Networks use relatively slow heartbeat mechanisms, usually in routing protocols, to detect failures when there is no hardware signaling to help out. The time to detect failures available in the existing protocols is no better than a second, which is far too long for some applications and represents a great deal of lost data at 10 Gigabit rates. We compare the convergence time of routing protocol applying Bidirectional Forwarding Detection (BFD) protocol in wired mesh network topology. This paper suggests the combinations of protocols improving fail-over performance. Through the performance analysis, we contribute to reduce convergence time when system is fail-over.

In wireless sensor networks, the transmission success ratio would be decreased when the scale of the WSNs increased. To defeat this problem, we propose a multipath routing based on opportunistic routing for improving end-to-end reliability in large-scale wireless sensor networks. The proposed scheme exploits the advantages of existing opportunistic routing and achieves high end-to-end success ratio by branching like a multipath routing through local decision without information of the whole network. As a result of the simulation result, the proposed scheme shows a similar or higher end-to-end transmission success ratio and less energy consumption rather than the existing scheme.

In the fourth industrial revolution era, various commercial smart platforms for smart system implementation are being developed and serviced. However, since most of the smart platforms have been developed for general purposes, they are difficult to apply / utilize because they cannot satisfy the requirements of real-time data management, data visualization and data storage of smart factory system. In this paper, we implemented an open source based smart manufacturing big data platform that can manage highly efficient / reliable data integration for the diagnosis diagnostic system of manufacturing robots.

In this paper, an efficient single dehazing algorithm is proposed based on linear transformation by assuming that a linear relationship exists in saturation component between the haze image and haze-free image. First, we analyze the linearity of saturation channel, estimate the medium transmission map in terms of the saturation component. Then, the intensity of haze-free image is assumed by using CLAHE to enhance contrast of haze image. Experimental results demonstrate that proposed algorithm can naturally recover the image, especially can remove color distortion caused by conventional methods. Therefore, our approach is competitive with other state-of-the art single dehazing methods.

The purpose of this study is to develop a model that can systematically study the whole learning process of machine learning. Since the existing model describes the learning process with minimum coding, it can learn the progress of machine learning sequentially through the new model, and can visualize each process using the tensor flow. The new model used all of the existing model algorithms and confirmed the importance of the variables that affect the target variable, survival. The used to classification training data into training and verification, and to evaluate the performance of the model with test data. As a result of the final analysis, the ensemble techniques is the all tutorial model showed high performance, and the maximum performance of the model was improved by maximum 5.2% when compared with the existing model using. In future research, it is necessary to construct an environment in which machine learning can be learned regardless of the data preprocessing method and OS that can learn a model that is better than the existing performance.

One of the most widely studied protocols for tactical ad-hoc networks is Optimized Link State Routing Protocol (OLSR). As for OLSR research, most research work focus on reducing control traffic overhead and choosing relay point. In addition, because OLSR is mostly dependent on link detection and propagation, dynamic Hello timer become research challenges. However, different timer interval causes imbalance of link validity time by affecting link lifetime. To solve this problem, we propose a weighted topology graph model for constructing a robust network topology based on the link validity time. In order to calculate the link validity time, we use control message timer, which is set for each node. The simulation results show that the proposed mechanism is able to achieve high end-to-end reliability and low end-to-end delay in small networks.