• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3584-3602
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• 2022

NFV realizes flexible and rapid software deployment and management of network functions in the cloud network, and provides network services in the form of chained virtual network functions (VNFs). However, using VNFs to provide quality guaranteed services is still a challenge because of the inherent difficulty in intelligently scaling VNFs to handle traffic fluctuations. Most existing works scale VNFs with fixed-capacity instances, that is they take instances of the same size and determine a suitable deployment location without considering the cloud network resource distribution. This paper proposes a traffic forecasted assisted proactive VNF scaling approach, and it adopts the instance capacity adaptive to the node resource. We first model the VNF scaling as integer quadratic programming and then propose a proactive adaptive VNF scaling (PAVS) approach. The approach employs an efficient traffic forecasting method based on LSTM to predict the upcoming traffic demands. With the obtained traffic demands, we design a resource-aware new VNF instance deployment algorithm to scale out under-provisioning VNFs and a redundant VNF instance management mechanism to scale in over-provisioning VNFs. Trace-driven simulation demonstrates that our proposed approach can respond to traffic fluctuation in advance and reduce the total cost significantly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2492-2512
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• 2018

Multicast communication can effectively reduce network resources consumption in contrast with unicast. With the advent of SDN, current researches on multicast traffic are mainly conducted in the SDN scenario, thus to mitigate the problems of IP multicast such as the unavoidable difficulty in traffic engineering and high security risk. However, migration to SDN cannot be achieved in one step, hybrid SDN emerges as a transitional networking form for ISP network. In hybrid SDN, for acquiring similar TE and security performance as in SDN multicast, we redirect every multicast traffic to an appropriate SDN node before reaching the destinations of the multicast group, thus to build up a core-based multicast tree substantially which is first introduced in CBT. Based on the core SDN node, it is possible to realize dynamic control over the routing paths to benefit traffic engineering (TE), while multicast traffic manageability can also be obtained, e.g., access control and middlebox-supported network services. On top of that, multiple core-based multicast trees are constructed for each multicast group by fully taking advantage of the routing flexibility of SDN nodes, in order to further enhance the TE performance. The multicast routing and splitting (MRS) algorithm is proposed whereby we jointly and efficiently determine an appropriate core SDN node for each group, as well as optimizing the traffic splitting fractions for the corresponding multiple core-based trees to minimize the maximum link utilization. We conduct simulations with different SDN deployment rate in real network topologies. The results indicate that, when 40% of the SDN switches are deployed in HSDN as well as calculating 2 trees for each group, HSDN multicast adopting MRS algorithm can obtain a comparable TE performance to SDN multicast.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06a
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• pp.282-283
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• 2007

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1084-1090
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• 2015

In this paper, we propose a Tabu search algorithm to efficiently deploy the sensor nodes for maximizing the network sensing coverage in wireless sensor networks. As the number of the sensor nodes in wireless sensor networks increases, the amount of calculation for searching the solution would be too much increased. To obtain the best solution within a reasonable execution time in a high-density network, we propose a Tabu search algorithm to maximize the network sensing coverage. In order to search effectively, we propose some efficient neighborhood generating operations of the Tabu search algorithm. We evaluate those performances through some experiments in terms of the maximum network sensing coverage and the execution time of the proposed algorithm. The comparison results show that the proposed algorithm outperforms other existing algorithms.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.2
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• pp.220-226
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• 2013

Recently, with the rapid development of factory automation and logistics system, a few workers were able to manage the broad workplace such as large vessels and warehouse. To estimate the exact location of these workers in the conventional wireless indoor localization systems, three or more fixed nodes are generally used to recognize the location of a mobile node consisting of a single node. However, these methods are inefficient in terms of node deployment because the broad workplace requires a lot of fixed nodes compared to workers(mobile nodes). Therefore, to efficiently deploy fixed nodes in these environments that need a few workers, this paper presents a novel estimation algorithm which can reduce the number of fixed nodes by efficiently recognizing the relative coordinates of two fixed nodes through a mobile node composed of three nodes. Also, to minimize the distance errors between mobile node and fixed node, rounding estimation(RE) technique is proposed. Experimental results show that the error rate of localization is improved, by using proposed RE technique, 90.9% compared to conventional trilateration in the free space. In addition, despite the number of fixed nodes can be reduced by up to 50% in the indoor free space, the proposed estimation algorithm recognizes precise location which has average error of 0.15m.

