• The Transactions of the Korea Information Processing Society
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• v.5 no.10
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• pp.2521-2532
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• 1998

This paper proposes Heterogeneous Duplicatio Scheduling(HDS) which alleviates excessive communication overhead between tasks for distributed computing on a teerogeneous distributed environment. HDS is to allocate a copy of a task that causes excesive data communication with a message receiving task to the dame machine wherein the message receiving task is scheduled. The proposed algorithm allows only the duplication of parent tasks so as not to increase the complexity of the algorithm. Simulation on various type of task graphs provides that the scheduling results by using HDS are better than those by using the existing geterogencous cheduling schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4372-4388
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• 2014

Robotic sensor network (RSN) contains mobile sensors and robots providing feasible solution for many multi-agent applications. One of the most critical issues in RSN and its application is how to effectively assign tasks. This paper presents a novel connectivity preserving hybrid task allocation strategy to answer the question particularly for RSN. Firstly, we model the task allocation in RSN to distinguish the discovering and allocating processes. Secondly, a fully distributed simple Task-oriented Unoccupied Neighbor Algorithm, named TUNA, is developed to allocate tasks with only partial view of the network topology. A connectivity controller is finally developed and integrated into the strategy to guarantee the global connectivity of entire RSN, which is critical to most RSN applications. The correctness, efficiency and scalability of TUNA are proved with both theoretical analysis and experimental simulations. The evaluation results show that TUNA can effectively assign tasks to mobile robots with the requirements of only a few messages and small movements of mobile agents.

• The KIPS Transactions:PartA
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• v.11A no.3
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• pp.181-188
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• 2004

PDF(Parallel/Distributed Processing) is an internet-based parallel/distributed processing system that utilizes resources from hosts on the internet in idle state to perform large scale application through parallel processing, thus decreasing the total execution time. In this paper. do propose an adaptive method to be changed network environment at any time using realtime monitoring of host. It is found from experiments that parallel/distributed processing has better performance than its without monitoring as an adaptive strategy, which copy with task delay factor by overload and fault of network, be applicable to the cockpits of task allocation algorithm in PDP.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1464-1480
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• 1997

Distributed systems offer environments for attaining high performance, fault-tolerance, information sharing, resource sharing, etc. But we cannot benefit from these potential advantages without suitable management of events/states occurring in distributed systems. These events and states can be symptoms for performance degradation, erroneous functions, suspicious activities, etc. and are subject to further analysis. To properly manage events/states, we need to be able to specify and efficiently detect these events/states. In this paper we first describe an event/state specification language and a centralized algorithm for detecting events/states specified with this language. Then we describe an algorithm for distributing an event/state detection task in a distributed system which is hierarchically organized. The algorithm consists of decomposing an event/state detection task into subtasks and allocation these subtasks to the proper nodes. We also explain a method to make the distributed detection fault-tolerant.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2659-2669
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• 1999

This paper a heuristic, clustering based task allocation scheme applicable to non-directed task graph on a distributed system. This scheme firstly builds a task-machine graph, and then applies a clustering process where in a pair of tasks that are connected to the highest cost edge is merged into a big one or a task is allocated to a machine. During the process, the proposed scheme figure out a machine onto which the task allocation may cause deduction of large communication overhead that has incurred between the task and tasks that are already allocated to the machine while the computation costs is slightly increased in the machine. Simulation for the various task graphs shows that the scheduling using the proposed scheme result far better than ones by using the traditional schemes. A comparison with optimal task scheduling also promises that our scheme derives optimal results more occasionally than the traditional schemes do.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10c
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• pp.777-779
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• 1999

A new distributed/parallel algorithm simulator, DASim(Distributed Algorithm Simulator), is proposed in this paper. The idea is to ease the task of design, analysis and implementation of distributed algorithms. A small high level language has been proposed for the purpose. Through this non-language specific high level language, the users are spared from the tedious details about how to program distributed or parallel algorithms. Further, visualization of these algorithms are pretty helpful to understand behaviors of these algorithms.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.6
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• pp.9-19
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• 1993

This paper presents a new concept of a reconfigurable manipulator system which adjusts its mechanical structure to suit the kinematic characteristics of a given task. A highly redundant manipulator designed as a general purpose manipulator needs to be reconfigured for a specific task. A general task can be decomposed of motion and force components with different control requirements: either gross motion control or fine motion control. Each of these task components are distributed to each part of the manipulator based on the control requirements and the structure of the manipulator. Through the reconfiguration, a redundant manipulator is decomposed into two local arms, and the kinematic characteristics of each local arm is adjusted to suit the assigned task. The reconfigured redundant manipulator has two local arms well-configured for the local tasks and cooperating in serial for a given task. This globally enhances the performance of a redundant manipulator to execute a specific task. The simulation results are shown.

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1203-1211
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• 1999

Checkpointing is the one of fault-tolerant techniques to restore faults and to restart job fast. Checkpointing algorithms in distributed systems have been studied for many years. These algorithms can be classified into synchronous Checkpointing algorithms and asynchronous Checkpoiting algorithms. In this paper, we propose an independent Checkpointing algorithm that has a minimum Checkpointing counts equal to periodic Checkpointing algorithm, and relatively short rollback distance at faulty situation. Checkpointing count is directly related to task completion time in a fault-free situation and short rollback distance is directly related to task completion time in a faulty situation. The proposed algorithm is compared with the previously proposed asynchronous Checkpointing algorithms using simulation. In the simulation, the proposed Checkpointing algorithm produces better results than other algorithms in terms of task completion time in fault-free as well as faulty situations.

• Journal of Korea Multimedia Society
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• v.20 no.9
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• pp.1559-1566
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• 2017

Recently in the IoT(Internet of Things) environment, a data collection in real-time through device's sensor has increased with an emergence of various devices. Collected data from IoT environment shows a large scale, non-uniform generation cycle and atypical. For this reason, the distributed processing technique is required to analyze the IoT sensor data. However if you do not consider the optimal scheduling for data and the processor of IoT in a distributed processing environment complexity increase the amount in assigning a task, the user is difficult to guarantee the QoS(Quality of Service) for the sensor data. In this paper, we propose APQTA(Adaptive Priority Queue-driven Task Allocation method for sensor data processing) to efficiently process the sensor data generated by the IoT environment. APQTA is to separate the data into job and by applying the priority allocation scheduling based on the deadline to ensure that guarantee the QoS at the same time increasing the efficiency of the data processing.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.117.2-117
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• 2002

In this paper, a software framework is proposed for the personal robot located on home network. The proposed software framework is divided into four layers-a transparency layer, a behavior layer, a distributed task layer, and a mission scenario layer. The transparency layer consists of a virtual machine for platform transparency, and a communication broker for communication transparency among behavior modules. The communication architecture includes both server/client communication and publisher/subscriber communication. A mission scenario is assumed to be a composition of sequentially planned distributed tasks. In addition to the software framework, a new concept, personal robot design cent...