• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.131-134
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• 1996

Application of machine learning to scheduling problems has focused on improving system performance based on opportunistic selection among multitudes of simple rules. This study proposes a new method of learning scheduling rules, which first establishes qualitatively meaningful criteria and quantitatively optimizes the use of them, a similar way as human scheduler accumulate their expertise. The weighting of these criteria is trained in response to the system states through simulation. To mimic human quantitative feelings, distributed fuzzy sets are used for assessing the system state. The proposed method was applied to job dispatching in a simulated FMS environment. The job-dispatching criteria used were the length of the processing time of a job and the situation of the next workstation. The results show that the proposed method can develop efficient and robust scheduling strategies, which can also provide understandable and usable know-hows to the human scheduler.

• Journal of Communications and Networks
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• v.5 no.3
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• pp.230-239
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• 2003

In this paper, we propose a framework to study how to route packets efficiently in multipath communication networks. Two traffic congestion control techniques, namely, flow assignment and packet scheduling, have been investigated. The flow assignment mechanism defines an optimal splitting of data traffic on multiple disjoint paths. The resequencing delay and the usage of the resequencing buffer can be reduced significantly by properly scheduling the sending order of all packets, say, according to their expected arrival times at the destination. To illustrate our model, and without loss of generality, Gaussian distributed end-to-end path delays are used. Our analytical results show that the techniques are very effective in reducing the average end-to-end path delay, the average packet resequencing delay, and the average resequencing buffer occupancy for various path configurations. These promising results can form a basis for designing future adaptive multipath protocols.

• Journal of Communications and Networks
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• v.4 no.3
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• pp.209-220
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• 2002

In this paper, we propose a hierarchical packet scheduling technique to closely approximate a hierarchical extension of the generalized processor sharing model, Hierarchical Generalized Processor Sharing (H-GPS). Our approach is to undertake the tasks of service guarantee and hierarchical link sharing in an independent manner so that each task best serves its own objective. The H-GPS model is decomposed into two separate service components: the guaranteed service component to consistently provide performance guarantees over the entire system, and the excess service component to fairly distribute spare bandwidth according to the hierarchical scheduling rule. For tight and harmonized integration of the two service components into a single packet scheduling algorithm, we introduce two novel concepts of distributed virtual time and service credit, and develop a packet version of H-GPS called Hierarchical Fair Queueing (HFQ). We demonstrate the layerindependent performance of the HFQ algorithm through simulation results.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.5_6
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• pp.307-318
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• 2003

In this paper, we design and construct a TMO object group that provides the guaranteed real-time services in the distributed object computing environments, and verify execution power of its model for the correct distributed real-time services. The TMO object group we suggested is based on TINA's object group concept. This model consists of TMO objects having real-time properties and some components that support the object management service and the real-time scheduling service in the TMO object group. Also TMO objects can be duplicated or non-duplicated on distributed systems. Our model can execute the guaranteed distributed real-time service on COTS middlewares without restricting the specially ORB or the of operating system. For achieving goals of our model. we defined the concepts of the TMO object and the structure of the TMO object group. Also we designed and implemented the functions and interactions of components in the object group. The TMO object group includes the Dynamic Binder object and the Scheduler object for supporting the object management service and the real-time scheduling service, respectively The Dynamic Binder object supports the dynamic binding service that selects the appropriate one out of the duplicated TMO objects for the clients'request. And the Scheduler object supports the real-time scheduling service that determines the priority of tasks executed by an arbitrary TMO object for the clients'service requests. And then, in order to verify the executions of our model, we implemented the Dynamic Binder object and the Scheduler object adopting the binding priority algorithm for the dynamic binding service and the EDF algorithm for the real-time scheduling service from extending the existing known algorithms. Finally, from the numerical analyzed results we are shown, we verified whether our TMO object group model could support dynamic binding service for duplicated or non-duplicated TMO objects, also real-time scheduling service for an arbitrary TMO object requested from clients.

