21% and the DCPD by 7.66% with respect to the average speedup.