• Journal of Communications and Networks
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• v.18 no.2
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• pp.150-161
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• 2016

Coordinated multi-point transmission (CoMP) techniques are being touted as enabling technologies for interference mitigation in next generation heterogeneous wireless networks (HetNets). In this paper, we present a comparative performance study of uplink (UL) CoMP algorithms for the 3GPP LTE HetNets. Focusing on a distributed and functionally-split architecture, we consider six distinct UL-CoMP algorithms: 1. Joint reception in the frequency-domain (JRFD) 2. Two-stage equalization (TSEQ) 3. Log-likelihood ratio exchange (LLR-E) 4. Symmetric TSEQ (S-TSEQ) 5. Transport block selection diversity (TBSD) 6. Coordinated scheduling with adaptive interference mitigation (CS-AIM) where JRFD, TSEQ, S-TSEQ, TBSD and CS-AIM are our main contributions in this paper, and quantify their relative performances via the post-processing signal-to-interference-plus-noise ratio distributions.We also compare the CoMP-specific front-haul rate requirements for all the schemes considered in this paper. Our results indicate that, with a linear minimum mean-square error receiver, the JRFD and TSEQ have identical performances, whereas S-TSEQ relaxes the front-haul latency requirements while approaching the performance of TSEQ. Furthermore, in a HetNet environment, we find that CS-AIM provides an attractive alternative to TBSD and LLR-E with a significantly reduced CoMP-specific front-haul rate requirement.

• ETRI Journal
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• v.40 no.6
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• pp.759-773
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• 2018

Uncore components such as on-chip memory systems and on-chip interconnects consume a large amount of energy in emerging embedded applications. Few studies have focused on next-generation analytical models for future chip-multiprocessors (CMPs) that simultaneously consider the impacts of the power consumption of core and uncore components. In this paper, we propose a convex-optimization approach to design heterogeneous uncore architectures for embedded CMPs. Our convex approach optimizes the number and placement of memory banks with different technologies on the memory layer. In parallel with hybrid memory architecting, optimizing the number and placement of through silicon vias as a viable solution in building three-dimensional (3D) CMPs is another important target of the proposed approach. Experimental results show that the proposed method outperforms 3D CMP designs with hybrid and traditional memory architectures in terms of both energy delay products (EDPs) and performance parameters. The proposed method improves the EDPs by an average of about 43% compared with SRAM design. In addition, it improves the throughput by about 7% compared with dynamic RAM (DRAM) design.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.4
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• pp.165-172
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• 2023

Heterogeneous computing is a technology that utilizes different types of processors to perform parallel processing. It maximizes task processing and energy efficiency by leveraging various computing resources such as CPUs, GPUs, and FPGAs. On the other hand, edge computing has developed with IoT and 5G technologies. It is a distributed computing that utilizes computing resources close to clients, thereby offloading the central server. It has evolved to intelligent edge computing combined with artificial intelligence. Intelligent edge computing enables total data processing, such as context awareness, prediction, control, and simple processing for the data collected on the edge. If heterogeneous computing can be successfully applied in the edge, it is expected to maximize job processing efficiency while minimizing dependence on the central server. In this paper, experiments were conducted to verify the feasibility of various parallel programming models on high-end and low-end edge devices by using benchmark applications. We analyzed the performance of five parallel programming models on the Raspberry Pi 4 and Jetson Orin Nano as low-end and high-end devices, respectively. In the experiment, OpenACC showed the best performance on the low-end edge device and OpenSYCL on the high-end device due to the stability and optimization of system libraries.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.782-787
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• 2004

Recently, many enterprises are introducing EAI(Enterprise Application Integration) technologies for integrating heterogeneous enterprise information systems. Among EAI levels, data-level integration is relatively straightforward and most popular. However, current commercial solutions have complex functionalities and are expensive for implementing the data integration tasks. Also, they have their own proprietary architectures and have a restricted interoperability. Proposed in this paper is the development of data integration middleware for facilitating data exchanges between the heterogeneous information systems. The main feature of this middleware is a explicit mapping of meta data about the relationships between source and target data. Based on this mapping, users who do not have expertise in information technology at the small & medium enterprise can easily handle data exchange tasks between information systems.

