• The KIPS Transactions:PartA
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• v.18A no.6
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• pp.255-264
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• 2011

A sensor network is a special network that makes physical data sensed by sensor nodes and manages the data. The sensor network is a technology that can apply to many parts of field. It is very important to transmit the data to a user at real-time. The core of the sensor network is a sensor node and small operating system that works in the node. TinyOS developed by UC Berkeley is a sensor network operating system that used many parts of field. It is event-driven and component-based operating system. Basically, it uses non-preemptive scheduler. If an urgent task needs to be executed right away while another task is running, the urgent one must wait until another one is finished. Because of that property, it is hard to guarantee real-time requirement in TinyOS. According to recent study, Priority Level Scheduler, which can let one task preempt another task, was proposed in order to have fast response in TinyOS. It has restrictively 5 priorities, so a higher priority task can preempt a lower priority task. Therefore, this paper suggests Preemptive EDF(Earliest Deadline First) Scheduler that guarantees a real-time requirement and reduces average respond time of user tasks in TinyOS.

• Journal of Electrical Engineering and information Science
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• v.2 no.3
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• pp.105-112
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• 1997

The performance of a shared memory multiprocessor system is very sensitive to process scheduling. w can enhance the performance of a whole system as well as of an individual process by taking the multiprocessor characteristics into account in the design of the process scheduler. In this paper, we proposed a general purpose scheduler for a shared memory multiprocessor, called the Two-Level Multi-Scan (TLMS) process scheduler, that considers the processor affinity loosely and decreases the interference among multiple processors greatly. The TLMS scheduler is composed of a local scheduler at each processor and a semi-global scheduler that balances the load among processors. In particular, the semi-global scheduler tries to minimize priority inversion, which is an important factor of the system performance. The TLMS scheduler also tries to reduce the number of resources to be shared and improves the processor utilization. to meet these requirements, th semi-global scheduler interacts with the operation of the local scheduler when a need arises, thus the name is loose processor-affinity. We also show that the proposed scheduling technique can be extended for other types of resources making it a general purpose resource management queue.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1302-1320
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• 2015

In cloud, everything can be provided as a service wherein a large number of users submit their jobs and wait for their services. hus, scheduling plays major role for providing the resources efficiently to the submitted jobs. The brainwave of the proposed ork is to improve user satisfaction, to balance the load efficiently and to bolster the resource utilization. Hence, this paper roposes an Adaptive Multilevel Scheduling System (AMSS) which will process the jobs in a multileveled fashion. The first level ontains Preprocessing Jobs with Multi-Criteria (PJMC) which will preprocess the jobs to elevate the user satisfaction and to itigate the jobs violation. In the second level, a Deadline Based Dynamic Priority Scheduler (DBDPS) is proposed which will ynamically prioritize the jobs for evading starvation. At the third level, Contest Mapping Jobs with Virtual Machine (CMJVM) is roposed that will map the job to suitable Virtual Machine (VM). In the last level, VM Scheduler is introduced in the two-tier VM rchitecture that will efficiently schedule the jobs and increase the resource utilization. These contributions will mitigate job iolations, avoid starvation, increase throughput and maximize resource utilization. Experimental results show that the performance f AMSS is better than other algorithms.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06b
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• pp.313-317
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• 2008

센서 네트워크는 여러 분야에서 활용할 수 있는 기술이다. 센서 노드가 외부에서 채취한 데이터를 실시간으로 사용자에게 전달하는 것은 매우 중요하다. UC 버클리에서 개발된 TinyOS는 센서 노드에서 동작하는 운영체제 중 가장 많이 사용되고 있다. TinyOS는 Event-driven 방식이며 Component 기반의 센서 네트워크 운영체제이다. 기본적으로 비선점 방식의 스케줄러를 사용함으로써 TinyOS의 실시간성을 보장하기 어렵다. 최근 연구에서 TinyOS의 빠른 반응성을 위해 Priority Level Scheduler라는 선점 기능이 제안되었다. 여기서 본 논문은 TinyOS의 실시간성의 보장을 위해 Priority Level Scheduler에 EDF(Earliest Deadline First)를 적용한 선점형 EDF 스케줄링 방식을 제안하고자 한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.3A
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• pp.223-232
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• 2004

In this paper we propose the hierarchical-based dynamic bandwidth allocation algorithm for multi-class services in Ethernet-PON. The proposed algorithm consists of the high level scheduler in OLT and the low level scheduler in ONU. The hierarchical architecture is able to provide scalability and resource efficiency in Ethernet-PON which has the distributed nature of the scheduling domain, with queues and the scheduler located at a large distance from each other. We also propose three dynamic bandwidth allocation algorithms for the low level scheduler: Proportional Allocation algorithm, Maximum Request First Allocation (MRFA) algorithm and High Priority First Allocation (HPFA) algorithm. We implement the Ethernet-PON standardized in the IEEE 802,3ah using OPNET. We also evaluate and analyze the performance for the proposed algorithms in terms of channel utilization, queuing delay and the amount of remainder.

