Browsing by Author "Tung, Li-Ping"

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A Cloud-based Outdoor Assistive Navigation System for the Blind and Visually Impaired
(2014-01-01)
Lapyko, Anna N.
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Tung, Li-Ping
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Lin, Bao-Shuh Paul
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資訊工程學系
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Department of Computer Science
Safe navigation in non-familiar outdoor environments is a challenging activity for the blind and visually impaired (BVI) people. This work introduces a cloud-based outdoor assistive navigation system (COANS) for BVI people. The main goal of the system is to provide easy street navigation and help to make outdoor walk in non-familiar environment less stressful. Hardware part from the user-side includes an android-based mobile phone and an external low-cost L1 GPS receiver to improve position accuracy. Applying the technique known as Real Time Kinematic (RTK) ameliorates the issue of the user position estimation. Interaction between the application and the user is based on voice commands (user-side) and voice notifications (system-side), together with the user-friendly "shaking" and "swiping" commands. The test scenarios for the system include traffic light status detection, zebra crossing path detection, and a bench discovering within a short distance from the user. In order to evaluate overall system performance, two groups of tests have been conducted. One is for GPS location accuracy from RTKLib and the other is for server-client communication time. It shows the usability of the proposed COANS system.
A Practical Model for Traffic Forecasting based on Big Data, Machine-learning, and Network KPIs
(2018-01-01)
Le, Luong-Vy
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Sinh, Do
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Tung, Li-Ping
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Lin, Bao-Shuh Paul
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資訊工程學系
Traffic forecasting plays an important role in improving network quality and energy saving of mobile networks. In 5G, traffic forecasting directly influences the self-organizing network (SON) in managing and controlling the network effectively. Especially, long-term traffic forecasting can provide a detailed pattern of future traffic, besides permitting more time for planning and optimizing. Most of the traffic forecasting models used the history of traffic, while the utilization of another network KPIs (key performance indicators) for traffic forecasting is limited. Therefore, the authors propose here a practical platform and process for traffic forecasting, based on big data, machine-learning (ML), and network KPIs that are flexible to forecast accurately different statistical traffic characteristics of different types of cells (GSM, 3G, 4G) for both long-and short-term forecasting. The performance of the proposed model was evaluated by applying it to a real dataset that collected KPIs of more than 6000 cells of a real network during the years, 2016 and 2017
A Study of Comfort Measuring System Using Taxi Trajectories
(2011)
Tung, Li-Ping
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Chien, Tsung-Hsun
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Wang, Ting-An
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Lin, Cheng-Yu
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Jeng, Shyh-Kang
The comfort of rides has been identified as one of the top criteria that affects passengers' satisfaction with public transportation systems. Conventional comfort measurement approaches rely on professional measure tools or interviews from passengers, which are costly, time-consuming, and not yet feasible. The concept of Internet of Things (IoT) is a new solution to answer this problem. The idea of IoT is to interconnect state-of-the-art digital products in physical world to provide more powerful applications. Vehicles equipped with GPS devices and wireless access technologies are parts of the IoT elements in traffic networks. We use the GPS data to measure the comfort level of vehicle rides, and provide a detailed comfort statistics as a value added service. Using real data collected from one of the Taipei taxi service providers, we show that over 95% taxi trajectories are viewed as comfortable. In addition, rides without passengers get higher comfort scores than with passengers. We also give the rankings of all taxi drivers according to a number of criteria, such as the comfort score and the number of loads. With the ranking results, we can track back to the trajectories and infer drives' driving behaviors, road conditions, and traffic conditions. We believe that the proposed solution has the potential to provide a representative comfort measurement service for taxi services and additional value-added services for public transportation systems.
An Empirical Study on Data Retrievability in Decentralized Erasure Code Based Distributed Storage Systems
(2013)
Lin, Hsiao-Ying
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Tung, Li-Ping
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Lin, Bao-Shuh P.
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資訊工程學系
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Department of Computer Science
Erasure codes are applied in distributed storage systems to provide data robustness against server failures by storing data redundancy among many storage servers. A (n, k) erasure code encodes a data object, which is represented as k elements, into a codeword of n elements such that any k out of these n codeword elements can recover the data object back. Decentralized erasure codes are proposed for distributed storage systems without a central authority. The characteristic of decentralization makes resulting storage systems more scalable and suitable for loosely-organized networking environments. However, different from conventional erasure codes, decentralized erasure codes trade some probability of a successful data retrieval for decentralization. Although theoretical lower bounds on the probability are overwhelming from a theoretical aspect, it is essential to know what the data retrievability is in real applications from a practical aspect. We focus on decentralized erasure code based storage systems and investigate data retrievability from both theoretical and practical aspects. We conduct simulation for random processes of storage systems to evaluate data retrievability. Then we compare simulation results and analytical values from theoretical bounds. By our comparison, we find that data retrievability is underestimated by those bounds. Data retrievability is over 99% in most cases in our simulations, where the order of the used finite field is an 8-bit prime. Data retrievability can be enlarged by using a larger finite field. We believe that data retrievability of decentralized erasure code based storage systems is acceptable for real applications.