• IE interfaces
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• v.17 no.4
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• pp.407-413
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• 2004

Recently, many enterprises are adopting EAI (Enterprise Application Integration) technologies for integrating heterogeneous enterprise information systems. Among EAI levels, data-level integration is relatively straightforward and most popular. However, most commercial solutions provide complex functionalities and are expensive for implementing the data integration tasks at the small & medium enterprises. Also, they have their own proprietary architectures and have a restricted interoperability. Proposed in this paper is the development of a data integration middleware for facilitating data exchanges between the heterogeneous information systems. The main feature of this middleware is a explicit mapping of meta data about the relationships between source and target data. Based on this explicit mapping, users who do not have expertise in information technology at the small & medium enterprises can easily execute data exchange tasks among various information systems.

• Journal of Information Science Theory and Practice
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• v.6 no.3
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• pp.6-15
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• 2018

With the increasing demand for intelligent services, knowledge graph technologies have attracted much attention. Various application-specific knowledge bases have been developed in industry and academia. In particular, open knowledge bases play an important role for constructing a new knowledge base by serving as a reference data source. However, identifying the same entities among heterogeneous knowledge sources is not trivial. This study focuses on extracting and determining exact and precise entities, which is essential for merging and fusing various knowledge sources. To achieve this, several algorithms for extracting the same entities are proposed and then their performance is evaluated using real-world knowledge sources.

• 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.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.295-303
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• 2005

Semantic Web and its related technologies have been opening the era of information sharing via Web. In the meantime, there are several huddles to overcome toward the new era and one of the major huddles is information integration issue unless we build and use a single unified but huge ontology which address everything in the world. Particularly in e-business area, information integration problem must be a great concern in search and comparison of products from various internet shopping sites and e-marketplaces. To overcome such an information integration problem, we propose an ontology driven mapping algorithm between heterogeneous product classification and description frameworks. We also perform comparative evaluation of the proposed mapping algorithm against a well-known ontology mapping tool, PROMPT.

• Journal of Information Technology Services
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• v.7 no.4
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• pp.87-99
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• 2008

As the technologies for telecommunication have been evolving, more enhanced information services and integrated information systems have been introduced, which can manage a variety of information from the heterogeneous systems. The major obstacle for the integrated information systems is the integrating heterogeneous databases in the systems and the heterogeneity problems can be classified into the structural and data heterogeneities. However, the previous researches have mainly highlighted into the solving structural heterogeneity problems. This paper identifies the data heterogeneity problems for multi-database schema integrations and proposes a new solving method. We analyze the semantics equivalence in data values based on the functional dependency, primary and candidate keys, and present a procedural solution of data heterogeneity in the perspective of the concept of attribute equivalence, integration key and conceptual integration table.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.765-784
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• 2019

The smart city is one of the most promising, prominent, and challenging applications of the Internet of Things (IoT). Smart cities rely on everything connected to each other. This in turn depends heavily on technology. Technology literacy is essential to transform a city into a smart, connected, sustainable, and resilient city where information is not only available but can also be found. The smart city vision combines emerging technologies such as edge computing, blockchain, artificial intelligence, etc. to create a sustainable ecosystem by dramatically reducing latency, bandwidth usage, and power consumption of smart devices running various applications. In this research, we present a comprehensive survey of emerging technologies for a sustainable smart city network. We discuss the requirements and challenges for a sustainable network and the role of heterogeneous integrated technologies in providing smart city solutions. We also discuss different network architectures from a security perspective to create an ecosystem. Finally, we discuss the open issues and challenges of the smart city network and provide suitable recommendations to resolve them.