• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1133-1151
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• 2010

Energy balanced consumption routing is based on assumption that the nodes consume energy both in transmitting and receiving. Lopsided energy consumption is an intrinsic problem in low-cost sensor networks characterized by multihop routing and in many traffic overhead pattern networks, and this irregular energy dissipation can significantly reduce network lifetime. In this paper, we study the problem of maximizing network lifetime through balancing energy consumption for uniformly deployed low-cost sensor networks. We formulate the energy consumption balancing problem as an optimal balancing data transmitting problem by combining the ideas of corona cluster based network division and optimized transmitting state routing strategy together with data transmission. We propose a localized cluster based routing scheme that guarantees balanced energy consumption among clusters within each corona. We develop a new energy cluster based routing protocol called "OECR". We design an offline centralized algorithm with time complexity O (log n) (n is the number of clusters) to solve the transmitting data distribution problem aimed at energy balancing consumption among nodes in different cluster. An approach for computing the optimal number of clusters to maximize the network lifetime is also presented. Based on the mathematical model, an optimized energy cluster routing (OECR) is designed and the solution for extending OEDR to low-cost sensor networks is also presented. Simulation results demonstrate that the proposed routing scheme significantly outperforms conventional energy routing schemes in terms of network lifetime.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.51-56
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• 2022

In space based constellation network, users are allowed to enter or leave the network arbitrarily. Hence, the number, identities and transmitted data of active users vary with time and have considerable impacts on the receiver's performance. The so-called problem of multiuser detection means identifying the identity of each active user and detecting the data transmitted by each active user. Traditional methods assume that the number of active users is equal to the maximum number of users that the network can hold. The model of traditional methods are simple and the performance are suboptimal. In this paper a Maximum A Posteriori Probability (MAP) based multiuser detection method is proposed. The proposed method models the activity state of users as Markov chain and transforms multiuser detection into searching optimal path in grid map with BCJR algorithm. Simulation results indicate that the proposed method obtains 2.6dB and 1dB E_b/N₀ gains respectively when activity detection error rate and symbol error rate reach 10^-3, comparing with reference methods.

• Journal of applied mathematics & informatics
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• v.41 no.4
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• pp.861-868
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• 2023

Nonlinear network creates complex homotopy structural communication in wireless network medium because of complex distribution approach. Due to this multicast topological connection structure, the queuing probability was non regular principles to create routing structures. To resolve this problem, we propose a Co-cluster homotopy queuing model (Co-CHQT) for Nonlinear Algebraic Topological Structure (NLTS-) for improving poison distribution network communication. Initially this collects the routing propagation based on Nonlinear Distance Theory (NLDT) to estimate the nearest neighbor network nodes undernon linear at x_(a,b)→ax²+bx² = c. Then Quillen Network Decomposition Theorem (QNDT) was applied to sustain the non-regular routing propagation to create cluster path. Each cluster be form with co variance structure based on Two unicast 2(n+1)-Z2(n+1)-Z network. Based on the poison distribution theory X_(a,b) ≠ µ(C), at number of distribution routing strategies weights are estimated based on node response rate. Deriving shorte;'l/st path from behavioral of the node response, Hilbert -Krylov subspace clustering estimates the Cluster Head (CH) to the routing head. This solves the approximation routing strategy from the nonlinear communication depending on Max- equivalence theory (Max-T). This proposed system improves communication to construction topological cluster based on optimized level to produce better performance in distance theory, throughput latency in non-variation delay tolerant.

• Knowledge Management Research
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• v.12 no.2
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• pp.69-80
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• 2011

This paper reports on a structural view of a knowledge network comprised of clubs and organisationsexpressly concerned with cultural activities in a regional Australian city. Social network analysis showed an uneven distribution of power, influence, and prominence in the network. The network structure consisted of two modules of vertices clustered around particular categories of creative arts and these modules were linked most frequently by several organisations acting as communication hubs and boundary spanners. The implications of the findings include 'network weaving' for improving the network structure and developing a systemic approach for exploring the structures of social action that form community-based knowledge networks.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.78-80
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• 2009

In this paper, we have described the advantages of fixed mobile convergence access network based on FTTH. Also, we have investigated the possibility of mobile backhaul based on FTTH network combined TOM over IP emulation and adaptive clock recovery technologies, and verified successful transport of both E1 TDM traffic and Clock through the packet based PON network. within the allowable tolerance.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.53-63
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• 2022

