• Journal of the Korea Institute of Building Construction
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• v.18 no.6
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• pp.595-602
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• 2018

Network-based scheduling methods can be classified into CPM method and PERT method. In the network scheduling chart, critical path can be estimated by performing the forward calculation and the backward calculation though the paths in the network chart. In PERT method, however, it is unreasonable to simply estimate the critical path by adding the sum of the activity durations in a specific path, since it does not incorporate probabilistic concept of PERT. The critical path of a PERT network can change according to the target period and deviation, and in some cases, the expected time of the critical path may not be the path with longest expected time. Based on this concept, this study proposes a technique to derive the most-likely critical path by comparing the sum of estimated time with the target time. It also proposes a method of systematically deriving all alternate paths for a network of repetitive activities. Case studies demonstrated that the most-likely critical path is not a fixed path and may vary according to the target period and standard deviation. It is expected that the proposed method of project duration forecasting will be useful in construction environment with varying target date situations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.141-150
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• 2012

This paper suggests a critical path search algorithm that can easily draw PERT/GANTT chart which manages and plans a project schedule. In order to evaluate a critical path that determines the project schedule, Critical Path Method (CPM) is generally utilized. However, CPM undergoes 5 stages to calculate the critical path for a network diagram that is previously designed according to correlative relationship and execution period of project execution activities. And it may not correctly evaluate $T_E$ (The Earliest Time), since it does not suggest the way how to determine the sequence of the nodes activities that calculate the $T_E$. Also, the sequence of the network diagram activities obtained from CPM cannot be visually represented, and hence Lucko suggested an algorithm which undergoes 9 stages. On the other hand, the suggested algorithm, first of all, decides the sequence in advance, by reallocating the nodes into levels after Breadth-First Search of the network diagram that is previously designed. Next, it randomly chooses nodes of each level and immediately determines the critical path only after calculation of $T_E$. Finally, it enables the representation of the execution sequence of the project activity to be seen precisely visual by means of a small movement of $T_E$ of the nodes that are not belonging to the critical path, on basis of the $T_E$ of the nodes which belong to the critical path. The suggested algorithm has been proved its applicability to 10 real project data. It is able to get the critical path from all the projects, and precisely and visually represented the execution sequence of the activities. Also, this has advantages of, firstly, reducing 5 stages of CPM into 1, simplifying Lucko's 9 stages into 2 stages that are used to clearly express the execution sequence of the activities, and directly converting the representation into PERT/GANTT chart.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.29A no.9
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• pp.85-93
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• 1992

In this paper, the new timing optimization algorithm for combinational networks is proposed. First, we introduce the concept of P-path redundancy which is the extension of redundancy concept used in the testing of combinational networks. In this approach, the critical delay is minimized by removing the P-path redundant side inputs of the critical path, and more accurate timing optimization is possible by systematically considering the statically unsensitizable paths as well as the statically sensitizable paths. It's possible with all previous longest path based approaches that the critical delay of resulting network after timing optimization may be even increased. However, the proposed method guarantees to exclude such a possibility, and can be applied to optimize the timing of combinational networks in technology independent, and dependent phase.

• Bulletin of the Society of Naval Architects of Korea
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• v.3 no.1
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• pp.46-54
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• 1966

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.677-687
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• 2001

The critical path has been widely applied to many areas of computer engineering especially a directed acyclic graph. Its concept can also be useful in the context of a workflow. The workflow critical path is defined as a path which has the longest average execution time from the start activity to the end activity of workflow. Because there can be several concurrently executed workflow instances for a specific workflow a new method to determine the critical path should be developed. In this paper we specify our workflow queuing network model from which we can easily analyze many workflow characteristics. Based on this workflow model. we propose a method to identify the critical path In addition, we show come workflow areas which can utilze the critical path.