• Journal of Information Technology Services
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• v.19 no.3
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• pp.139-149
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• 2020

There are now many different commercial weather sensors suitable for smart farms, and various smart farm devices are being developed and distributed by companies participating in the government-led smart farm expansion project. However, most do not comply with standard specifications and are therefore limited to use in smart farms. This paper proposed the connecting structure of operating non-standard node devices in smart farms following standard specifications supporting smart greenhouse. This connecting structure was proposed as both a virtual node module method and a virtual node wrapper method. In addition, the SoftFarm2.0 system was experimentally operated to analyze the performance of the implementation of the two methods. SoftFarm2.0 system complies with the standard specifications and supports non-standard smart farm devices. According to the analysis results, both methods do not significantly affect performance in the operation of the smart farm. Therefore, it would be good to select and implement the method suitable for each non-standard smart farm device considering environmental constraints such as power, space, distance of communication between the gateway and the node of the smart farm, and software openness. This will greatly contribute to the spread of smart farms by maximizing deployment cost savings.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4971-4987
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• 2019

Node localization is the basic task of underwater wireless sensor networks (UWSNs). Most of the existing underwater localization methods rely on ranging accuracy. Due to the special environment conditions in the ocean, beacon nodes are difficult to deploy accurately. The narrow bandwidth and high delay of the underwater acoustic communication channel lead to large errors. In order to reduce the ranging error and improve the positioning accuracy, we propose a localization algorithm based on ranging correction and inertial coordination. The algorithm can be divided into two parts, Range Correction based Localization algorithm (RCL) and Inertial Coordination based Localization algorithm (ICL). RCL uses the geometric relationship between the node positions to correct the ranging error and obtain the exact node position. However, when the unknown node deviates from the deployment area with the movement of the water flow, it cannot communicate with enough beacon nodes in a certain period of time. In this case, the node uses ICL algorithm to combine position data with motion information of neighbor nodes to update its position. The simulation results show that the proposed algorithm greatly improves the positioning accuracy of unknown nodes compared with the existing localization methods.

• Journal of KIISE:Information Networking
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• v.31 no.4
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• pp.384-392
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• 2004

Mobile contents service providers have some difficulties to timely and proper service deployment due to rapid development cycle of diverse portable devices with different capabilities. A way to resolve the problem is to introduce a mobile contents service paltform that can adapt original mobile contents to diverse devices dynamically and automatically. In this paper, we propose a mobile contents service platform based on active network mechanisms, called Mobile Content Adaptation Network(MobiCAN). The MobiCAN node provides effective service deployment, execution, and maintenance features and accommodates service layering and service customization capabilities for easy deployment. The basic functional units of the MobiCAN node are micro services with well-defined service interfaces and service layering features. For reliable services among the MobiCAN nodes, we design new distributed and robust Overlay Management Protocols(OMPs). As an example of practical MobiCAN applications, we finally describe Dynamic Contents Customization Proxy(DCCP) service.

• Journal of the Korean Geographical Society
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• v.45 no.6
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• pp.788-805
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• 2010

The present USN (Ubiquitous Sensor Networks) node deployment practices have many limitations in terms of positional connectivity. The aim of this research was to minimize a redundancy of USN route nodes, by integrating spatially weighted parameters such as visibility, proximity to cell center, road density, building density and cell overlapping ratio into a comprehensive GIS database. This spatially weighted approach made it possible to reduce the number of route nodes (11) required in the study site as compared to that of the grid network method (24). The field test for RSSI (Received Signal Strength Indicator) indicates that the spatially weighted deployment could comply with the quality assurance standard for node connectivity, and that reduced route nodes do not show a significant degree of signal fluctuation for different site conditions. This study demonstrated that the spatially weighted deployment can be used to minimize a redundancy of USN route nodes in a routine manner, and the quantitative evidence removing a redundancy of USN route nodes could be utilized as major tools to ensure the strong signal in the USN, that is frequently encountered in real applications.

• Journal of information and communication convergence engineering
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• v.18 no.3
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• pp.183-187
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• 2020

The general Wi-Fi network connection structure is that a number of IoT (Internet of Things) sensor nodes are directly connected to one AP (Access Point) node. In this structure, the range of the network that can be established within the specified specifications such as the range of signal strength (RSSI) to which the AP node can connect and the maximum connection capacity is limited. To overcome these limitations, multiple middleware bridge technologies for dynamic scalability and load balancing were studied. However, these network expansion technologies have difficulties in terms of the rules and conditions of AP nodes installed during the initial network deployment phase In this paper, an intelligent edge computing IoT device is developed for constructing an intelligent autonomous cluster edge computing network and applying it to real-time road danger context aware and notification system through an intelligent risk situation recognition algorithm.