• Journal of Advanced Navigation Technology
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• v.16 no.3
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• pp.471-479
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• 2012

In cellular femto systems, femto Base stations(f-BSs) can be installed unnecessarily and overcrowded in small areas. This will cause an interference problem and it can impact on the capacity, blocking probability, and coverage of femtocells in the shared channel systems. In this paper, we propose a load distribution scheme by using forced handover and probabilistic subchannel scheduling policy to resolve the problem. The proposed scheme operates in distributed manner though communication with neighboring f-BSs, and includes self-detection of overcrowded area and radio resource management based on measurements. We evaluate the performance of the proposed scheme in terms of average cell throughput and average throughput per users.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2397-2399
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• 2004

This paper deals with the messages scheduling of a CAN (Controller Area Network), based on the distributed control scheme to integrate actuators and sensors in a humanoid robot. In order to supply the distributed processing for a humanoid robot, each control unit should have the efficient control method, fast calculation and valid data exchange. The preliminary study has concluded that the performance of CAN is better and easier to implement than other network such as FIP (Factory Instrumentation Protocol), VAN (Vehicle Area Network), etc. Since humanoid robot has to treat the significant control signals from many actuators and sensors, the communication time limitation could be critical according to the transmission speed and data length of CAN specification. In this paper, the CAN message scheduling in humanoid robot was suggested under the presence of Jitter in the message group, the existence of high load of messages over the network and the presence of transmission errors. In addition, the response time under the worst case is compared with the simulation by using the simulation algorithm. As a result, the suggested messages scheduling can guarantee our CAN limitation, and utilized to generate the walking patterns for the humanoid.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.193-214
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• 2017

In this paper, we study the problem of network utility maximization in a CSMA based multi-hop wireless network. Existing work in this aspect typically adopted continuous time Markov model for performance modelling, which fails to consider the channel conflict impact in actual CSMA networks. To maximize the utility of a CSMA based wireless network with channel conflict, in this paper, we first model its weighted network capacity (i.e., network capacity weighted by link queue length) and then propose a distributed link scheduling algorithm, called CSMA based Maximal-Weight Scheduling (C-MWS), to maximize the weighted network capacity. We derive the upper and lower bounds of network utility based on C-MWS. The derived bounds can help us to tune the C-MWS parameters for C-MWS to work in a distributed wireless network. Simulation results show that the joint optimization based on C-MWS can achieve near-optimal network utility when appropriate algorithm parameters are chosen and also show that the derived utility upper bound is very tight.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.7
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• pp.304-318
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• 2007

Grid computing is a service that share geographically distributed computing resources through high speed network. In this paper, we propose hybrid scheduling scheme which considers not only meta-scheduling scheme to distribute the job between the nodes of grid computing system but also the job scheduling to distribute the job within the local nodes. According to the number of processors needed and expected execution time, the job with high priority is allocated to job queue while the one with low priority and remote job are allocated to backfill queue. We evaluate the proposing scheme through the various experiments and the results show that the utilization of grid computing system increases and the job slowdown decreases.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.327-333
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• 2022

Wireless Sensor Networks (WSNs) plays an important role in our everyday life. WSN is distributed in all the places. Nowadays WSN devices are developing our world as smart and easy to access and user-friendly. The sensor is connected to all the resources based on the uses of devices and the environment [1]. In WSN, Quality of Service is based on time synchronization and scheduling. Scheduling is important in WSN. The schedule is based on time synchronization. Min-Max data size scheduling is used in this proposed work. It is used to reduce the Delay & Energy. In this proposed work, Two-hop neighboring node is used to reduce energy consumption. Data Scheduling is used to identify the shortest path and transmit the data based on weightage. The data size is identified by three size of measurement Min, Max and Medium. The data transmission is based on time, energy, delivery, etc., the data are sent through the first level shortest path, then the data size medium, the second level shortest path is used to send the data, then the data size is small, it should be sent through the third level shortest path.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.808-813
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• 2003

Maintaining agility and responsiveness m designing and manufacturing activities are the key issues for manufacturing companies to cope with global competition. Distributed design and control systems are regarded as an efficient solution for agility and responsiveness. However, distributed nature of a manufacturing system complicates production activities such as design, simulation, scheduling, and execution control. Especially, existing simulation systems have limited external integration capabilities, which make it difficult to implement complex control mechanisms for the distributed manufacturing systems. Moreover, integration and coupling of heterogeneous components and models are commonly required for the simulation of complex distributed systems. In this paper, a collaborative and adaptive simulation architecture is proposed as an open framework for simulation and analysis of the distributed manufacturing enterprises. By incorporating agents with their distributed characteristics of autonomy, intelligence, and goal-driven behavior, the proposed agent-based simulation architecture can be easily adapted to support the agile and distributed manufacturing systems. The architecture supports the coordination and cooperation relations, and provides a communication middleware among the participants in simulation.