Browsing by Author "Chang, Po-Yen"

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Aggregating Small Packets in M2M Networks: An OM2M Implementation
(2016-01-01)
Lee, Sheng-Chieh
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Wu, Kun-Ru
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Hsu, Ching-Kuo
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Chang, Po-Yen
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Liang, Jia-Ming
IoT (Internet of Things) and M2M (machine to machine) have attracted a lot of attention since more and more devices are expected to connect to the Internet for special purposes such as environment monitoring, home automation, industrial surveillance, and e-Health care. Currently, the OM2M (Open source platform for M2M communication) is a promising project which implements oneM2M and SmartM2M standards as an open-source platform for integrating various M2M services, applications, and devices. However, the individual data generated from those IoT/M2M devices is usually quite small, which incurs a lot of control overhead and thus decreases network performance significantly. Therefore, in this work we design and implement an OM2M 'plugin' that can aggregate small IoT data effectively. We will show how the plugin works and verify the effectiveness on the network bandwidth in this demonstration.
Energy-efficient DRX scheduling for D2D communication in 5G networks
(2018-08-15)
Liang, Jia-Ming
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Chang, Po-Yen
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Chen, Jen-Jee
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Huang, Chien-Feng
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Tseng, Yu-Chee
In recent years, intelligent devices such as smart phones and smart tablets are grown and developed rapidly. High-bandwidth media services such as live streaming, gaming and multi-user video conferencing are more and more popular. This results in spectrum resource depletion of the cellular network. To alleviate the problem, the 3rd Generation Partnership Project (3GPP) has proposed a new technology, called device-to-device (D2D) communications. However, D2D devices and direct link cellular users all share and access the same spectrum resource, thus degrading the network performance significantly due to the interference. In addition, due to the frequent communication nature of streaming and gaming services, the power consumption of devices is increasing dramatically. To mitigate above problems, this paper investigates how to improve the spectrum efficiency by well scheduling and allocating radio resource to more concurrent D2D and cellular users on the uplink direction and reduce unnecessary power consumption of devices via Discontinuous Reception (DRX) scheduling while guaranteeing users' Quality of Service (QoS). We propose an energy-efficient resource and sleep scheduling scheme. This scheme first establishes a conflict graph to maintain the transmission and interference relationship, and then tries to maximize concurrent D2D and mobile users by resource reuse. At the same time, the method also exploits DRX technology to further decrease possible interference and conserve devices' power consumption through optimizing their sleep operation. Simulation results show that our scheme can achieve better performance on system throughput, network capacity, and power saving compared to the existing schemes.
Energy-efficient scheduling scheme with spatial and temporal aggregation for small and massive transmissions in LTE-M networks
(2019-01-01)
Liang, Jia-Ming
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Chang, Po-Yen
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Chen, Jen-Jee
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資訊工程學系
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Department of Computer Science
Machine-to-machine (M2M) communication is one of the key technologies to realize Internet of Things (IoT). Since IoT applications are mainly for smart sensing, such as metering, home surveillance, disaster detection, and e-health, their special sensing/uploading behaviors will result in periodic and/or event-driven small data transmissions, which may potentially decrease the radio resource efficiency. On the other hand, due to the frequent communication nature of sensing data for IoT applications, the power consumption is increasing dramatically. To reduce the power consumption of IoT devices, the 3rd Generation Partnership Project (3GPP) has defined the discontinuous reception/discontinuous transmission (DRX/DTX) mechanism to allow devices to turn off their radio interfaces and go to sleep in various patterns. However, how to optimize the DRX/DTX scheduling while improving the resource efficiency is still an open issue. In this paper, we investigate an uplink resource allocation problem over long-term evolution machine-to-machine (LTE-M) networks, which is standardized by 3GPP to improve performance on IoT. In this network, we consider the periodic, event-driven, and query-based IoT traffic while minimizing the devices' power consumption. We prove this problem to be NP-complete and propose an aggregation-efficient DRX/DTX scheduling (AEDS) scheme. This scheme takes advantage of both spatial and temporal data aggregation while applying DRX/DTX for energy saving. Specifically, the scheme consists of three phases. The first phase exploits long-term static scheduling for periodic data to ensure the latency and data rate while minimizing the devices' wake-up time. The second phase tries to decrease devices' power consumption through precisely determining their DRX/DTX configurations. Finally, the third phase employs short-term dynamic scheduling for event-driven and query-based data to improve transmission efficiency. Therefore, both small data and power consumption problems are relieved. Extensive simulation results show that the proposed scheme can improve resource efficiency, enlarge network capacity while reducing power consumption compared to the existing schemes. (C) 2018 Elsevier B.V. All rights reserved.
From Spotting the Difference to Spotting Your Difference
(2015-01-01)
Chan, Tsung-Yen
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Chang, Po-Yen
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Ren, Yi
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Tseng, Yu-Chee
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資訊工程學系
E-healthcare games are a new patient care tool for providing fun, on-line monitoring enabled lifestyle, and a way for redefining traditional doctor-patient relationship. In this work, we demonstrate the use of intelligent sensors to capture patient behaviors for home healthcare. We design a new e-healthcare game user interface, iCube, for monitoring and recording patient activities. The iCube is a 3D game which has six display panels on the surfaces of a 3D cube embedded with a zigbee interface and some sensors for behavior monitoring. To prove its concept, we implement a Spot the Difference game. When a player is playing the game, the iCube can capture the player's hand shaking, rolling response, and visual capability. Those collected data are then sent to a database for spotting the progress/difference of the player over a long period time.
Spatial and Temporal Aggregation for Small and Massive Transmissions in LTE-M Networks
(2017-01-01)
Chang, Po-Yen
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Liang, Jia-Ming
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Chen, Jen-Jee
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Wu, Kun-Ru
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Tseng, Yu-Chee
Machine-to-machine (M2M) communication is one of the key technologies to realize Internet of Things (IoT). Since IoT applications are mainly for smart sensing, such as metering, home surveillance, disaster detection, and e-health, their special sensing/uploading behaviors will result in periodic and/or eventdriven small data transmissions, which may potentially decrease the radio resource efficiency. On the other hand, the widespread deployment of IoT raises the concurrent massive connectivity of IoT devices. How to solve these two problems is a critical issue. In this paper, we investigate an uplink resource allocation problem which considers the periodic, event-driven, and query-based IoT traffic behaviors over LTE-M. The proposed approach takes advantage of data aggregation and both spatial and temporal reuse. Our solution exploits long-term static scheduling for periodic data to ensure the latency and data rate, and employs short-term dynamic scheduling for event-driven, query-based data to improve transmission efficiency. Therefore, both small data and massive connectivity problems are relieved. Extensive simulation results show that the proposed scheme can improve resource efficiency and enlarge network capacity effectively.