• KIISE Transactions on Computing Practices
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• v.23 no.9
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• pp.517-534
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• 2017

This paper proposes an Internet of Things (IoT) middleware called Middleware for Cooperative Interaction of Things (MinT). MinT supports a fully distributed IoT environment in which IoT devices directly connect to peripheral devices, easily constructing a local or global network and sharing their data in an energy efficient manner. MinT provides a sensor abstract layer, a system layer and an interaction layer. These layers enable integrated sensing device operations, efficient resource management, and interconnection between peripheral IoT devices. In addition, MinT provides a high-level API, allowing easy development of IoT devices by developers. We aim to enhance the energy efficiency and performance of IoT devices through the performance improvements offered by MinT resource management and request processing. The experimental results show that the average request rate increased by 25% compared to existing middlewares, average response times decreased by 90% when resource management was used, and power consumption decreased by up to 68%. Finally, the proposed platform can reduce the latency and power consumption of IoT devices.

• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.481-488
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• 2009

GIS is used to isolate large power electrical equipment using SF6 gas. While GIS has simple structure, it has few break down, relatively high reliability. But it is hard to check up faults for reason of pressure. Faults of GIS should have a ripple effect on community and be hard to recovery. Consequently, GIS imports a preventive diagnostic system to find internal faults in advance. It is most important that reliability on the GIS preventive diagnostic system, because it estimates abnormality of system by analysis result of collected data. But, exist system which used central data management is low efficiency, and hard to guarantee timeliness and accuracy of data. To guarantee timeliness and accuracy, the GIS preventive diagnostic system needs accordingly to use a real-time middleware. So, in this paper, to improve reliability of the GIS preventive diagnostic system, we use a middleware based on TMO for guaranteeing timeliness of real-time distributed computing. And we propose an improved GIS preventive diagnostic system applying data acquisition, monitoring and control methods based on the TMO model. The presented system uses the Communication Control Unit(CCU) for distributed data handling which is supported by TMO. CCU can improve performance of the GIS preventive diagnostic system by guaranteeing timeliness of data handling process and increasing reliability of data through the TMO middleware. And, it has designed to take full charge of overload on a data acquisition task had been processed in an exist server. So, it could reduce overload of the server and apply distribution environment from now. Therefore, the proposed system can improve performance and reliability of the GIS preventive diagnostic system and contribute to stable operation of GIS.

• Journal of Korea Spatial Information System Society
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• v.8 no.2 s.17
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• pp.91-107
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• 2006

To handling the extreme situation that must manage positional information of a very large volume, at least millions of moving objects. A cluster-based sealable distributed computing system architecture, called the GALIS which consists of multiple data processors, each dedicated to keeping records relevant to a different geographical zone and a different time zone, was proposed. In this paper, we proposed a valid time management and time-zone shifting scheme, which are essential in realizing the long-term location data subsystem of GALIS, but missed in our previous prototype development. We explain how to manage valid time of moving objects to avoid ambiguity of location information. We also describe time-zone shifting algorithm with three variations, such as Real Time-Time Zone Shifting, Batch-Time Zone Shifting, Table Partitioned Batch-Time Zone Shifting, Through experiments related with query processing time and CPU utilization, we show the efficiency of the proposed time-zone shifting schemes.

• The KIPS Transactions:PartC
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• v.11C no.7 s.96
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• pp.1033-1042
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• 2004

According to the arbitration mechanism among the peers in the network, the P2P networking environments can be classified into hybrid P2P networking environments and pure P2P networking environments. In hybrid P2P networking environments, each peer gets continual services from the servers that arc operational most of the time, and so, network isolation does not occur because every peer can always keep connection to the server. In pure P2P networking environments, however, every peer directly connects to another peer without server intervention, and so, network isolation can occur when the per mediating the connection is terminated. In this paper, we propose a scheme for each peer to keep connection information of other peers by maintaining IDs of its neighbor peers, to reconnect to another peers when the mediating peer fails to work. and, for efficiency. to balance the number of connections that should be maintained by each peer. With our mechanism, each pier in the network can continuously maintain connection to the network and get seamless services from other peers. Through the simulation, we ascer-tained that network isolation does not occur in the pure P2P network adopting our mechanism and that our mechanism distributes and balances the connections that are maintained by each peer. We also analyzed the total network traffic and the mean number of hops for the connections made by each peer according to the recommended number of connections that is established at system setup time.

• Journal of KIISE
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• v.43 no.10
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• pp.1115-1123
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• 2016

Assumption-based truth maintenance system (ATMS) is a tool that maintains the reasoning process of inference engine. It also supports non-monotonic reasoning based on dependency-directed backtracking. Bookkeeping all the reasoning processes allows it to quickly check and retract beliefs and efficiently provide solutions for problems with large search space. However, the amount of data has been exponentially grown recently, making it impossible to use a single machine for solving large-scale problems. The maintaining process for solving such problems can lead to high computation cost due to large memory overhead. To overcome this drawback, this paper presents an approach towards incrementally maintaining the reasoning process of inference engine on cluster using Spark. It maintains data dependencies such as assumption, label, environment and justification on a cluster of machines in parallel and efficiently updates changes in a large amount of inferred datasets. We deployed the proposed ATMS on a cluster with 5 machines, conducted OWL/RDFS reasoning over University benchmark data (LUBM) and evaluated our system in terms of its performance and functionalities such as assertion, explanation and retraction. In our experiments, the proposed system performed the operations in a reasonably short period of time for over 80GB inferred LUBM2000 dataset.

