• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.9
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• pp.1799-1805
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• 2007

Wireless Ad-hoc networks may contain nodes of various types of which many can have limited power capabilities. A failure of a node due to energy exhaustion may impact the performance of the whole network hence, energy must be conserved. In this paper, we propose a Delay and Energy-Aware Routing (DEAR) algorithm a multiple metric path cost routing algorithm which considers not only the energy consumed by the node during transmission and reception but as well as the residual energy of the node and the delay incurred during route discovery. Based on our results, DEAR algorithm performs well and maximizes network lifetime by routing flows to nodes with sufficient energy such that the energy consumption is balanced among nodes in proportion to their energy reserves.

• ETRI Journal
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• v.43 no.4
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• pp.674-683
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• 2021

A trust-aware secure routing protocol (TSRP) for wireless sensor networks is proposed in this paper to defend against varieties of attacks. First, each node calculates the comprehensive trust values of its neighbors based on direct trust value, indirect trust value, volatilization factor, and residual energy to defend against black hole, selective forwarding, wormhole, hello flood, and sinkhole attacks. Second, any source node that needs to send data forwards a routing request packet to its neighbors in multi-path mode, and this continues until the sink at the end is reached. Finally, the sink finds the optimal path based on the path's comprehensive trust values, transmission distance, and hop count by analyzing the received packets. Simulation results show that TSRP has lower network latency, smaller packet loss rate, and lower average network energy consumption than ad hoc on-demand distance vector routing and trust based secure routing protocol.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.301-307
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• 2022

Energy consumption has grown alongside dramatic population increases. Statistics show that buildings in particular utilize a significant amount of energy, worldwide. Because of this, building energy prediction is crucial to best optimize utilities' energy plans and also create a predictive model for consumers. To improve energy prediction performance, this paper proposes a ResNet-LSTM model that combines residual networks (ResNets) and long short-term memory (LSTM) for energy consumption prediction. ResNets are utilized to extract complex and rich features, while LSTM has the ability to learn temporal correlation; the dense layer is used as a regression to forecast energy consumption. To make our model more robust, we employed Huber loss during the optimization process. Huber loss obtains high efficiency by handling minor errors quadratically. It also takes the absolute error for large errors to increase robustness. This makes our model less sensitive to outlier data. Our proposed system was trained on historical data to forecast energy consumption for different time series. To evaluate our proposed model, we compared our model's performance with several popular machine learning and deep learning methods such as linear regression, neural networks, decision tree, and convolutional neural networks, etc. The results show that our proposed model predicted energy consumption most accurately.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.413-435
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• 2018

Although the accuracy of handwritten character recognition based on deep networks has been shown to be superior to that of the traditional method, the use of an overly deep network significantly increases time consumption during parameter training. For this reason, this paper took the training time and recognition accuracy into consideration and proposed a novel handwritten character recognition algorithm with newly designed network structure, which is based on an extended nonlinear kernel residual network. This network is a non-extremely deep network, and its main design is as follows:(1) Design of an unsupervised apriori algorithm for intra-class clustering, making the subsequent network training more pertinent; (2) presentation of an intermediate convolution model with a pre-processed width level of 2;(3) presentation of a composite residual structure that designs a multi-level quick link; and (4) addition of a Dropout layer after the parameter optimization. The algorithm shows superior results on MNIST and SVHN dataset, which are two character benchmark recognition datasets, and achieves better recognition accuracy and higher recognition efficiency than other deep structures with the same number of layers.

• The KIPS Transactions:PartC
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• v.15C no.4
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• pp.289-296
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• 2008

In wireless mesh network, studies on routing protocols have been actively carried out recently, and hop count is used as a major routing metric in destination-sequenced distance-vector (DSDV) routing protocol, which is a representative proactive routing protocol. Although hop-by-hop multi-path (HMP) DSDV and enhanced HMP (EHMP) DSDV routing protocols perform routing by considering both hop count and residual bandwidth within one hop distance nodes, it has a shortcoming that routing is carried out via non-optimal path from the aspect of end-to-end routing. In order to overcome the shortcoming, a cost-aware multi-path (CAMP) DSDV routing protocol is proposed in this paper, which considers hop count and end-to-end minimum residual bandwidth. Simulation results based on NS-2 show that the proposed routing protocol performs better than DSDV, HMP DSDV, and EHMP DSDV protocols from the aspect of throughput and packet delivery ratio, by appropriately using hop count and end-to-end minimum residual bandwidth information and has the same number of management messages with HMP DSDV and EHMP DSDV protocols.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.247-255
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• 2011

Most existing clustering protocols have been aimed to provide balancing the residual energy of each node and maximizing life-time of wireless sensor networks. In this paper, we present the adaptive clustering strategy related to sink position for clustering protocols in wireless sensor networks. This protocol allows networks topology to be adaptive to the change of the sink position by using symmetrical clustering strategy that restricts the growth of clusters based on depth of the tree. In addition, it also guarantees each cluster the equal life-time, which may be extended compared with the existing clustering protocols. We evaluated the performance of our clustering scheme comparing to LEACH and EEUC, and observe that our protocol is observed to outperform existing protocols in terms of energy consumption and longevity of the network.

