• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1238-1259
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• 2019

Saving energy is a big challenge for Wireless Sensor Networks (WSNs), which becomes even more critical in large-scale WSNs. Most energy waste is communication related, such as collision, overhearing and idle listening, so the schedule-based access which can avoid these wastes is preferred for WSNs. On the other hand, clustering technique is considered as the most promising solution for topology management in WSNs. Hence, providing interference-free clustering is vital for WSNs, especially for large-scale WSNs. However, schedule management in cluster-based networks is never a trivial work, since it requires inter-cluster cooperation. In this paper, we propose a clustering method, called Interference-Free Clustering Protocol (IFCP), to partition a WSN into interference-free clusters, making timeslot management much easier to achieve. Moreover, we model the clustering problem as a multi-objective optimization issue and use non-dominated sorting genetic algorithm II to solve it. Our proposal is finally compared with two adaptive clustering methods, HEED-CSMA and HEED-BMA, demonstrating that it achieves the good performance in terms of delay, packet delivery ratio, and energy consumption.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.975-983
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• 2022

This paper presents an innovative way of integrating scheduling and project controls with the environmental impact of a construction project to track, monitor, and manage environmental emissions at the activity level. As a starting point, scheduling and project controls help monitor the status of a project to provide an assessment of the duration and sequence of activities. Additionally, project schedules can also reflect resource allocation and costs associated with various phases of a construction project. Owners, contractors and construction managers closely monitor tasks or activities on the critical path(s) and/or longest path(s) calculated through network based scheduling techniques. However, existing industry practices do not take into account environmental impact associated with each activity during the life cycle of a project. Although the environmental impact of a project may be tracked in various ways, that tracking is not tied to the project schedule and, as such, generally is not updated when schedules are revised. In this research, a Cradle to Gate approach is used to estimate environmental emissions associated with each activity of a sample project schedule. The research group has also investigated the potential determination of scenarios of lowest environmental emissions, just as project managers currently determine scenarios with lowest cost or time. This methodology can be scaled up for future work to develop a library of unit emissions associated with commonly used construction materials and equipment. This will be helpful for project owners, contractors, and construction managers to monitor, manage, and reduce the carbon footprint associated with various projects.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.3B
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• pp.189-203
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• 2012

In cognitive radio networks, a secondary user opportunistically accesses an empty channel based on periodic sensing results for avoiding possible interference to the primary users. However, local sensing does not guarantee the full protection of the primary users because hidden primary receivers may exist within the interference range of the secondary transmitter. To protect primary systems and simultaneously to maximize utilization of the secondary users, we need to derive carefully designed coexistence solutions for various network scenarios. In this paper, we propose coexistence conditions without any harmful interference in accordance with the uplink/downlink schedule and user position. We have classified the coexistence conditions into four different scenario cases depending on the provided information to the secondary network basestations. Computer simulation results demonstrated that the proposed method can be applied to the real cognitive radio system to improve the communication probability of CR devices.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.161-172
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• 2007

Vehicles transporting hazardous materials can make huge damage to people, properties and environment by traffic accidents. Therefore, transporting hazardous materials is a big issue with the cutting edge technology of communications in these days. However, despite this situation, Korean government gives limited efforts for systematic management, research and investment about hazardous materials. Accordingly, this research suggests the key path finding algorithm about management of real-time schedule and routes for vehicles transporting hazardous materials. Besides, the case study is progressed in transportation networks of Seoul in order to evaluate the reality of algorithm. Specifically, time-space network transformation is performed for time window attributes. In addition, this study proposes the techniques searching for non-dominated paths considering schedule by the multiobjective shortest path algorithm based on dynamic programming in dynamic transportation networks including multiobjective attributes.