• Journal of Korea Spatial Information System Society
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• v.8 no.1 s.16
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• pp.93-106
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• 2006

A Grid Database is a database management system to process effectively and use the distributed data in a grid computing environment. Spatial data is more important than other general data according to the local characteristics and requires a large storage. The grid database can be used as the optimal system for the management of the spatial data. However, contrary to the conventional distributed database systems, the Grid Database which guarantees the local autonomy has a possibility not to provide an effective system, or it is impossible to use a centralized management environment. In order to allow flexible responses to a dynamically changing environment, it is required to use effectively reorganized method. In this paper, hierarchical reorganization method is presented for dynamic reorganization in a grid database. When the reorganization is conducted, an organizer is created to collect the information of databases. In addition, the organizer which is constructed by the hierarchical structure supports information communication and reorganization, and then it allows the support of regional reorganization operation and effective balance control. The performance assessment of the proposed method shows that the processing capacity is increased after the reorganization.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.67-76
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• 2018

This paper addresses the problem of efficient processing of region monitoring queries. The centralized methods used for existing region monitoring query processing assumes that the mobile object periodically sends location-updates to the server and the server continues to update the query results. However, a large amount of location updates seriously degrade the system performance. Recently, some distributed methods have been proposed for region monitoring query processing. In the distributed methods, the server allocates to all objects i) a resident domain that is a subspace of the workspace, and ii) a number of nearby query regions. All moving objects send location updates to the server only when they leave the resident domain or cross the boundary of the query region. In order to allocate the resident domain to the moving object along with the nearby query region, we use a query index structure that is constructed by splitting the workspace recursively into equal halves. However, However, the above index structure causes unnecessary division, resulting in deterioration of system performance. In this paper, we propose an adaptive split method to reduce unnecessary splitting. The workspace splitting is dynamically allocated i) considering the spatial relationship between the query region and the resultant subspace, and ii) the distribution of the query region. We proposed an enhanced QR-tree with a new splitting method. Through a set of simulations, we verify the efficiency of the proposed split methods.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.11-20
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• 2019

Numerous enterprises, organizations and individual users are exposed to large DDoS (Distributed Denial of Service) attacks. DDoS attacks are performed through a BotNet, which is composed of a number of computers infected with a malware, e.g., zombie PCs and a special computer that controls the zombie PCs within a hierarchical chain of a command system. In order to detect a malware, a malware detection software or a vaccine program must identify the malware signature through an in-depth analysis, and these signatures need to be updated in priori. This is time consuming and costly. In this paper, we propose a botnet detection scheme that does not require a periodic signature update using an artificial neural network model. The proposed scheme exploits Word2Vec and accelerated hierarchical density-based clustering. Botnet detection performance of the proposed method was evaluated using the CTU-13 dataset. The experimental result shows that the detection rate is 99.9%, which outperforms the conventional method.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.1
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• pp.66-77
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• 2006

In this paper, we researched the searching and tracking locations of a home resident using ON/OFF switches and sensors and designed a remote monitoring system. As an implementation environment, this system is developed on the base of the distributed object group framework we have developed from previous works. In order to trace the moving locations of a home resident, we firstly showed a home structure which attaches ON/OFF switches and sensors to home appliances and indoor facilities being fixed in home. Whenever a home resident opens/closes these objects, the signals operated from ON/OFF switches and sensors are sent to a home server system. In this time, the real locations of ON/OFF switches and sensors that the signals are being occurred must be the current location that he/she stays. A home server system provides the functionalities that map the real location of a resident in home to virtual location designed on remote desk-tops or terminals like PDAs, and that construct a healthcare database consisted of moving patterns, moving ranges, momentum for analyzing the given searching locations and times Finally, this system provides these information for remotely monitoring services.

• The KIPS Transactions:PartA
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• v.10A no.2
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• pp.93-100
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• 2003

With the advent of distributed computing and Web service technologies, lots of users have been requiring services that can conveniently obtain and/or support well-assembled information based on Web. For this reason, we are to construct Automatic Linking Support Systems for generating Web-based integrated information and supporting retrieval information according to user's various requirements. Our system organization is based on client/server system. A server environment consisted of automatic linking engine that can provide lexical analyzing, query processing and integrated document generating functions, and databases that are made of dictionaries, image and URL contents. Also, client environments consisted of Web editor that can generate integrated documents and Web helper that can retrieve them via automatic linking engine and databases. For client's user-friendly interfaces, web editor and helper programs can directly execute by down leading from a server without setup them before inside clients. For reducing server's overheads, Parts of server's executing modules are distributed to clients on which they can be executing. As an implementation of our system, we use the JDK 1.3, SWING for user interfaces like Web editor and helper, RMI mechanism for interaction between clients and a server, and SQL server 7.0 for database development, respectively. Finally, we showed the access procedures of automatic document linking engine and databases from Web editor or Web helper, and results appearing on their screens.