• Journal of Korea Water Resources Association
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• v.39 no.1 s.162
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• pp.35-46
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• 2006

In this study, we proposed a layout of the integrated decision support system in order to prevent the contamination and to manage risk in water supply networks for safe and smooth water supply. We evaluated the priority of risk factors to detect anomaly in water supply networks using PROMETHEE and ANP techniques, which are applied to various Multi-Criteria Decision Making area in Europe and America. To develop the model, we selected pH, residual chlorine concentration, discharge, hydraulic pressure, electrical conductivity, turbidity, block leakage and water temperature as the key data item. We also chose pipe corrosion, pipe burst and water pollution in pipe as the criteria and then we present the results of PROMETHEE and ANP analysis. The evaluation results of the priority of risk factors in water supply networks will provide basic data to establish a contingency plan for accidents so that we can establish the specific emergency response procedures.

• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.117-121
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• 2008

In ad hoc network, the scarce energy management of the mobile devices has become a critical issue in order to extend the network lifetime. Therefore, the energy consumption is important in the routing design, otherwise cluster schemes are efficient in energy conserving. For the above reasons, an Energy conserving Context aware Clustering algorithm (ECC) is proposed to establish the network clustering structure, and a routing algorithm is introduced to choose the Optimal Energy Routing Protocol (OERP) path in this paper. Because in ad hoc network, the topology, nodes residual energy and energy consuming rate are dynamic changing. The network system should react continuously and rapidly to the changing conditions, and make corresponding action according different conditions. So we use the context aware computing to actualize the cluster head node, the routing path choosing. In this paper, we consider a novel routing protocol using the cluster schemes to find the optimal energy routing path based on a special topology structure of Resilient Ontology Multicasting Routing Protocol (RODMRP). The RODMRP is one of the hierarchical ad hoc network structure which combines the advantage of the tree based and the mesh based network. This scheme divides the nodes in different level found on the node energy condition, and the clustering is established based on the levels. This protocol considered the residual energy of the nodes and the total consuming energy ratio on the routing path to get the energy efficiently routing. The proposed networks scheme could get better improve the awareness for data to achieve and performance on their clustering establishment and messages transmission. Also, by using the context aware computing, according to the condition and the rules defined, the sensor nodes could adjust their behaviors correspondingly to improve the network routing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.5B
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• pp.274-286
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• 2005

In this paper, we propose a new power-efficient and reliable connected dominating set based routing protocol in the mobile ad hoc networks. Gateway nodes must be elected in consideration of residual energy and mobility because frequent reconstruction of connected dominating set result in transmission error for route losses. If node density is high, it results in a lot of contentions and more delays for network congestion. Therefore, in this paper, we propose a new construction method of connected dominating set that supports reliable and efficient data transmission through minimizing reconstruction of connected dominating set by delaying neighbor set advertisement message broadcast in proportion to weighted sum of residual energy, mobility, and the number of neighbor nodes. The performance of the proposed protocol is proved by simulation of various conditions.

• Journal of Communications and Networks
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• v.14 no.4
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• pp.434-442
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• 2012

Several gateway selection schemes have been proposed that select gateway nodes based on a single Quality of Service (QoS) path parameter, for instance path availability period, link capacity or end-to-end delay, etc. or on multiple non-QoS parameters, for instance the combination of gateway node speed, residual energy, and number of hops, for Mobile Ad hoc NETworks (MANETs). Each scheme just focuses on the ment of improve only a single network performance, i.e., network throughput, packet delivery ratio, end-to-end delay, or packet drop ratio. However, none of these schemes improves the overall network performance because they focus on a single QoS path parameter or on set of non-QoS parameters. To improve the overall network performance, it is necessary to select a gateway with stable path, a path with themaximum residual load capacity and the minimum latency. In this paper, we propose a gateway selection scheme that considers multiple QoS path parameters such as path availability period, available capacity and latency, to select a potential gateway node. We improve the path availability computation accuracy, we introduce a feedback system to updated path dynamics to the traffic source node and we propose an efficient method to propagate QoS parameters in our scheme. Computer simulations show that our gateway selection scheme improves throughput and packet delivery ratio with less per node energy consumption. It also improves the end-to-end delay compared to single QoS path parameter gateway selection schemes. In addition, we simulate the proposed scheme by considering weighting factors to gateway selection parameters and results show that the weighting factors improve the throughput and end-to-end delay compared to the conventional schemes.