• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권3호
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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.

• International journal of advanced smart convergence
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• 제8권2호
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• pp.39-46
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• 2019

Human mobility estimation plays a key factor in a lot of promising applications including location-based recommendation systems, urban planning, and disease outbreak control. We study the human mobility estimation problem in the case where recent locations of a person-of-interest are unknown. Since matrix decomposition is used to perform latent semantic analysis of multi-dimensional data, we propose a human location estimation algorithm based on matrix factorization to reconstruct the human movement patterns through the use of information of persons with correlated movements. Specifically, the optimization problem which minimizes the difference between the reconstructed and actual movement data is first formulated. Then, the gradient descent algorithm is applied to adjust parameters which contribute to reconstructed mobility data. The experiment results show that the proposed framework can be used for the prediction of human location and achieves higher predictive accuracy than a baseline model.

• 한국공간정보시스템학회 논문지
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• 제10권3호
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• pp.45-54
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• 2008

텔레매틱스 네트워크 구성을 위한 유용한 가이드라인과 정보를 제공하기 위하여 본 논문은 현재 운영되고 있는 택시 텔레매틱스 시스템으로부터 수집된 실제 이동이력 데이터를 바탕으로 하이브리드 텔레매틱스 네트워크에 있어서의 연결성 분석기를 설계하고 구현한다. 본 설계에 따라 구현된 분석기는 다양한 인자들을 고려한 시뮬레이션에 의해 1) 각각의 차량의 위치를 추적하고, 2) 차량의 타입, 즉, 게이트웨이 또는 일반 노드인지를 설정하며, 3) 특정시간에 한 노드가 모바일 게이트웨이에 연결 될 수 있는지 판단하고 4) 차량의 상태추적에 의해 연결의 단절 시간을 계산한다. 무선 전송거리와 게이트웨이 비율 등의 성능인자를 고려한 이 분석을 통해, 셀룰러 네트워크와 애드혹 네트워크가 결합된 하이브리드 네트워크에서 각 노드의 연결성과 연결 단절시간에 대한 사전분석을 시행할 수 있으며 이에 의해 효율적인 모바일 게이트웨이의 밀도와 버퍼 공간의 양을 결정할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권12호
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• pp.5712-5728
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• 2017

Recently, there are many studies, that considering green wireless cellular networks, have taken the energy consumption of the base station (BS) into consideration. In this work, we first introduce an energy consumption model of multi-mode sharing BS powered by multiple energy sources including renewable energy, local storage and power grid. Then communication load requests of the BS are transformed to energy demand queues, and battery energy level and worst-case delay constraints are considered into the virtual queue to ensure the network QoS when our objective is to minimize the long term electricity cost of BSs. Lyapunov optimization method is applied to work out the optimization objective without knowing the future information of the communication load, real-time electricity market price and renewable energy availability. Finally, linear programming is used, and the corresponding energy efficient scheduling policy is obtained. The performance analysis of our proposed online algorithm based on real-world traces demonstrates that it can greatly reduce one day's electricity cost of individual BS.