• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.167-174
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• 2005

This paper experimentally validates the efficacy of scheduling method that satisfies the performance requirement of periodic data in the Foundation Fieldbus. The scheduling method allocates periodic data traffic to a bandwidth-limited fieldbus medium. The scheduling method generates schedule list that records schedule starting time and schedule period of each periodic data. This study developed an experimental model of a Foundation Fieldbus network system. Using the experimental model, this study showed that the scheduling method can be easily implemented in a practical Foundation Fieldbus network system. The results obtained from the experimental evaluation showed that the scheduling method restricts the delay of periodic data to a pre-specified bound.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5013-5034
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• 2019

In the Peer-to-Peer (P2P) streaming systems, peers randomly form a network overlay to share video resources with a data scheduling scheme. A data scheduling scheme can have a great impact on system performance, which should achieve two optimal objectives at the same time ideally. The two optimization objectives are to improve the perceived video quality and maximize the network throughput, respectively. Maximizing network throughput means improving the utilization of peer's upload bandwidth. However, maximizing network throughput will result in a reduction in the perceived video quality, and vice versa. Therefore, to achieve the above two objects simultaneously, we proposed a new data scheduling scheme based on multi-objective particle swarm optimization data scheduling scheme, called MOPSO-DS scheme. To design the MOPSO-DS scheme, we first formulated the data scheduling optimization problem as a multi-objective optimization problem. Then, a multi-objective particle swarm optimization algorithm is proposed by encoding the neighbors of peers as the position vector of the particles. Through extensive simulations, we demonstrated the MOPSO-DS scheme could improve the system performance effectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5805-5825
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• 2019

Smartphones are important platforms because of their sophisticated computation, communication, and sensing capabilities, which enable a variety of applications in the Internet of Things (IoT) systems. Moreover, advancements in hardware have enabled sensors on smartphones such as environmental and chemical sensors that make sensor data collection readily accessible for a wide range of applications. However, dynamic, opportunistic, and heterogeneous mobility patterns of smartphone users that vary throughout the day, which greatly affects the efficacy of sensor data collection. Therefore, it is necessary to consider phone users mobility patterns to design data collection schedules that can reduce the loss of sensor data. In this paper, we propose a mobility-based weighted adaptive opportunistic scheduling framework that can adaptively adjust to the dynamic, opportunistic, and heterogeneous mobility patterns of smartphone users and provide prioritized scheduling based on various application scenarios, such as velocity, region of interest, and sensor type. The performance of the proposed framework is compared with other scheduling frameworks in various heterogeneous smartphone user mobility scenarios. Simulation results show that the proposed scheduling improves the transmission rate by 8 percent and can also improve the collection of higher-priority sensor data compared with other scheduling approaches.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5A
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• pp.574-582
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• 2004

This paper shows the performance comparisons of several different rate scheduling schemes for non-real time data service over the uplink of burst switching-based direct sequencecode division multiple access (DS/CDMA) system to support the integrated voice/data service. The closed-form solution of optimal scheduling formulation, which minimizes average transmission delay when all of the active data users are transmitting simultaneously, is presented and mathematical analyses with other rate scheduling schemes, which provide efficiency criterion of transmission delay for rate scheduling schemes, are performed. Numerical results show the analyses explicitly.

• Journal of the Korea Society of Computer and Information
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• v.23 no.9
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• pp.43-50
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• 2018

In this paper, we propose a hexagon model-based efficient beacon frame scheduling approach for wireless sensor networks. The existing beacon frame scheduling approaches use a lot of slots and subslots for the beacon frame scheduling. Thus, the data from source nodes are not efficiently delivered to a sink node. Also in case a sink node needs to broadcast a beacon frame to the nodes in the network, delivering the beacon frame to the network nodes is not efficient as well. Thus, to solve the problem, we use a hexagon model to find the number of slots and subslots for the beacon frame scheduling. By using them for the beacon frame scheduling, the proposed approach performs better than other approaches in terms of the data transmission delay, the number of received data, the beacon transmission delay and the number of relaying the beacon frames.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.7
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• pp.719-727
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• 2006

This paper proposes a new method to obtain a maximum allowable delay bound for a scheduling of networked discrete control systems and event-based scheduling method. The proposed method is formulated in terms of linear matrix inequalities and can give a much less conservative delay bound than the existing methods. A network scheduling method is presented based on the delay obtained through the proposed method, and it can adjust the sampling period to allocate same utilization to each control loop. The presented method can handle three types of data (sporadic, emergency data, periodic data and non real-time message) and guarantees real-time transmission of periodic and sporadic emergency data using modified EDF scheduling method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.11
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• pp.2124-2126
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• 2008

In the wireless communication systems, the demand of multimedia services is also increased. Unlike typical data packets, realtime service such as VoIP packets have delay bound and low loss rate requirement. In this paper we propose a new scheduling algorithm that be able to allocate resources to the different kinds of services such as VoIP and data packet. The proposed algorithm considers both time delay and channel condition toe determine the priority. Simulation results show that the proposed algorithm works more efficiently than the conventional algorithms.

• Journal of Electrical Engineering and information Science
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• v.3 no.1
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• pp.1-7
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• 1998

High-Level synthesis of digital circuits calls for automatic translation of a behavioral description to a structural design entity represented in terms of components and connection. One of the critical steps in high-level synthesis is to determine a particular scheduling algorithm that will assign behavioral operations to control states. A new scheduling algorithm called Data Availability Scheduling (DAS) for high-level synthesis is presented. It can determine an appropriate scheduling algorithm and minimize the number of states required using data availability and dependency conditions extracted from the behavioral code, taking into account of states required using data availability and dependency conditions extracted from the behavioral code, taking into account resource constraint in each control state. The DAS algorithm is efficient because data availability conditions, and conditional and wait statements break the behavioral code into manageable pieces which are analyzed independently. The output is the number of states in a finite state machine and shows better results than those of previous algorithms.

• Journal of Computing Science and Engineering
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• v.10 no.1
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• pp.9-20
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• 2016

Several task clustering heuristics are proposed for allocating tasks in heterogeneous systems to achieve a good response time in data intensive jobs. However, one of the challenging problems is the process in task scheduling after task allocation by task clustering. We propose a task scheduling method after task clustering, leveraging worst schedule length (WSL) as an upper bound of the schedule length. In our proposed method, a task in a WSL sequence is scheduled preferentially to make the WSL smaller. Experimental results by simulation show that the response time is improved in several task clustering heuristics. In particular, our proposed scheduling method with the task clustering outperforms conventional list-based task scheduling methods.