An Improved Method of Constructing a Data Aggregation Tree in Wireless Sensor Networks
(2012)
Liu, Bing-Hong
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Jhuang, Ying-Hong
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Tung, Li-Ping
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Jhang, Jyun-Yu
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資訊工程學系
With the rapid application development for wireless sensor networks, effective information collection methods are becoming increasingly emphasized. The effectiveness of data aggregation is mainly determined by the routing structure while tree is an important structure for data aggregation. Many researchers have studied the problem of how to construct a routing tree in a wireless sensor network with relay nodes so that the total transmission and reception energy cost consumed by all sensors is minimized, the so-called Minimum Energy-Cost Aggregation Tree with Relay Nodes problem. In this paper, we propose an improved method to reconstruct a routing tree so that the total energy cost can be reduced. Using simulation, we demonstrate that a shortest path routing tree applied with our proposed Reconstruction algorithm could have lower total energy cost than the original one.
An Interference-aware Small Cell on/off Mechanism in Hyper Dense Small Cell Networks
(2016-01-01)
Tung, Li-Ping
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Wang, Li-Chun
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Chen, Kuan-Sheng
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資訊工程學系
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電機工程學系
Small cells have been proposed to improve the signal quality of cell edge users and enhance the serving coverage. But a large number of small cells will cause severe interference and high energy consumption. Hence, green communication is an important issue. The main contribution of this paper is to provide an interference-aware small cell on/off mechanism in a downlink heterogeneous network system to reduce inter-cell interference in the sense of energy saving. Two criteria for the small cell on/off mechanism are proposed; one is based on the generated interference (GI) and the other is based on the signal to generated interference ratio (SGIR). In addition, two selection rules are provided; one is the exhaustive search (ES) method and the other is the one time (OT) method. In hyper dense small cells deployment scenario, our interference-aware small cell on/off mechanism can efficiently reduce inter-cell interference to maximize the total network energy efficiency. Compare to the traditional UE-cell association approach, our method provide 47.38% improvement at lambda(b)/lambda(u) = 0 : 4 and 61.44% improvement lambda(b)/lambda(u) = 0 : 6.
Analysis of DRX Power Saving with RRC States Transition in LTE Networks
(2015)
Tung, Li-Ping
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Wang, Li-Chun
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Hsueh, Cheng-Wen
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Chang, Chung-Ju
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資訊工程學系
The 3GPP Long Term Evolution (LTE) wireless technology provides high data rates and improved latency to the end users. Such improvement is obtained from the advanced MAC and PHY layer techniques, which exhaust the battery life of the User Equipment (UE) quickly. To save the power of UE, 3GPP LTE proposes a mechanism called Discontinuous Reception Mechanism (DRX) which lets the UE switch its RF module off when data needs not be transmitted. In this paper, we have developed an analytical model to derive the DRX power saving obtained by the UE in LTE system. Different from other work, the RRC (Radio Resource Control) states transition is considered. The time period for power saving operation is divided into several independent parts to derive the power consumption and the transmission delay. In addition, we introduce the real power consumption model into the derived power saving model to obtain the truly power consumption. The analytical results show the UE with lower packet arrival rate can effectively save more power when entering RRC IDLE state, and there is a trade-off between the power consumption and the transmission delay.
Analytical Model For Power Savings in LTE Networks using DRX Mechanism
(2015)
Varma, Syama R.
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Sivalingam, Krishna M.
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Tung, Li-Ping
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Lin, Ying-Dar
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資訊工程學系
This paper presents an analytical model, based on a semi-Markov process, for determining the power savings achieved in a User Equipment (UE) device of a Long Term Evolution (LTE) network using the Discontinuous Reception (DRX) mechanism. Systems with and without packet buffers and the UE and enodeB are presented in this paper. Using the models, it is possible to determine the savings in power attainable by the UE when different DRX sleep cycles and timers are used. The analytical models has been validated using a discrete-event simulation model. The numerical results show that it is possible to obtain UE power savings of up to 63%.
