• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.872-885
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• 2015

The rapid increase of smart mobile devices and mobile applications has led to explosive growth of data traffic in cellular network. Offloading data traffic becomes one of the most urgent technical problems. Recent work has proposed to exploit opportunistic communications to offload cellular traffic for mobile data dissemination services, especially for accepting large delayed data. The basic idea is to deliver the data to only part of subscribers (called target-nodes) via the cellular network, and allow target-nodes to disseminate the data through opportunistic communications. Human mobility shows temporal and spatial characteristics and predictability, which can be used as effective guidance efficient opportunistic communication. Therefore, based on the regularity of human mobility we propose NodeRank algorithm which uses the encounter characteristics between nodes to choose target nodes. Different from the existing work which only using encounter frequency, NodeRank algorithm combined the contact time and inter-contact time meanwhile to ensure integrity and availability of message delivery. The simulation results based on real-world mobility traces show the performance advantages of NodeRank in offloading efficiency and network redundant copies.

• Annual Conference of KIPS
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• 2018.05a
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• pp.81-84
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• 2018

Recently, many researchers claim that mobile data offloading is a key solution to alleviating overloaded cellular traffic by dividing the overloaded traffic with femtocells, WiFi networks or users. In this paper, we propose an idea to select a group of users, known as VIPs, that is able to effectively transfer the data to others using Density-Based Spatial Clustering of Application with Noise, also known as DBSCAN algorithm. We conducted our experiments using NCCU real trace dataset. The results show that our proposed idea offload about 70~77% of the network with VIP set size of four, which is better than the compared methods.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.513-522
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• 2016

We propose a mechanism for monitoring load in quality of service (QoS)-enabled wireless networks and show how it can be used for network management as well as for dynamic pricing. Mobile network traffic, especially video, has grown exponentially over the last few years and it is anticipated that this trend will continue into the future. Driving factors include the availability of new affordable, smart devices, such as smart-phones and tablets, together with the expectation of high quality user experience for video as one would obtain at home. Although new technologies such as long term evolution (LTE) are expected to help satisfy this demand, the fact is that several other mechanisms will be needed to manage overload and congestion in the network. Therefore, the efficient management of the expected huge data traffic demands is critical if operators are to maintain acceptable service quality while making a profit. In the current work, we address this issue by first investigating how the network load can be accurately monitored and then we show how this load metric can then be used to provide creative pricing plans. In addition, we describe its applications to features like traffic offloading and user satisfaction tracking.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3916-3936
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• 2014

Smartphone applications like games, image processing, e-commerce and social networking are gaining exponential growth, with the ubiquity of cellular services. This demands increased computational power and storage from mobile devices with a sufficiently high bandwidth for mobile internet service. But mobile nodes are highly constrained in the processing and storage, along with the battery power, which further restrains their dependability. Adopting the unlimited storage and computing power offered by cloud servers, it is possible to overcome and turn these issues into a favorable opportunity for the growth of mobile cloud computing. As the mobile internet data traffic is predicted to grow at the rate of around 65 percent yearly, even advanced services like 3G and 4G for mobile communication will fail to accommodate such exponential growth of data. On the other hand, developers extend popular applications with high end graphics leading to smart phones, manufactured with multicore processors and graphics processing units making them unaffordable. Therefore, to address the need of resource constrained mobile nodes and bandwidth constrained cellular networks, the computations can be migrated to resourceful servers connected to cloud. The server now acts as a bridge that should enable the participating mobile nodes to offload their computations through Wi-Fi directly to the virtualized server. Our proposed model enables an on-demand service offloading with a decision support system that identifies the capabilities of the client's hardware and software resources in judging the requirements for offloading. Further, the node's location, context and security capabilities are estimated to facilitate adaptive migration.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.9
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• pp.263-272
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• 2023