• ETRI Journal
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• v.26 no.4
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• pp.321-331
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• 2004

In this paper, we propose a new dynamic bandwidth allocation (DBA) algorithm for multimedia services over Ethernet PONs (passive optical networks). The proposed algorithm is composed of a low-level scheduler in the optical network unit (ONU) and a high-level scheduler in the optical line terminal (OLT). The hierarchical DBA algorithm can provide expansibility and efficient resource allocation in an Ethernet PON system in which the packet scheduler is separated from the queues. In the proposed DBA algorithm, the OLT allocates bandwidth to the ONUs in proportion to the weight associated with their class and queue length, while the ONU preferentially allocates its bandwidth to queues with a static priority order. The proposed algorithm provides an efficient resource utilization by reducing the unused remaining bandwidth caused by the variable length of the packets. We also define the service classes and present control message formats conforming to the multi-point control protocol (MPCP) over an Ethernet PON. In order to evaluate the performance, we designed an Ethernet PON system on the basis of IEEE 802.3ah "Ethernet in the first mile" (EFM) using OPNET and carried out simulations. The results are analyzed in terms of the channel utilization, queuing delay, and ratio of the unused remaining bandwidth.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.585-588
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• 2008

센서 네트워크에 사용되는 운영체제 중 TinyOS는 Event-driven 방식이며 Component 기반의 센서 네트워크 운영체제이다. 이러한 TinyOS는 일단 태스크가 시작되면 마칠 때까지 다른 태스크가 기다려야하는 비선점형(Non-preemption) 방식이다. 최근 연구에서 TinyOS의 빠른 반응성을 위해 선점(Preemption)할 수 있는 기능이 추가되었다. 그러나 프로그래밍할 때 우선순위를 미리 주어줘야 하는 단점이 있다. 본 논문에서는 좀 더 유연하게 우선순위를 변경할 수 있는 방식을 제안하고자 한다.

• Journal of Communications and Networks
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• v.5 no.1
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• pp.73-81
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• 2003

The controlled load service defined within the IETF's Integrated Services architecture for quality-of-service (QoS) in the Internet requires source nodes to regulate their traffic while the network, in combination with an admission control strategy, provides a guarantee of performance equivalent to that achieved in a lightly loaded network. Packets sent in violation of the traffic contract are marked so that the network may assign them a lower priority in the use of bandwidth and buffer resources. In this paper, we define the requirements of a scheduler serving packets belonging to the controlled load service and present a novel scheduler that exactly achieves these requirements. In this set of requirements, besides efficiency and throughput, we include an additional important requirement to bound the additional delay of unmarked packets caused due to the transmission of marked packets while dropping as few marked packets as possible. Without such a bound, unmarked packets that are in compliance with the traffic contract are not likely to experience delays consistent with that in al lightly loaded network. For any given desired bound ${\alpha}$ on this additional delay, we present the CL(${\alpha}$) scheduler which achieves the bound while also achieving a per-packet work complexity of O(1) with respect to the number of flows. We provide an analytical proof of these properties of the CL(${\alpha}$) scheduler, and we also verify this with simulation using real traces of video traffic. The scheduler presented here may be readily adapted for use in scheduling flows with multi-level priorities such as in some real-time video streams, as well as in other emerging service models of the Internet that mark packets to identify drop precedences.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3201-3223
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• 2020

Wireless communication has become the promising technology in the recent times because of its applications in Internet of Things( IoT) devices. The IEEE 802.15.4e has become the key technology for IoT devices which utilizes the Time-Slotted Channel Hopping (TSCH) networks for the communication between the devices. In this paper, we develop a Two Level Scheduling Algorithm (TLSA) for scheduling multiple packets with different arrival rate at the source nodes in a TSCH networks based on the link activated by a centralized scheduler. TLSA is developed by considering three types of links in a network such as link i with packets arrival type 1, link j with packets arrival type 2, link k with packets arrival type 3. For the data packets arrival, two stages in a network is considered.At the first stage, the packets are considered to be of higher priority.At the second stage, the packets are considered to be of lower priority.We introduce level 1 schedule for the packets at stage 1 and level 2 schedule for the packets at stage 2 respectively. Finally, the TLSA is validated with the two different energy functions i.e., y = e^ax - 1 and y = 0.5x² using MATLAB 2017a software for the computation of average and worst ratios of the two levels.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2993-3010
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• 2021

The job shop scheduling problem (JSSP) plays a critical role in smart manufacturing, an effective JSSP scheduler could save time cost and increase productivity. Conventional methods are very time-consumption and cannot deal with complicated JSSP instances as it uses one optimal algorithm to solve JSSP. This paper proposes an effective scheduler based on deep learning technology named self-supervised long-short term memory (SS-LSTM) to handle complex JSSP accurately. First, using the optimal method to generate sufficient training samples in small-scale JSSP. SS-LSTM is then applied to extract rich feature representations from generated training samples and decide the next action. In the proposed SS-LSTM, two channels are employed to reflect the full production statues. Specifically, the detailed-level channel records 18 detailed product information while the system-level channel reflects the type of whole system states identified by the k-means algorithm. Moreover, adopting a self-supervised mechanism with LSTM autoencoder to keep high feature extraction capacity simultaneously ensuring the reliable feature representative ability. The authors implemented, trained, and compared the proposed method with the other leading learning-based methods on some complicated JSSP instances. The experimental results have confirmed the effectiveness and priority of the proposed method for solving complex JSSP instances in terms of make-span.