Applying Big Data, Machine Learning, and SDN/NFV to 5G Traffic Clustering, Forecasting, and Management
(2018-01-01)
Luong-Vy Le
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Sinh, Do
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Lin, Bao-Shuh Paul
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Tung, Li-Ping
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資訊工程學系
Traffic clustering, forecasting, and management play a crucial role in improving network efficiency, network quality, load balancing (LB), and energy saving of mobile networks. Especially, in 5G networks, a dense heterogeneous architecture of various types of cells (macro cells and small cells) make traffic management become more complicated. Moreover, investigating and understanding traffic patterns of a huge number of cells are challenging issues, but valuable for network operators. On the other hand, big data, machine learning (ML), software defined network (SDN), and network functions virtualization (NFV) have recently been proposed as emerging technologies and the necessary tools for empowering the SON of 5G to address the intensive computation and optimization issues. In this study, the authors applied those technologies to build a practical and powerful framework for clustering, forecasting, and managing traffic behaviors for a huge number of base stations with different statistical traffic characteristics of different types of cells (GSM, 3G, 4G). Besides, several applications based on traffic forecasting were also introduced. Finally, the performance of the proposed models was evaluated by applying them to a real dataset that collected traffic KPIs (key performance indicators) of more than 6000 cells of a real network during the years, 2016 and 2017.
Big Data and Machine Learning Driven Handover Management and Forecasting
(2017-01-01)
Vy, Le Luong
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Tung, Li-Ping
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Lin, Bao-Shuh Paul
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材料科學與工程學系
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資訊工程學系
Handover (HO), as a key aspect of mobility management, plays an important role in improving network quality and mobility performance in mobile networks. Especially, in 5G networks, heterogeneous networks (HetNets) deployment of macro cells and small cells, and the deployment of ultra-dense networks (UDNs) make HO management become more challenging. Besides, the understanding of HO behavior in a cell is quite limited in existing studies, thus the forecasting HO for an individual cell is complicated, even impossible. This challenge led the authors to propose a practical process for managing and forecasting HO for a huge number of cells, based on machine-learning (ML) algorithms and big data. Moreover, based on HO forecasting, the authors also propose an approach to detect any abnormal HO in cells. The performance of the proposed approaches was evaluated by applying it to a real dataset that collected HO KPI of more than 6000 cells of a real network during the years, 2016 and 2017. The results show that the study was successful in identifying, separating HO behavior, forecasting the future number of HO attempts, and detecting abnormal HO behaviors of cells.
CrowdSMILE: A Crowdsourcing-based Social and Mobile Integrated System for Learning by Exploration
(2013-01-01)
Punjabi, Dennis Mohan
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Tung, Li-Ping
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Lin, Bao-Shuh Paul
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資訊工程學系
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Department of Computer Science
Lifelong Learning (LLL) can be enabled by Personal Learning Environments (PLEs), which are usually composed of a mixed set of loosely coupled tools, applications and systems. In such a mixed environment, managing learning content across the PLE can often be challenging and lead to disorganized content and as such, makes content reuse difficult while also possibly causing learners to lose content over time. In this paper, we propose an integrated system, called CrowdSMILE, using web, social and mobile technologies to provide a unified system that allows for easy organization, accessing, and reuse of learning content within a social and collaborative environment to support LLL. Content in the CrowdSMILE system is authored and organized by crowdsourcing the task to users of a Social Networking Service (SNS) platform. The learning content will then be organized according to location-based contexts so that any learner may easily find and retrieve it. Content may then be searched and accessed via an outdoor exploratory activity using a mobile phone application that employs an intuitive mobile augmented reality (MAR) user interface. The system usability of the CrowdSMILE is evaluated by applying the Computer System Usability Questionnaire (CSUQ). The results show that the proposed system received high scores throughput which indicates positive attitude and usability of the proposed CrowdSMILE system.
Dynamic DRX Algorithms for Reduced Energy Consumption and Delay in LTE Networks
(2014)
Varma, Syama R.
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Sivalingam, Krishna M.
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Tung, Li-Ping
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Lin, Ying-Dar
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資訊工程學系
The Long Term Evolution (LTE) standard specifies the Discontinuous Reception Mechanism (DRX) mechanism for saving power at the User Equipment (UE). Here, a UE switches off its RF circuitry when there are no packets to be transmitted or received. The existing DRX algorithms use static operational parameters that are determined by the evolved nodeB (eNB) at the start of a UE\'s session. During the switch-off period, packets destined to the UE are buffered in the eNB leading to higher packet latency. This paper presents two adaptive algorithms to dynamically adjust the DRX parameters, in order to reduce both energy consumption and the extra delay incurred. The algorithms use application Quality-of-Service (QoS) and Channel Quality Information (CQI) to adjust the DRX parameters. Performance studies based on ns3 simulator show that the algorithms are able to reduce packet delay compared to static DRX by up to 60%, 60% and 75% and reduce energy consumption by up to 75%, 43% and 90% for video streaming, VoIP and bursty data applications respectively.