In the paper, we propose a TSCH-based scheduling scheme for IEEE 802.15.4e, which is able to perform the scheduling of its own network by avoiding collision from interference network cluster (INC). Firstly, we model a bipartite graph structure for presenting the slot-frame (channel-slot assignment) of TSCH. Then, based on the bipartite graph edge weight, we utilize the Hungarian assignment algorithm to implement a scheduling scheme. We have employed two features (maximization and minimization) of the Hungarian-based assignment algorithm, which can perform the assignment in terms of minimizing the throughput of INC and maximizing the throughput of own network. Further, in this work, we called the scheme "dual-stage Hungarian-based assignment algorithm". Furthermore, we also propose deep learning (DL) based deep neural network (DNN)scheme, where the data were generated by the dual-stage Hungarian-based assignment algorithm. The performance of the DNN scheme is evaluated by simulations. The simulation results prove that the proposed DNN scheme providessimilar performance to the dual-stage Hungarian-based assignment algorithm while providing a low execution time.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.3
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• pp.246-256
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• 2020

In the future Network Centric Warfare(NCW), changing to IPv6 based network environment is required to enable various future technologies such as the Internet of Things(IoT) and cloud technology which are expected to be introduced to the tactical network evolution. With the change to the IPv6 network, an ID/LOC(Identifier/Location) separation protocol that decomposes context of the IP address to location and identifier can enhance network capacity of increasing number of device and provide efficient mobility management in the tactical network that changes topology dynamically. In this paper, we choose ILNP(Identifier-Locator Network Protocol) as an ID/LOC separation for tactical network environment. In addition to ILNP-based tactical network design, this paper proposes a network-based mobility management scheme for providing efficient mobility management. Through numerical performance analysis, we show that the proposed scheme can reduce network loads more effectively than the conventional IP-based mobility management scheme and common handover procedure in ILNP.

• Management & Information Systems Review
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• v.32 no.5
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• pp.193-231
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• 2013

As developed IT, Word-of-Mouth(WOM) used varied terms as buzz marketing and viral marketing, and impressed that importance. Despite introduced new marketing tool on managers and professionals, online word-of-mouth including SNS lack of study on social network what based viral in marketing. In social network, patterns of relationship between individuals influence each other individual behaviors. Therefore this research grouped friendship-network and advice-network by characteristics, studied on trust of information source that antecedents of word-of-mouth in network. This study examined that affect- and cognition based trust affect WOM acceptance as WOM behaviors and examined effect of type of product as moderating variable. Additional this literature studied that WOM acceptance affect WOM recommend. To find the Influence of Trust on Word-of-Mouth Behaviors, a survey has done 206 samples(undergraduate students). The results of this study are as following : First, type of trust different friendship network and advice network. Affect-based trust is outstanding in friendship network than in advice network, while cognition-based trust stands out in advice network than another. Second, affect- and cognition based trust positive affect WOM acceptance. Contrary to expectations, what is preconceived trust in network have a similar effect for WOM acceptance regardless of type of trust. Third, WOM acceptance positive affect WOM recommend. Fourth, affect based trust affect WOM acceptance of hedonic product rather than utilitarian product. Upon especially in friendship network terms, affect-based trust has a more effect on WOM acceptance than cognition-based trust. This study has many implications. First, it is important that trust what have an influence WOM acceptance grouped affect- and cognition based trust. Second, it confirmed that trust is antecedents of positive WOM. Third, it is important that network grouped friendship network and advice-network by trust. Fourth, it gave managerial implications that they have to supply WOM through which network by type of product. We This study classified network and trust based on previous study. Then it examined relations between WOM behaviors. Further research could do enrich various things for example various age group, valence of message, quality of information.

• Proceedings of the Korea Society for Simulation Conference
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• 2003.11a
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• pp.139-144
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• 2003

Mobile Node has to maintain communication as they move form place to place, so it doesn't guarantee Quality of Service(QoS). Fast Handoff is important to provide multimedia and real-time applications services in mobile, and it is closely related to handoff delay. Therefore, handoff delay problem is actively studied to quarantee QoS as a main issue in mobile IP research area. Next generation Mobile IPv6 resolve this problem somewhat, triangle problem for first packet and handoff delay still remain. In this paper, we suggest SNMP Information-based routing that adds keyword management method to Information-based routing in active network in order to resolve such a problem, and then suggest QoS controlled handoff based on SNMP Information-Based routing. After modeling of suggested method and existing handoff method, simulations are carried out with NS-2 for performance evaluation. The results of simulations show the some improvement on handoff delay, and therefore on QoS improvement.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.127-136
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• 2023

Many research results on the traffic enforcement of illegal driving of twowheeled motor vehicles using license plate recognition are introduced. Deep learning convolutional neural networks can be used for character and word recognition of license plates because of better generalization capability compared to traditional Backpropagation neural networks. In the plates of twowheeled motor vehicles, the interdependent government and city words are included. If we implement the mutually independent word recognizers using error correction rules for two word recognition results, efficient license plate recognition results can be derived. The CPU based convolutional neural network without library under real time processing has an advantage of low cost real application compared to GPU based convolutional neural network with library. In this paper twowheeled motor vehicle license plate recognition algorithm is introduced using CPU based deep-learning convolutional neural network. The experimental results show that the proposed plate recognizer has 96.2% success rate for outdoor twowheeled motor vehicle images in real time.