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Tao Gu
Department of Computing, Macquarie University, Sydney, NSW 2109, Australia

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Journal article
Published: 13 August 2021 in IEEE/ACM Transactions on Networking
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Personal mobile sensing is fast permeating our daily lives to enable activity monitoring, healthcare and rehabilitation. Combined with deep learning, these applications have achieved significant success in recent years. Different from conventional cloud-based paradigms, running deep learning on devices offers several advantages including data privacy preservation and low-latency response for both model inference and update. Since data collection is costly in reality, Google's Federated Learning offers not only complete data privacy but also better model robustness based on data from multiple users. However, personal mobile sensing applications are mostly user-specific and highly affected by environment. As a result, continuous local changes may seriously affect the performance of a global model generated by Federated Learning. In addition, deploying Federated Learning on a local server, e.g., edge server, may quickly reach the bottleneck due to resource limitation. Towards pushing deep learning on devices, we present MDLdroid, a novel decentralized mobile deep learning framework to enable resource-aware on-device collaborative learning for personal mobile sensing applications. To address resource limitation, we propose a ChainSGD-reduce approach which includes a novel chain-directed Synchronous Stochastic Gradient Descent algorithm to effectively reduce overhead among multiple devices. We also design an agent-based multi-goal reinforcement learning mechanism to balance resources in a fair and efficient manner. Our evaluations show that our model training on off-the-shelf mobile devices achieves 2x to 3.5x faster than single-device training, and 1.5x faster on average than the existing master-slave approach.

ACS Style

Yu Zhang; Tao Gu; Xi Zhang. MDLdroid: A ChainSGD-Reduce Approach to Mobile Deep Learning for Personal Mobile Sensing. IEEE/ACM Transactions on Networking 2021, PP, 1 -14.

AMA Style

Yu Zhang, Tao Gu, Xi Zhang. MDLdroid: A ChainSGD-Reduce Approach to Mobile Deep Learning for Personal Mobile Sensing. IEEE/ACM Transactions on Networking. 2021; PP (99):1-14.

Chicago/Turabian Style

Yu Zhang; Tao Gu; Xi Zhang. 2021. "MDLdroid: A ChainSGD-Reduce Approach to Mobile Deep Learning for Personal Mobile Sensing." IEEE/ACM Transactions on Networking PP, no. 99: 1-14.

Journal article
Published: 21 July 2021 in IEEE/ACM Transactions on Networking
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This paper presents LiteNap which improves the energy efficiency of LoRa by enabling LoRa nodes to operate in a downclocked `light sleep' mode for packet reception. A fundamental limit that prevents radio downclocking is the Nyquist sampling theorem which demands the clock-rate being at least twice the bandwidth of LoRa chirps. Our study reveals under-sampled LoRa chirps suffer frequency aliasing and cause ambiguity in symbol demodulation. LiteNap addresses the problem by leveraging an empirical observation that the hardware of LoRa radio can cause phase jitters on modulated chirps, which result in frequency leakage in the time domain. The timing information of phase jitters and frequency leakages can serve as physical fingerprints to uniquely identify modulated chirps. We propose a scheme to reliably extract the fingerprints from under-sampled chirps and resolve ambiguities in symbol demodulation. We update the reception pipeline of LoRa radio to enable reliable packet detection and decoding when operating in downclocked mode. We implement LiteNap on a software defined radio platform and conduct trace-driven evaluation to validate the proposed strategies. Experiment results show that LiteNap can downclock LoRa receiver to sub-Nyquist rates for energy savings (e.g., 1/8 of Nyquist rate), without substantially affecting packet reception performance (e.g., >95% packet reception rate).

ACS Style

Xianjin Xia; Yuanqing Zheng; Tao Gu. LiteNap: Downclocking LoRa Reception. IEEE/ACM Transactions on Networking 2021, PP, 1 -14.

AMA Style

Xianjin Xia, Yuanqing Zheng, Tao Gu. LiteNap: Downclocking LoRa Reception. IEEE/ACM Transactions on Networking. 2021; PP (99):1-14.

Chicago/Turabian Style

Xianjin Xia; Yuanqing Zheng; Tao Gu. 2021. "LiteNap: Downclocking LoRa Reception." IEEE/ACM Transactions on Networking PP, no. 99: 1-14.

