• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.723-724
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• 2017

Recently, researches are being conducted to build a smart environment using various sensors and devices and to provide customized services to users through inter object communication. However, the existing system utilizes a centralized method of transmitting measured sensor data in real time to the server and processing it in batches and As the system is expanded, there is a problem that a high-end server must be configured. In this paper, we design a Resource Allocation Algorithm for IoT distributed processing environment to solve these problems. The resources required for the device to operate are transferred to the server and the server allocates resources in comparison to the task in progress. Therefore, it is expected that the data throughput of the server will be reduced and various devices can be configured in a server having a low specification.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.3
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• pp.264-276
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• 2000

Recent advances of technologies make easy sharing various information and utilizing system resources on the Internet. Especially, code migration using applets of Java supports the distribution of programs on the web environment, and also browsers executing the applets guarantee the reliability of a migrated codes. In this paper, we describe the design and implementation of a web-based parallel processing system, which distributes migratable codes of a large job, makes the distributed codes to execute in parallel, and controls and gathers the results of each execution. The hosts participate in the computation reside on the Internet, spreaded out geographically, and the heterogeneity and the variability among them are severe. Thus, task allocation considering the performance differences and the adaptability to the severe variability are necessary. We present an adaptive task allocation algorithm applied to our system and the performance evaluation.

• Journal of Aerospace System Engineering
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• v.18 no.2
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• pp.56-63
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• 2024

As the safety of unmanned vehicles continues to improve, their usage in urban environments, which are full of obstacles such as buildings, is expected to increase. When numerous unmanned vehicles are operated in such environments, an algorithm that takes into account mutual collision avoidance, as well as static and dynamic obstacle avoidance, is necessary. In this paper, we propose an algorithm that handles task assignment and path planning. To efficiently plan paths, we construct a grid-based map and derive the paths from it. To enable quick re-planning in dynamic environments, we focus on reducing computational time. Through simulation, we explain obstacle avoidance and mutual collision avoidance in small-scale problems and confirm their performance by observing the entire mission completion time (Makespan) in large-scale problems.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.615-629
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• 2021

With the development of mobile edge computing, how to utilize the computing power of edge computing to effectively and efficiently offload data and to compute offloading is of great research value. This paper studies the computation offloading problem of multi-user and multi-server in mobile edge computing. Firstly, in order to minimize system energy consumption, the problem is modeled by considering the joint optimization of the offloading strategy and the wireless and computing resource allocation in a multi-user and multi-server scenario. Additionally, this paper explores the computation offloading scheme to optimize the overall cost. As the centralized optimization method is an NP problem, the game method is used to achieve effective computation offloading in a distributed manner. The decision problem of distributed computation offloading between the mobile equipment is modeled as a multi-user computation offloading game. There is a Nash equilibrium in this game, and it can be achieved by a limited number of iterations. Then, we propose a distributed computation offloading algorithm, which first calculates offloading weights, and then distributedly iterates by the time slot to update the computation offloading decision. Finally, the algorithm is verified by simulation experiments. Simulation results show that our proposed algorithm can achieve the balance by a limited number of iterations. At the same time, the algorithm outperforms several other advanced computation offloading algorithms in terms of the number of users and overall overheads for beneficial decision-making.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.347-352
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• 2004

This thesis deals with a task scheduling on a message-passing system. Scheduling and allocation are very important issues since the inappropriate scheduling of tasks cannot exploit the true potential of the system and it can offset the grain from parallelization. It is difficult to apply previous schemes to message-passing system, because previous schemes assume the shared memory system. This thesis proposes an modified priority function and processor selection technique that consider the problems caused by the difference between previous models and message-passing environments. The priority function includes the cumulative communication cost which causes task execution to be delayed. The processor selection technique avoids the situation that a child task is assigned to the same Processor allocated to its parent task that has other unscheduled child tasks. We showed by some simulations that our modified features of task scheduling algorithm can make the better scheduling results than the previous algorithms.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.3
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• pp.120-132
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• 2008

Networks-on-Chip (NoC) is emerging as a practical development platform for future systems-on-chip products. We propose an energy-efficient static algorithm which optimizes the energy consumption of task communications in NoCs with voltage scalable links. In order to find optimal link speeds, the proposed algorithm (based on a genetic formulation) globally explores the design space of NoC-based systems, including network topology, task assignment, tile mapping, routing path allocation, task scheduling and link speed assignment. Experimental results show that the proposed design technique can reduce energy consumption by 28% on average compared with existing techniques.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.304-310
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• 2021

The paper presents problems of optimization of the synthesis of embedded systems, in particular Pareto optimization. The model of such a system for its design for high-level of abstract is based on the classic approach known from the theory of task scheduling, but it is significantly extended, among others, by the characteristics of tasks and resources as well as additional criteria of optimal system in scope structure and operation. The metaheuristic algorithm operating according to this model introduces a new approach to system synthesis, in which parallelism of task scheduling and resources partition is applied. An algorithm based on a genetic approach with simulated annealing and Boltzmann tournaments, avoids local minima and generates optimized solutions. Such a synthesis is based on the implementation of task scheduling, resources identification and partition, allocation of tasks and resources and ultimately on the optimization of the designed system in accordance with the optimization criteria regarding cost of implementation, execution speed of processes and energy consumption by the system during operation. This paper presents examples and results for multi-criteria optimization, based on calculations for specifying non-dominated solutions and indicating a subset of Pareto solutions in the space of all solutions.

• Advances in robotics research
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• v.2 no.3
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• pp.247-257
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• 2018

Various studies have been performed to coordinate robots in transporting objects and different artificial intelligence algorithms have been considered in this field. In this paper, we investigate and solve Multi-Robot Transportation problem by using a combined auction algorithm. In this algorithm each robot, as an agent, can perform the auction and allocate tasks. This agent tries to clear the auction by studying different states to increase payoff function. The algorithm presented in this paper has been applied to a multi-robot system where robots are responsible for transporting objects. Using this algorithm, robots are able to improve their actions and decisions. To show the excellence of the proposed algorithm, its performance is compared with three heuristic algorithms by statistical simulation approach.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.634-636
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• 2004

실시간 운영체제는 멀티태스킹 및 ITC(Inter Task Communication)를 제공한다는 면에서는 범용운영체제와 비슷하나, 시간 결정성을 보장해야 한다는 면에서는 일반 운영체제와 다르다. 실시간 시스템에서는 메모리를 할당하는데 있어서 시간 제약을 어기지 않아야 하기 때문에 동적 메모리 할당은 효율적으로 구성되어야 한다. 본 논문에서는 실시간 운영체제 $_{1}$RTOS$^{TM}$에서 메모리 할당에 소요되는 시간을 향상시키기 위해 최대 힙 알고리즘을 적용한 메모리 할당 기법을 설계 및 구현하였다.

• 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.