Enhanced Component Carrier Selection and Power Allocation in LTE-Advanced Downlink Systems
(2013)
Ho, Wei-Ching
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Tung, Li-Ping
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Chang, Tain-Sao
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Feng, Kai-Ten
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電子工程學系及電子研究所
Because of the scarcity of spectrum and energy resource, the problems about allocation of these resources become more and more important in recent years. However, inappropriate resource allocation may bring about high inter-cell interference which has a great effect on the performance of the entire system. Thus, in this paper, considering inter-cell interference, we provide the optimal formulation of the resource allocation problem and divide it into two sub-problems, including the component carrier (CC) selection problem and the power allocation problem. The proposed enhanced data rate component carrier selection (EDR-CCS) scheme not only reduces the inter-cell interference but also maximizes the UEs' data transmission rates. Regarding the power allocation problem, two schemes (i.e., geometry programming power allocation (GPPA) and constant interference power allocation (CIPA)) are proposed with the target of finding suboptimal solutions to the power allocation problem under the constraints of eNB's maximum transmission power and UEs' transmission rate requirement on the control channel of primary CC (PCC). Simulation results demonstrate that the data rate performance of EDR-CCS scheme is better than that of random CC selection scheme. Furthermore, GPPA scheme can achieve better performance than CIPA scheme since the GPPA scheme can accommodate the variations from inter-cell interference.
Measuring Link Characteristics of Power Line Communication Systems
(2013)
Lee, Wei-Xian
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Tung, Li-Ping
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Ho, Yao-Hua
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Chen, Ling-Jyh
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資訊工程學系
Knowing link characteristics of a network connection is essential for the efficient design, management, and usage of a network. In view of the proliferation of power line communication systems, in this work, we propose a novel measurement approach, called PLC-Probe, to concurrently measure link capacity and available bandwidth of PLC links. PLC-Probe uses \'train-chirps\' to probe the network, and it combines the strengths of the packet train and packet chirp approaches for estimation of link characteristics. Using testbed experiment, we evaluate the proposed approach and show that PLC-Probe is accurate, stable, and robust against cross traffic. Moreover, PLC-Probe is simple, effective, and applicable to other multi-rated PLC-like networks.
MetroNet: a disruption-tolerant approach for mobile downloads on metro systems
(2014-08-01)
Tung, Li-Ping
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Chen, Yi-Chao
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Lan, Kun-chan
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Chen, Ling-Jyh
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交大名義發表
In this study, we propose a disruption-tolerant network based system called MetroNet, which exploits the precise schedules of metro systems to pre-fetch data and facilitate mobile Internet downloads, even if an end-to-end path between the source (i.e. content sources) and the destination (i.e. users) does not exist contemporaneously. Using a comprehensive set of simulations, as well as real-world scenarios of the Taipei and Atlanta metro systems, we demonstrate that MetroNet can handle the intermittent Internet connectivity caused by mobility and therefore provide a better mobile download service. The simulation results demonstrate that the proposed call admission control algorithm utilises the network resource effectively and provides better quality of service for mobile users than the first-come-first-serve and least-first algorithms. Copyright (C) 2013 John Wiley & Sons, Ltd.
On Local Cache Management Strategies for Mobile Augmented Reality
(2014-01-01)
Wu, Chien-Cheng
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Tung, Li-Ping
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Lin, Chih-Yu
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Lin, Bao-Shuh P.
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Tseng, Yu-Chee
Mobile Augmented Reality (MAR) is generally defined as the service that is capable of enhancing the real-world camera views of a smartphone with extra information on top of the screen. Thus, MAR has triggered strong interests in mobile e-commerce, location-based service, etc. However, MAR is usually constrained by the local storage and computing power of the device as well as the latency and bandwidth of the underlying wireless channel. The computation demand is high because a targeted object needs to be compared to lots of images in the database. The communication demand is high because potential objects need to be continuously transmitted to the server and the augmented information needs to be downloaded from the server. This paper investigates the Local Cache Management (LCM) problem to manage the computation and communication work of a mobile device and harmonize the local and remote workloads. We present strategies to pre-fetch higher-priority objects from the server and replace lower-priority objects in the local cache based on temporal and spatial access locality. We verify the effectiveness of our strategies in term of cache hit ratio, response latency, and remote requests via simulations.