Journal article
Published: 02 September 2020 in IEEE/ACM Transactions on Networking
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Network simulation is a fundamental service for performance testing and protocol design in wireless networks. Due to the wireless dynamics, it is highly challenging to provide repeatable and reliable simulation results that are comparable to the empirical experimental results. To achieve repeatability for simulation, the existing works focus on reproducing the behaviors on individual links. However, as observed in recent works, individual link behaviors alone are far from enough to characterize the protocol-level performance. As a result, even if the link behaviors can be simulated very closely, these works often fail to simulate the protocol performance with high reliability. In this article, we propose a novel performance-aware simulation approach which can preserve not only the link-level behaviors but also the performance-level behaviors. We first combine the spatial-temporal link diversity to devise an accurate performance model. Based on the model, we then propose a Performance Aware Hidden Markov Model (PA-HMM), where the protocol performance is directly fed into the Markov state transitions. Compared to the existing works, PA-HMM is able to simulate both link-level behaviors and high-level protocol performance. We conduct extensive testbed and simulation experiments with broadcast and anycast protocols. The results show that 1) the proposed model is able to accurately characterize communication performance for both broadcast and anycast and 2) the protocol performance is closely simulated as compared to the empirical results and the PA-HMM based simulation is more repeatable compared to the existing works.

ACS Style

Zhiwei Zhao; Geyong Min; Wei Dong; Xue Liu; Weifeng Gao; Tao Gu; Minghang Yang. Exploiting Link Diversity for Performance-Aware and Repeatable Simulation in Low-Power Wireless Networks. IEEE/ACM Transactions on Networking 2020, 28, 2545 -2558.

AMA Style

Zhiwei Zhao, Geyong Min, Wei Dong, Xue Liu, Weifeng Gao, Tao Gu, Minghang Yang. Exploiting Link Diversity for Performance-Aware and Repeatable Simulation in Low-Power Wireless Networks. IEEE/ACM Transactions on Networking. 2020; 28 (6):2545-2558.

Chicago/Turabian Style

Zhiwei Zhao; Geyong Min; Wei Dong; Xue Liu; Weifeng Gao; Tao Gu; Minghang Yang. 2020. "Exploiting Link Diversity for Performance-Aware and Repeatable Simulation in Low-Power Wireless Networks." IEEE/ACM Transactions on Networking 28, no. 6: 2545-2558.

Journal article
Published: 27 August 2020 in IEEE/ACM Transactions on Networking
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LoRa has emerged as a promising Low-Power Wide Area Network (LP-WAN) technology to connect a huge number of Internet-of-Things (IoT) devices. The dense deployment and an increasing number of IoT devices lead to intense collisions due to uncoordinated transmissions. However, the current MAC/PHY design of LoRaWAN fails to recover collisions, resulting in degraded performance as the system scales. This article presents FTrack, a novel communication paradigm that enables demodulation of collided LoRa transmissions. FTrack resolves LoRa collisions at the physical layer and thereby supports parallel decoding for LoRa transmissions. We propose a novel technique to separate collided transmissions by jointly considering both the time domain and the frequency domain features. The proposed technique is motivated from two key observations: (1) the symbol edges of the same frame exhibit periodic patterns, while the symbol edges of different frames are usually misaligned in time; (2) the frequency of LoRa signal increases continuously in between the edges of symbol, yet exhibits sudden changes at the symbol edges. We detect the continuity of signal frequency to remove interference and further exploit the time-domain information of symbol edges to recover symbols of all collided frames. We substantially optimize computation-intensive tasks and meet the real-time requirements of parallel LoRa decoding. We implement FTrack on a low-cost software defined radio. Our testbed evaluations show that FTrack demodulates collided LoRa frames with low symbol error rates in diverse SNR conditions. It increases the throughput of LoRaWAN in real usage scenarios by up to 3 times.

ACS Style

Xianjin Xia; Yuanqing Zheng; Tao Gu. FTrack: Parallel Decoding for LoRa Transmissions. IEEE/ACM Transactions on Networking 2020, 28, 2573 -2586.

AMA Style

Xianjin Xia, Yuanqing Zheng, Tao Gu. FTrack: Parallel Decoding for LoRa Transmissions. IEEE/ACM Transactions on Networking. 2020; 28 (6):2573-2586.

Chicago/Turabian Style

Xianjin Xia; Yuanqing Zheng; Tao Gu. 2020. "FTrack: Parallel Decoding for LoRa Transmissions." IEEE/ACM Transactions on Networking 28, no. 6: 2573-2586.

