• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9B
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• pp.823-833
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• 2003

To satisfy the requirements of the real-time Internet services, queue management and scheduling schemes should be enhanced to accommodate the delay and jitter characteristic of them. Although the existing queue management schemes can address the congestion problems of TCP flows, they have some problems in supporting real-time services. That is, they show performance degradation when burst traffics are continuously going into the system after the queue is occupied at a predefined threshold level. In addition, under the congestion state, they show large jitter, which is not a desirable phenomenon for real-time transmissions. To resolve these problems, we propose a SDRED (State Dependent Random Early Detection) and dynamic scheduling scheme that can improve delay and jitter performances by adjusting RED parameters such as ma $x_{th}$ and $w_{q}$ according to the queue status. The SDRED is designed to adapt to the current traffic situation by adjusting the max,$_{th}$ and $w_{q}$ to four different levels. From the simulation results, we show that the SDRED decreases packet delays in a queue and has more stable jitter characteristics than the existing RED, BLUE, ARED and DSRED schemes.mes.mes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1554-1566
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• 2014

Cloud Computing allows application providers seamlessly scaling their services and enables users scaling their usage according to their needs. In this paper, using queuing game model, we present service scheduling schemes which are used in software as a service (SaaS). The object is maximizing the Cloud Computing platform's (CCP's) payoff via controlling the service requests whether to join or balk, and controlling the value of CCP's admission fee. Firstly, we treat the CCP as one virtual machine (VM) and analyze the optimal queue length with a fixed admission fee distribution. If the position number of a new service request is bigger than the optimal queue length, it balks. Otherwise, it joins in. Under this scheme, the CCP's payoff can be maximized. Secondly, we extend this achievement to the multiple VMs situation. A big difference between single VM and multiple VMs is that the latter one needs to decide which VM the service requests turn to for service. We use a corresponding algorithm solve it. Simulation results demonstrate the good performance of our schemes.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.2
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• pp.9-17
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• 1994

This paper proposes Double queue threshold QLT(Queue Length Threshold) algorithm and Hysteresis effect QLT algorithm. as being DPS(Dynamic Priority Scheduling) techniques. in order to advance the processing of multiple class traffics. Also, the performance of the proposed algorithms is analyzed through computer simulations,and the priority scheduling is analyzed using a retrial queue with two types of calls. Our simulation results show that the performance of the proposed Double queue length threshold QLT algorithm is superior to that of the conventinal QLT algorithm for 2 or more classes delay sensitive traffics. Also we find that Hysteresis effecT QLT algorithm is better mechanism than that of the existing QLT for real time and non-real time traffics.

• Journal of KIISE:Information Networking
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• v.30 no.1
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• pp.38-47
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• 2003

Communication between Bluetooth devices is based on TDD by a master unit. In this discipline, the transmission of slave packets can be made only when the master transmits a packet to the slave. Thus, some slots may be wasted when there is no user data in the master's or slave's queue due to the transmission of a POLL or NULL packet. Therefore a scheduling scheme which can minimize the slot waste is required in Bluetooth intra-piconet communication. However, since the master is responsible for the intra-piconet scheduling, it must be provided with an information on each slave's queue length to apply traditional scheduling schemes. which is impossible in Bluetooth. This paper presents a new Bluetooth intra-piconet scheduling scheme that is efficient and does not require the information on each slave's queue length. The scheduling is done based on the information about the existence of data in the master and slave queues which is derived by the master identifying the type of packets transmitted. The master schedules to communicate with the slaves according to the priorities determined based on this information. We Presents simulation results which indicate a significant improvement in the performance when our proposed scheme is used.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.541-551
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• 2009

Generalized processor sharing(GPS) service policy is a scheduling algorithm to allocate the bandwidth of a queueing system with multi-class input traffic. In a queueing system with single-class traffic, the stationary queue length becomes larger stochastically when the bandwidth (i.e. the service rate) of the system decreases. For a given GPS server, we consider the similar problem to this. We define the monotonicity for the head of the line processor sharing(HLPS) servers in which the units in the heads of the queues are served simultaneously and the bandwidth allocated to each queue are determined by the numbers of units in the queues. GPS is a type of monotonic HLPS. We obtain the HLPS server whose queue length of a class stochastically bounds upper that of corresponding class in the given monotonic HLPS server for all classes. The queue lengths process of all classes in the obtained HLPS server has the stationary distribution of product form. When the given monotonic HLPS server is GPS server, we obtain the explicit form of the stationary queue lengths distribution of the bounding HLPS server. Numerical result shows how tight the stochastic bound is.

• 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.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.165-170
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• 2023

Scheduling algorithms plays a significant role in optimizing the CPU in operating system. Each scheduling algorithms schedules the processes in the ready queue with its own algorithm design and its properties. In this paper, the performance analysis of First come First serve scheduling, Non preemptive scheduling, Preemptive scheduling, Shortest Job scheduling and Round Robin algorithm has been discussed with an example and the results has been analyzed with the performance parameters such as minimum waiting time, minimum turnaround time and Response time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6A
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• pp.474-480
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• 2005

In this paper, we present a new scheduling scheme for MIMO OFDM Multiuser Diversity System. This scheduling scheme maximizes the system throughput, and at the same time fairly shares the resources based on the feedback information from the receivers and the queue information. To show the effectiveness of the proposed algorithm, we evaluate the performance of the proposed algorithm as compared to K&H and RR algorithms.

• Journal of Internet of Things and Convergence
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• v.10 no.3
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• pp.19-24
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• 2024

Recent advances in large-scale data processing technologies such as big data, cloud computing, and artificial intelligence have increased the demand for high-performance storage devices in data centers and enterprise environments. In particular, the fast data response speed of storage devices is a key factor that determines the overall system performance. Solid state drives (SSDs) based on the Non-Volatile Memory Express (NVMe) interface are gaining traction, but new bottlenecks are emerging in the process of handling large data input and output requests from multiple hosts simultaneously. SSDs typically process host requests by sequentially stacking them in an internal queue. When long transfer length requests are processed first, shorter requests wait longer, increasing the average response time. To solve this problem, data transfer timeout and data partitioning methods have been proposed, but they do not provide a fundamental solution. In this paper, we propose a dual queue based scheduling scheme (DQBS), which manages the data transfer order based on the request order in one queue and the transfer length in the other queue. Then, the request time and transmission length are comprehensively considered to determine the efficient data transmission order. This enables the balanced processing of long and short requests, thus reducing the overall average response time. The simulation results show that the proposed method outperforms the existing sequential processing method. This study presents a scheduling technique that maximizes data transfer efficiency in a high-performance SSD environment, which is expected to contribute to the development of next-generation high-performance storage systems

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.532-532
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• 2006