Industrial Internet of Things (IIoT) is an important factor in increasing production efficiency in industrial sectors, along with data collection, exchange and analysis through large-scale connectivity. However, as traffic increases explosively due to the recent spread of IIoT, an allocation method that can efficiently process traffic is required. In this thesis, I propose a two-stage task offloading decision method to increase successful task throughput in an IIoT environment. In addition, I consider a hybrid offloading system that can offload compute-intensive tasks to a mobile edge computing server via a cellular link or to a nearby IIoT device via a Device to Device (D2D) link. The first stage is to design an incentive mechanism to prevent devices participating in task offloading from acting selfishly and giving difficulties in improving task throughput. Among the mechanism design, McAfee's mechanism is used to control the selfish behavior of the devices that process the task and to increase the overall system throughput. After that, in stage 2, I propose a multi-armed bandit (MAB)-based task offloading decision method in a non-stationary environment by considering the irregular movement of the IIoT device. Experimental results show that the proposed method can obtain better performance in terms of overall system throughput, communication failure rate and regret compared to other existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1884-1903
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• 2019

Device-to-Device (D2D) communications can provide proximity based services in the future 5G cellular networks. It allows short range communication in a limited area with the advantages of power saving, high data rate and traffic offloading. However, D2D communications may reuse the licensed channels with cellular communications and potentially result in critical interferences to nearby devices. To control the interference and improve network throughput in overlaid D2D cellular networks, a novel channel assignment approach is proposed in this paper. First, we characterize the performance of devices by using Poisson point process model. Then, we convert the throughput maximization problem into an optimal spectrum allocation problem with signal to interference plus noise ratio constraints and solve it, i.e., assigning appropriate fractions of channels to cellular communications and D2D communications. In order to mitigate the interferences between D2D devices, a cluster-based multi-channel assignment algorithm is proposed. The algorithm first cluster D2D communications into clusters to reduce the problem scale. After that, a multi-channel assignment algorithm is proposed to mitigate critical interferences among nearby devices for each D2D cluster individually. The simulation analysis conforms that the proposed algorithm can greatly increase system throughput.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.8
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• pp.900-908
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• 2012

Owing to the proliferation of smart phone users, a proactive spectrum policy is needed in order to deal with increasing data traffic. Therefore, the prediction of frequency requirements for future wireless local area network (WLAN) as well as a licensed cellular communication is necessary. In this paper, we proposed a new prediction method for WLAN spectrum requirements. This method includes both a traditional prediction method and an offloading percentage from cellular network, Also, it can consider a frequency interference between access points using a statistical approach. Based on these approaches, we can predict the spectrum requirements of future domestic WLAN services considering the frequency interference. Finally, we suggest the spectrum policy for WLAN which can prevent spectrum shortage of future WLAN services.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.1
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• pp.31-38
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• 2012

Next generation cellular applications and smart phone usage generate very heavy wireless data traffic. It becomes ineluctable for mobile network operators to have multiple core network entities such as Serving Gateway and Packet Data Network Gateway in 4G-LTE to share this high traffic generated. A typical configuration consists of multiple serving gateways behind a load-balancer which would determine which serving gateway would service a end-users'request. Such hardware is expensive, has a rigid policy set, and is a single point of failure. Another perspective of today's increasingly high data traffic is that besides it is being widely accepted that the high bandwidth L TE provides is creating bottlenecks for service providers by the increasing user bandwidth demands without creating any corresponding revenue improvements, a hidden problem that is also passively advancing on the newly emerging 4G-LTE that may need more immediate attention is the network signaling traffic, also known as the control-plane traffic that is generated by the applications developed for smartphones and tablets. With this as starting point, in this paper, we propose a solution, by a new approach considering OpenFlow switch connected to a controller, which gains flexibility in policy, costs less, and has the potential to be more robust to failure with future generations of switches. This also solves the problem of scaling the control-plane traffic that is imperative to preserve revenue and ensure customer satisfaction. Thus, with the proposed architecture with OpenFlow, mobile network operators could manipulate the traffic generated by the control-plane signaling separated from the data-plane, besides also reducing the cost in installing multiple core-network entities.