Journal article
Published: 31 July 2020 in IEEE Internet of Things Journal
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Long-range (LoRa) is an attractive low-power wide-area networks (LPWANs) technology for its features of low power, long range and support for concurrent transmission. Our study reveals LoRa concurrent transmission suffer from the mismatch between sender’s reception (RX) and gateway’s transmission (TX) window, which leads to the decline of goodput even the throughput is improved. Our experiment shows that goodput only accounts for two-fifths of throughput in concurrent transmissions with 48 nodes at a duty cycle of 20%. This paper presents a window match scheme named Cantor which improves the goodput of LoRa concurrent transmission by controlling the RX window size. Cantor does not require the frequent exchange of controlling information. Instead, it introduces a novel concurrent transmission model to estimate downlink packet reception rate (PRR) with different network parameters, a regression model is used to make the result more realistic. Then we propose a simple optimization algorithm to select optimal RX window sizes in which nodes are able to receive acknowledgments. We implement and evaluate Cantor with commodity LoRa gateway and nodes, and conduct experiments in different scenarios. Experiment results show that Cantor increases the goodput by 70% and reduces energy consumption by 30% in LoRa concurrent transmissions with 48 nodes operate at a duty cycle of 20%.

ACS Style

Dan Xu; Xiaojiang Chen; Nannan Zhang; Nana Ding; Jing Zhang; Dingyi Fang; Tao Gu. Cantor: Improving Goodput in LoRa Concurrent Transmission. IEEE Internet of Things Journal 2020, 8, 1519 -1532.

AMA Style

Dan Xu, Xiaojiang Chen, Nannan Zhang, Nana Ding, Jing Zhang, Dingyi Fang, Tao Gu. Cantor: Improving Goodput in LoRa Concurrent Transmission. IEEE Internet of Things Journal. 2020; 8 (3):1519-1532.

Chicago/Turabian Style

Dan Xu; Xiaojiang Chen; Nannan Zhang; Nana Ding; Jing Zhang; Dingyi Fang; Tao Gu. 2020. "Cantor: Improving Goodput in LoRa Concurrent Transmission." IEEE Internet of Things Journal 8, no. 3: 1519-1532.

Journal article
Published: 24 September 2019 in IEEE Systems Journal
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Sensing coverage has attracted considerable attention in wireless sensor networks. Existing work focuses mainly on the 0/1 disk model which provides only coarse approximation to real scenarios. In this article, we study the connected target coverage problem which concerns both coverage and connectivity. We use directional probabilistic sensors, and combine probabilistic and directional sensing model features to characterize the quality of coverage more accurately in an energy efficient manner. Based on the analysis of the collaborative detection probability with multiple sensors, we formulate the minimum energy connected target ϵ-probability coverage problem, aiming at minimizing the total energy cost while satisfying the requirements of both coverage and connectivity. By a reduction from a unit disk cover, we prove that the problem is nondeterministic polynomial (NP)-hard, and present an approximation algorithm with provable time complexity and approximation ratio. To evaluate our design, we analyze the performance of our algorithm theoretically and also conduct extensive evaluations to demonstrate its effectiveness.

ACS Style

Xianghua Xu; Zhixiang Dai; Anxing Shan; Tao Gu. Connected Target ϵ-probability Coverage in WSNs With Directional Probabilistic Sensors. IEEE Systems Journal 2019, 14, 3399 -3409.

AMA Style

Xianghua Xu, Zhixiang Dai, Anxing Shan, Tao Gu. Connected Target ϵ-probability Coverage in WSNs With Directional Probabilistic Sensors. IEEE Systems Journal. 2019; 14 (3):3399-3409.

Chicago/Turabian Style

Xianghua Xu; Zhixiang Dai; Anxing Shan; Tao Gu. 2019. "Connected Target ϵ-probability Coverage in WSNs With Directional Probabilistic Sensors." IEEE Systems Journal 14, no. 3: 3399-3409.

Journal article
Published: 14 August 2019 in IEEE Transactions on Mobile Computing
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The widespread use of smartphones has brought great convenience to our daily lives, while at the same time we have been increasingly exposed to security threats. Keystroke security is essential to user privacy protection. In this paper, we present GazeRevealer, a novel side-channel based keystroke inference framework to infer sensitive inputs on smartphone from video recordings of victim's eye patterns captured from smartphone front camera. We observe that eye movements typically follow the keystrokes typing on the number-only soft keyboard during password input. By exploiting eye movement patterns, we are able to infer the passwords being entered. We propose a novel algorithm to extract sensitive eye images from video streams, and classify these images with Support Vector Classification. We also propose a novel classification enhancement algorithm to further improve classification accuracy. Compared with prior keystroke detection approaches, GazeRevealer does not require any external auxiliary devices, and it only relies on smartphone front camera. We evaluate the performance of GazeRevealer on several smartphones under different real-life usage scenarios. The results show that GazeRevealer achieves an inference rate of 77.89% for single key number and an inference rate of 84.38% for 6-digit password in the ideal case.