• Journal of Korea Game Society
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• v.18 no.5
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• pp.83-92
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• 2018

Many studies in deep learning show results as good as human's decision in various fields. And importance of activation of online-community and SNS grows up in game industry. Even it decides whether a game can be successful or not. The purpose of this study is to construct a system which can read texts and create comments according to schedule in online-community and SNS using deep learning. Using recurrent neural network, we constructed models generating a comment and a schedule of writing comments, and made program choosing a news title and uploading the comment at twitter in calculated time automatically. This study can be applied to activating an online game community, a Q&A service, etc.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.127-139
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• 2023

Numerous genuine issues, for example, financial exchange expectation, climate determining and so forth has inalienable arbitrariness related with them. Receiving a probabilistic system for forecast can oblige this dubious connection among past and future. Commonly the interest is in the contingent likelihood thickness of the arbitrary variable included. One methodology for expectation is with time arrangement and auto relapse models. In this work, liner expectation technique and approach for computation of forecast coefficient are given and likelihood of blunder for various assessors is determined. The current methods all need in some regard assessing a boundary of some accepted arrangement. In this way, an elective methodology is proposed. The elective methodology is to gauge the restrictive thickness of the irregular variable included. The methodology proposed in this theory includes assessing the (discretized) restrictive thickness utilizing a Markovian definition when two arbitrary factors are genuinely needy, knowing the estimation of one of them allows us to improve gauge of the estimation of the other one. The restrictive thickness is assessed as the proportion of the two dimensional joint thickness to the one-dimensional thickness of irregular variable at whatever point the later is positive. Markov models are utilized in the issues of settling on an arrangement of choices and issue that have an innate transience that comprises of an interaction that unfurls on schedule on schedule. In the nonstop time Markov chain models the time stretches between two successive changes may likewise be a ceaseless irregular variable. The Markovian methodology is especially basic and quick for practically all classes of classes of issues requiring the assessment of contingent densities.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2198-2202
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• 2003

The data transmission of MVB(Multifunction Vehicle Bus) of TCN(Train Network Communication) is divided into the periodic transmission phase and the sporadic transmission phase. TCN standard defines the event-polling method for the message transfer in the sporadic phase. However, since the event-polling method does not use pre-scheduling to the priority of the messages to be transmitted, it is inefficient for the real-time systems. To schedule message transmission, a master node should know the priority of message to be transmitted by a slave node prior to the scheduling the sporadic phase, but the existing TCN standard does not support any protocol for this. This paper proposes the slave frame bit-stuffing algorithm, with which a master node gets the necessary information for transmission scheduling and includes the simulation results of the event-polling method and the proposed algorithm.

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.256-259
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• 2007

Multicast and Broadcast Service (MBS) provides flexible and efficient transmission of the same information to multiple users using shared radio resources on WiBro network. The advantage of this service is to achieve the most efficient use of radio and network resources as well as to lessen sender's processing load when sending the same information to multiple users. Though radio resources are saved since a multicast or broadcast transport connection is associated with a service flow, it is hard to change MBS service channel dynamically. In this paper, we propose a Radio Resource Management System (RRMS) for supporting dynamic scheduling of MBS service channels. Results show that our proposed scheme using Radio Resource Allocation Table (RRAT) can efficiently support MBS services by providing dynamic schedule for MBS service channels.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.5
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• pp.123-133
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• 1994

This paper presents an output arbitrator for input buffering ATM (Asynchronous Transfer Mode) switches using neural networks. To avoid blocking in ATM switches with blocking characteristics, it is required to buffer ATM cells in input buffer and to schedule them. The N$\times$N request matrix is divided into N/16 submatrices in order to get rid of internal blocking systematically in scheduling phase. The submatrices are grouped into N/4 groups, and the cells in each group are switched alternatively. As the window size of input buffer is increases, the number of input cells switched in a time slot approaches to N. The selection of nonblocking cells to be switched is done by neural network modules. N/4 neural network modules are operated simultaneously. Fast selection can be achieved by massive parallelism of neural networks. The neural networks have 4N neurons and 14N connection. The proposed method is implemented in C language, and the simulation result confirms the feasibility of this method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.593-594
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• 2015

In wireless sensor networks (WSNs), due to the very low data rate, the sleeping schedule is usually used to save consumed energy and prolong the lifetime of nodes. However, duty-cycled approach can cause a high end-to-end (E2E) delay. In this paper, we study a node scheduling algorithm in WSNs such that E2E delay meets bounded delay with a given probability. We have applied the probability theory to spot the relationship between E2E delay and node interval. Simulation result illustrates that we can create the network to achieve given delay with prior probability and high energy use efficient as well.