• Journal of KIISE
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• v.43 no.3
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• pp.314-326
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• 2016

Some process algebras were applied to enterprise business modelling for formal specification and verification. ${\pi}$-calculus and mobile ambient can be considered for the distributed and mobile, especially to represent the movements of distributed real-time business processes. However there are some limitations to model the movements: 1) ${\pi}$-calculus passes the name of port for indirect movements, and 2) mobile ambient uses ambient to synchronize asynchronous movements forcefully. As a solution to the limitations, this paper presents a new process algebra, called ${\delta}$-calculus, to specify direct and synchronous movements of business processes over geo-temporal space. Any violation of safety or security of the systems caused by the movements can be indicated by the properties of the movements: synchrony, priority and deadline. A tool, called SAVE, was developed on ADOxx metamodelling platform to demonstrate the concept.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2543-2554
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• 2000

Packet schedulers for real-time communication must provide bounded delay and efficient use of network resources such as bandwidth, buffers and so on. In order to satisfy them, a large number of packet scheduling methods have been proposed. Among packet scheduling methods, an EDF (Earliest Deadline First) scheduling is the optimal one for a bounded delay service. A disadvantage of EDF scheduling is that queued packets must be sorted according to their deadlines, requiring a search operation whenever a new packet arrives at the scheduler. Although an RPQ (Rotating Priority Queue) scheduler, requiring large size of buffers, does not use such operation, it can closely approximate the schedulability of an EDF scheduler. To overcome the buffer size problem of an RPQ scheduler, this paper proposes a new scheduler named MRPQ (Multiple Rotating Priority Queue). In a MRPQ scheduler, there are several layers with a set of Queues. In a layer, Queues are configured by using a new strategy named block Queue. A MRPQ scheduler needs nearly half of buffer size required in an RPQ scheduler and produces schedulability as good as an RPQ scheduler.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.9-16
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• 2016

The project schedule risk in the engineering and facility construction industry is increasingly considered as important management factor because the risks in terms of schedule or deadline may significantly affect the project cost. Especially, the project-based operating companies attempt to find the best estimate of the project completion time for use at their proposals, and therefore, usually have much interest in accurate estimation of the duration of the projects. In general, the management of projects schedule risk is achieved by modeling project schedule with PERT/CPM techniques, and then performing risk assessment with simulation such as Monte-Carlo simulation method. However, since these approaches require the accumulated executional data, which are not usually available in project-based operating company, and, further, they cannot reflect various schedule constraints, which usually are met during the project execution, the project managers have difficulty in preparing for the project risks in advance of their occurrence in the project execution. As these constraints may affect time and cost which role as the crucial evaluation factors to the quality of the project result, they must be identified and described in advance of their occurrence in the project management. This paper proposes a Bayesian Net based methodology for estimating project schedule risk by identifying and enforcing the project risks and its response plan which may occur in storage tank engineering and construction project environment. First, we translated the schedule network with the project risks and its response plan into Bayesian Net. Second, we analyzed the integrated Bayesian Net and suggested an estimate of project schedule risk with simulation approach. Finally, we applied our approach to a storage tank construction project to validate its feasibility.

• The KIPS Transactions:PartA
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• v.8A no.3
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• pp.217-226
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• 2001

In this paper, for continuous media access operations performed by Clustered Continuous Media Storage Server (CCMSS) system, we present the analytical model based on the open queueing network, which considers simultaneously two critical delay factors, the disk I/O and the internal network, in the CCMSS system. And we derive by using the analytical model the stochastic model for the total service delay time in the system. Next, we propose the integrated stochastic admission control model for the CCMSS system, which estimate the maximum number of admittable service requests at the allowable service failure rate by using the derived stochastic model and apply the derived number of requests in the admission control operation. For the performance evaluation of the proposed model, we evaluated the deadline miss rates by means of the previous stochastic model considering only the disk I/O and the propose stochastic model considering the disk I/O and the internal network, and compared the values with the results obtained from the simulation under the real cluster-based distributed media server environment. The evaluation showed that the proposed admission control policy reflects more precisely the delay factors in the CCMSS system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10C
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• pp.1469-1483
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• 2004

We propose a packet scheduling algorithms for streaming media. We assume that the receiver periodically reports back the channel throughput. From the original video data, the importance level of a video packet is determined by its relative position within its group of pictures, taking into account the motion-texture discrimination and temporal scalability. Thus, we generate a number of nested substreams. Using feedback information from the receiver and statistical characteristics of the video, we model the streaming system as a queueing system, compute the run-time decoding failure probability of a Same in each substream based on effective bandwidth approach, and determine the optimum substream to be sent at that moment in time. Since the optimum substream is updated periodically, the resulting sending order is different from the original playback order. From experiments with real video data, we show that our proposed scheduling scheme outperforms the conventional sequential sending scheme.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.527-534
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• 2023