• Journal of KIISE:Databases
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• v.29 no.2
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• pp.138-147
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• 2002

The concept of the critical path in the workflow is important because it can be utilized In many issues in workflow systems, e.g., workflow resource management and workflow time management. However, the critical path in the contest of the workflow has not been much addressed in the past. This is because control flows in the workflow, generally including sequence, parallel, alternative, iteration and so on, are much more complex than those in the ordinary graph or network. In this paper we first describe our workflow model that has considerable work(low control constructs. They would provide the sufficient expressive power for modeling the growing complexities of today's most business processes. Then, we propose a method to systematically determine the critical path in a workflow schema built by the workflow control constructs described in our workflow model.

• Journal of the Korea Institute of Building Construction
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• v.12 no.6
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• pp.558-565
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• 2012

Schedule management of construction work is critical to completing construction projects within a given period of time. Many efforts have been made and multiple tools have been developed to support the management of construction projects using smart devices such as smartphones and tablet PCs. This study proposed a method for managing construction schedules via a smart device using Flash. The interactive and graphic properties of Flash enable the development of an app that can allow a field manager to manage schedules easily and efficiently. A prototype was implemented using Adobe Flex Builder, and a sample network was applied in a smartphone. It is convenient for a construction manager to manage construction schedules using the tool because Flash controls graphic components easily. In further studies, network diagrams such as CPM (Critical Path Method) should be developed and applied to the app.

• Journal of Construction Engineering and Project Management
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• v.3 no.2
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• pp.21-34
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• 2013

Various risk factors affect construction projects. Due to the uncertainties created by risk factors, actual activity durations frequently deviate from the estimated durations in either favorable or adverse direction. For this reason, evaluation of schedule uncertainty is required to make decisions accurately when managing construction projects. In this regard, this paper presents a new computer simulation model - the Repetitive Schedule Risk Analysis Model (RSRAM) - to evaluate unit-based repetitive building project schedules under uncertainty when activity durations and risk factors are correlated. The proposed model utilizes Monte Carlo Simulation and a Critical Path Method based repetitive scheduling procedure. This new procedure concurrently provides the utilization of resources without interruption and the maintenance of network logic through successive units. Furthermore, it enables assigning variable production rates to the activities from one unit to another and any kind of relationship type with or without lag time. Details of the model are described and an example application is presented. The findings show that the model produces realistic results regarding the extent of uncertainty inherent in the schedule.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.389-395
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• 2022

A Mobile Sensor Network is widely used in real time applications. A critical need in Mobile Sensor Network is to achieve energy efficiency during routing as the sensor nodes have scarce energy resource. The nodes' mobility in MWSN poses a challenge to design an energy efficient routing protocol. Clustering helps to achieve energy efficiency by reducing the organization complexity overhead of the network which is proportional to the number of nodes in the network. This paper proposes"EERA: Energy Efficient Routing Algorithm for Mobile Sensor Network" is divided into five phases. 1, Cluster Formation 2.Cluster head and Transmission head selection 3.Path Establishment / Route discovery and 4,Data Transmission. Experimental Analysis has been done and is found that the proposed method performs better than the existing method with respect to four parameters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.10
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• pp.2338-2356
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• 2013

In cognitive radio networks, acquiring the position information of the primary user is critical to the communication of the secondary user. Localization of primary users can help improve the efficiency with which the spectrum is reused, because the information can be used to avoid harmful interference to the network while simultaneity is exploited to improve the spectrum utilization. Despite its inherent inaccuracy, received signal strength based on range has been used as the standard tool for distance measurements in the location detection process. Most previous works have employed the path-loss propagation model with a fixed value of the path loss exponent. However, in actual environments, the path loss exponent for each channel is different. Moreover, due to the complexity of the radio channel, when the number of channel increases, a larger number of RSS measurements are needed, and this results in additional energy consumption. In this paper, to overcome this problem, we propose using the Bayesian compressive sensing method with a calibrated path loss exponent to improve the performance of the PU localization method.