• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1B
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• pp.22-30
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• 2007

In this paper, to achieve consistency maintenance as well as stable service execution, we build a Fault-Tolerant Object Group framework that provides both of the group management service and the load scheduling service. The group management service supports the object management such as registration and authentication, and provides two schemes for failure recovery using the service priority and the checkpointing. In the load scheduling servile, we improve the effectiveness of service execution through the reasoning process of object loads based on the ANFIS architecture. The effectiveness in the performance of the developed framework is validated through a virtual home-network simulation based on the FTOG framework.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.149-152
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• 2000

The chartered bus scheduling is to determine the allocation of buses to customer service requests. For the scheduling, we first represent the scheduling problem using a graph and develop a mathematical model. Second, we develop an algorithm for the scheduling problem including heuristic methods. We tested the performance of the algorithm on instances with real data. As a result, the total empty load driving time is reduced over 10% comparing with that of current practice at the company

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4103-4121
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• 2018

Quality of Service (QoS) awareness is recognized as a key point for the success of Internet of Things (IOT).Realizing the full potential of the Internet of Things requires, a real-time task scheduling algorithm must be designed to meet the QoS need. In order to schedule tasks with diverse QoS requirements in cloud environment efficiently, we propose a task scheduling strategy based on dynamic priority and load balancing (DPLB) in this paper. The dynamic priority consisted of task value density and the urgency of the task execution, the priority is increased over time to insure that each task can be implemented in time. The scheduling decision variable is composed of time attractiveness considered earliest completion time (ECT) and load brightness considered load status information which by obtain from each virtual machine by topic-based publish/subscribe mechanism. Then sorting tasks by priority and first schedule the task with highest priority to the virtual machine in feasible VMs group which satisfy the QoS requirements of task with maximal. Finally, after this patch tasks are scheduled over, the task migration manager will start work to reduce the load balancing degree.The experimental results show that, compared with the Min-Min, Max-Min, WRR, GAs, and HBB-LB algorithm, the DPLB is more effective, it reduces the Makespan, balances the load of VMs, augments the success completed ratio of tasks before deadline and raises the profit of cloud service per second.

• 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.

• The Journal of Engineering Research
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• v.7 no.1
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• pp.29-36
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• 2005

In multi-server environment, We have to design a mechanism that selects appropriate servers for processing each service request while maximizing server throughput and minimizing average response of service requests. In this paper, we propose a job scheduling method for courseware delivery system using a idle computing resources on LAN. The proposed scheduling method propose an approach that uses client service request time, server available period and server load of requested service as guidelines of server selection. Comparing the our approach method to conventional one, experiments that the proposed approach provides better performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2B
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• pp.11-20
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• 2005

Strict priority scheduling scheme is a good candidate for the implementation of service differentiation in an Internet because of simplicity in implementation and the capability to guarantee the delay requirement of the highest class of traffic. However, it is also blown that strict priority starves the lower-class traffic at the cost of prioritizing the higher-class traffic. The purpose of this work is to propose an analytic method which can estimate the average delay performance of Diffserv service architecture and shows that strict priority scheme does not sacrifice the lower class traffic over a diverse condition of the load. From the numerical experiments for three-class Diffserv network we validate our argument that strict priority scheme may be applied to a service differentiation scheme for the future Internet.

• Journal of information and communication convergence engineering
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• v.16 no.4
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• pp.264-270
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• 2018

In our research study, we aim at optimizing multiple load in cloud, effective resource allocation and lesser response time for the job assigned. Using Hadoop on datacenter is the best and most efficient analytical service for any corporates. To provide effective and reliable performance analytical computing interface to the client, various cloud service providers host Hadoop clusters. The previous works done by many scholars were aimed at execution of workflows on Hadoop platform which also minimizes the cost of virtual machines and other computing resources. Earlier stochastic hill climbing technique was applied for single parameter and now we are working to optimize multiple parameters in the cloud data centers with proposed heuristic hill climbing. As many users try to priorities their job simultaneously in the cluster, resource optimized workflow scheduling technique should be very reliable to complete the task assigned before the deadlines and also to optimize the usage of the resources in cloud.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.126-133
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• 2023

Recent advancements in cloud service virtualization technologies have witnessed a shift from a Virtual Machine-centric approach to a container-centric paradigm, offering advantages such as faster deployment and enhanced portability. Container orchestration has emerged as a key technology for efficient management and scheduling of these containers. However, with the increasing complexity and diversity of heterogeneous workloads and service types, resource scheduling has become a challenging task. Various research endeavors are underway to address the challenges posed by diverse workloads and services. Yet, a systematic approach to container orchestration for effective cloud management has not been clearly defined. This paper proposes the DRA-Engine (Dynamic Resource Allocation Engine) for resource scheduling in container orchestration. The proposed engine comprises the Request Load Procedure, Required Resource Measurement Procedure, and Resource Provision Decision Procedure. Through these components, the DRA-Engine dynamically allocates resources according to the application's requirements, presenting a solution to the challenges of resource scheduling in container orchestration.

• 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.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.1
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• pp.85-101
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• 1995

Automated Guided Vehicles(AGVs) are widely used in computer integrated manufacturing(CIM) systems for material handling purposes. Although automated guided vehicles provide higher levels of flexibility and computer integrability, the installations are limited in number and one of the critical reasons lies in the complexity involved in the operation. The main objective of this research is to alleviate this problem by proposing efficient integrated operational control methods for AGV-based CIM systems. Particularly, this research is concerned with the mixed problem of dispatching automated guided vehicles and scheduling machines operation. The proposed dynamic heuristic algorithm uses various priority schemes and relevant information concerning the load of the system, the status of queues, and the position of AGVs in the scheduling process. The scheduling decision process is hierarchical in the sense that different decision criteria are applied sequentially to identify the most appropriate part to be served. This algorithm consists of two sections, the section of part selection by AGVs for the next service whenever an AGV completes the current assignment, and the section of part selection by machines for next service whenever a machine completes the current operation. The proposed algorithm has been compared with other scheduling schemes using the performance measure of mean flow-time and mean tardiness. Simulation results indicate that the proposed algorithm can reduce the mean flow-time and mean tardiness significantly.