Triple modular redundancy (TMR) systems can continue their mission by virtue of their structural redundancy even if one processor is attacked by faults. In this paper, we propose a new fault tolerance strategy by introducing checkpoints into the TMR system in which data saving and fault detection processes are separated while they corporate together in the conventional checkpoints. Faults in one processor are tolerated by synchronizing the state of three processors upon detecting faults. Simultaneous faults occurring to more than one processor are tolerated by re-executing the task from the latest checkpoint. We propose the checkpoint placement and fault detection strategy to maximize the probability of successful execution of a task within the given deadline. We develop the Markov chain model for the TMR system having the proposed checkpoint strategy, and derive the optimal fault detection and checkpoint interval.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.484-493
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• 2001

As real-time database systems are extended to the distributed computing environment, the need to apply the existing real-time concurrency control schemes to the distributed computing environment has been made. In this paper we propose an efficient concurrency control scheme for distributed real-time database system. Our proposed scheme guarantees a transaction to commit at its maximum, reduces the restart of a transaction that is on the prepared commit phase, and minimizes the time of the lock holding. This is because it raises the priority of the transaction that is on the prepared commit phase in the distributed real-time computing environment. In addition, it reduces the waiting time of a transaction that owns borrowed data and improves the performance of the system, as a result of lending the data that the transaction with the raised priority holds. We compare the proposed scheme with DO2PL_PA(Distributed Optimistic Two-Phase Locking) and MIRROR(Managing Isolation in Replicated Real-time Object Repositories) protocol in terms of the arrival rate of transactions, the size of transactions, the write probability of transactions, and the replication degree of data in a firm-deadline real-time database system based on two-phase commit protocol. It is shown through the performance evaluation that our scheme outperforms the existing schemes.

• The KIPS Transactions:PartC
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• v.14C no.4
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• pp.371-382
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• 2007

In this paper, we propose a real-time sensor node platform that efficiently manages periodic and aperiodic tasks. Since existing sensor node platforms available in literature focus on minimizing the usage of memory and power consumptions, they are not capable of supporting the management of tasks that need their real-time execution and fast average response time. We first analyze how to structure periodic or aperiodic task decomposition in the TinyOS-based sensor node platform as regard to guaranteeing the deadlines of ail the periodic tasks and aiming to providing aperiodic tasks with average good response time. Then we present the application and efficiency of the proposed real-time sensor node platform in the sensor node equipped with a low-power 8-bit microcontroller, an IEEE802.15.4 compliant 2.4GHz RF transceiver, and several sensors. Extensive experiments show that our sensor node platform yields efficient performance in terms of three significant, objective goals: deadline miss ratio of periodic tasks, average response time of aperiodic tasks, and processor utilization of periodic and aperiodic tasks.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.17-27
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• 2022

In this paper, ED-H algorithm, an optimal real-time scheduling algorithm dealing with the characteristics of the integrated energy harvester system with a capacitor, is extended to satisfy the time constraint under the blackout state which is a deliberate power-off state by an intelligent power management unit adopted in the system. If the power supply system does not have enough energy, it temporarily shuts off the power supply to protect the circuit and capacitor and resumes the supply again when the capacitor is fully charged, which may delay the task execution during these blackout states by calculating the time according to the occurrence of the events. To mitigate the problem, even if task execution is delayed by the original ED-H algorithm, the remaining time of the subsequent time units no longer can afford to delay the execution of the task is predicted in the extended algorithm and the task is forced to be scheduled to meet the time deadline. According to the simulation results, it is confirmed that the algorithm proposed in this paper has a high scheduling performance increase of 0.4% to 7.7% depending on the characteristics of the set of tasks compared to the ED-H.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8B
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• pp.509-520
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• 2007

In this paper, we propose a real-time sensor node platform that guarantees the real-time scheduling of periodic and aperiodic tasks through a multitask-based software decomposition technique. Since existing sensor networking operation systems available in literature are not capable of supporting the real-time scheduling of periodic and aperiodic tasks, the preemption of aperiodic task with high priority can block periodic tasks, and so periodic tasks are likely to miss their deadlines. This paper presents a comprehensive evaluation of how to structure periodic or aperiodic task decomposition in real-time sensor-networking platforms as regard to guaranteeing the deadlines of all the periodic tasks and aiming to providing aperiodic tasks with average good response time. A case study based on real system experiments is conducted to illustrate the application and efficiency of the multitask-based dynamic component execution environment in the sensor node equipped with a low-power 8-bit microcontroller, an IEEE802.15.4 compliant 2.4GHz RF transceiver, and several sensors. It shows that our periodic and aperiodic task decomposition technique yields efficient performance in terms of three significant, objective goals: deadline miss ratio of periodic tasks, average response time of aperiodic tasks, and processor utilization of periodic and aperiodic tasks.