On the Classification of Mobile Broadband Applications
(2016)
Hsieh, I-Ching
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Tung, Li-Ping
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Lin, Bao-Shuh Paul
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材料科學與工程學系
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資訊工程學系
In the past decade, the Internet has been widely used in everyday life. Different types of mobile broadband applications are created and require an increasing amount of network resources. However, Internet service providers must maximize the use of these limited resources to provide users with different levels of quality of service. The first step toward traffic engineering is to perform traffic classification. In this work, we propose a classification method for identifying mobile applications executed at an early stage. We first collected traffic traces from a WiFi access point and then developed a hidden Markov model based on the packet size and transmission direction of the first 20 packets. In a series of our experiments, we evaluated the number of hidden states through 10-fold cross validation, and classified six types of mobile applications. The accuracy of the proposed method achieved 99.17%. In addition, we set specific threshold values for different application models and identified 91.33% of flows in the testing data set, which comprised unknown traffic flows. These experimental results demonstrate that our proposed method is effective for classifying Internet flows as well as unknown traffic in a real network.
Reducing power consumption in LTE data scheduling with the constraints of channel condition and QoS
(2014-12-24)
Tung, Li-Ping
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Lin, Ying-Dar
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Kuo, Yu-Hsien
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Lai, Yuan-Cheng
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Sivalingam, Krishna M.
3GPP has developed the Discontinuous Reception (DRX) power saving mechanism, which periodically turns off the radio interface to reduce the power consumption. However, packets cannot be received during the turn-off duration, as a result that the Quality of Services (QoS) may be violated. Therefore, optimal DRX parameters should be configured to satisfy QoS and minimize power consumption. In addition, channel condition may be unstable during the transmission, so the DRX parameters should also be dynamically adjusted. In this paper, we propose the Dynamic Scheduling with Extensible Allocation and Dispersed Offsets (DXD) scheme, which is composed of two algorithms, DRX parameters decision, to determine DRX period by considering channel condition and QoS constraints, and DRX-aware scheduling, to determine whether to extend the on duration so that QoS would not be affected by DRX. Simulation results demonstrate that the proposed DXD approach can reduce power consumption up to 96.7% compared to No-DRX scheme and guarantee QoS as good as No-DRX scheme. In addition, the power consumption can be reduced by 70.1% and 45.7% compared to the Fixed-DRX (100 ms), start-offset scheme and IS scheme in good channel condition. Our approach effectively reduces power consumption in varied channel conditions and high loading system and still achieves better delay satisfaction ratio than others. (C) 2014 Elsevier B.V. All rights reserved.
Reducing Power Consumption in LTE Data Scheduling with the Constraints of Channel Condition and QoS
(2014-01-01)
Tung, Li-Ping
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Lin, Ying-Dar
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Ku, Yu-Hsien
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Lai, Yuan-Cheng
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Sivalingam, Krishna M.
3GPP has developed the Discontinuous Reception (DRX) power saving mechanism, which periodically turns off the radio interface to reduce power consumption. However, packets cannot be received during the on period, as a result that the Quality of Services (QoS) may be violated. In addition, channel condition may be unstable during the transmission, so the optimal DRX parameters should also be dynamically adjusted. In this paper, we propose the Dynamic Scheduling with Extensible Allocation and Dispersed Offsets (DXD) scheme, which is composed of two algorithms, DRX parameter decision algorithm, to determine the DRX period by considering channel condition and QoS constraints, and DRX-aware scheduling algorithm, to determine whether to extend the on duration so that QoS would not be affected by DRX. Simulation results demonstrate that our DXD approach can reduce power consumption up to 96.9% compared to no DRX scheme and guarantee QoS as good as no DRX scheme.
Reliable Repair Mechanisms with Low Connection Cost for Code Based Distributed Storage Systems
(2014-01-01)
Lin, Hsiao-Ying
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Tung, Li-Ping
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Lin, Bao-Shuh P.
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資訊工程學系
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Department of Computer Science
Erasure codes are applied in distributed storage systems for fault-tolerance with lower storage overhead than replications. Later, decentralized erasure codes are proposed for decentralized or loosely-organized storage systems. Repair mechanisms aim at maintaining redundancy over time such that stored data are still retrievable. Two recent repair mechanisms, NOOP and COOP, are designed for decentralized erasure code based distributed storage system to minimize connection cost in theoretical manner. We propose a generalized repair framework, which includes NOOP and COOP as two extreme cases. We then investigate trade-off between connection cost and data retrievability from an experimental aspect in our repair framework. Our results show that a reasonable data retrievability is achievable with constant connection cost, which is less than previously analytical values. These results are valuable references for a system manager to build a reliable storage system with low connection cost.