ACS Style

Yao Wang; Wandong Cai; Tao Gu; Wei Shao. Your Eyes Reveal Your Secrets: An Eye Movement Based Password Inference on Smartphone. IEEE Transactions on Mobile Computing 2019, 19, 2714 -2730.

AMA Style

Yao Wang, Wandong Cai, Tao Gu, Wei Shao. Your Eyes Reveal Your Secrets: An Eye Movement Based Password Inference on Smartphone. IEEE Transactions on Mobile Computing. 2019; 19 (11):2714-2730.

Chicago/Turabian Style

Yao Wang; Wandong Cai; Tao Gu; Wei Shao. 2019. "Your Eyes Reveal Your Secrets: An Eye Movement Based Password Inference on Smartphone." IEEE Transactions on Mobile Computing 19, no. 11: 2714-2730.

Journal article
Published: 26 May 2019 in Sensors
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Heterogeneous Bistatic Radars (BR) have different sensing ranges and couplings of sensing regions, which provide more flexible coverage for the boundary at complex terrain such as across rivers and valleys. Due to the Cassini oval sensing region of a BR and the coupling of sensing regions among different BRs, the coverage problem of BR sensor networks is very challenging. Existing works in BR barrier coverage focus mainly on homogeneous BR sensor networks. This paper studies the heterogeneous BR placement problem on a line barrier to achieve optimal coverage. 1) We investigate coverage differences of the basic placement sequences of heterogeneous BRs on the line barrier, and prove the optimal basic placement spacing patterns of heterogeneous BRs. 2) We study the coverage coupling effect among adjacent BRs on the line barrier, and determine that different placement sequences of heterogeneous BR transmitters will affect the barrier’s coverage performance and length. The optimal placement sequence of heterogeneous BR barrier cannot be solved through the greedy algorithm. 3) We propose an optimal BRs placement algorithm on a line barrier when the heterogeneous BR transmitters’ placement sequence is predetermined on the barrier, and prove it to be optimal. Through simulation experiments, we determine that the different placement sequences of heterogeneous BR transmitters have little influence on the barrier’s maximum length. Then, we propose an approximate algorithm to optimize the BR placement spacing sequence on the heterogeneous line barrier. 4) As a heterogeneous barrier case study, a minimum cost coverage algorithm of heterogeneous BR barrier is presented. We validate the effectiveness of the proposed algorithms through theory analysis and extensive simulation experiments.

ACS Style

Xianghua Xu; Chengwei Zhao; Zongmao Cheng; Tao Gu. Approximate Optimal Deployment of Barrier Coverage on Heterogeneous Bistatic Radar Sensors. Sensors 2019, 19, 2403 .

AMA Style

Xianghua Xu, Chengwei Zhao, Zongmao Cheng, Tao Gu. Approximate Optimal Deployment of Barrier Coverage on Heterogeneous Bistatic Radar Sensors. Sensors. 2019; 19 (10):2403.

Chicago/Turabian Style

Xianghua Xu; Chengwei Zhao; Zongmao Cheng; Tao Gu. 2019. "Approximate Optimal Deployment of Barrier Coverage on Heterogeneous Bistatic Radar Sensors." Sensors 19, no. 10: 2403.

Journal article
Published: 06 March 2019 in IEEE/ACM Transactions on Networking
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This paper identifies two energy saving opportunities of Wi-Fi interface emerged during smartphone's screen-off periods. Exploiting the opportunities, we propose a new power saving strategy, BackPSM, for screen-off Wi-Fi communications. BackPSM regulates client to send and receive packets in batches and coordinates multiple clients to communicate at different slots (i.e., beacon interval). The core problem in BackPSM is how to coordinate client without incurring extra traffic overheads. To handle the problem, we propose a novel paradigm, Out-of-Band Communication (OBC), for client-to-client direct communications. OBC exploits the Traffic Indication Map (TIM) field of Wi-Fi Beacon to create a free side-channel between clients. It is based upon the observation that a client may control 1 → 0 appearing on TIM bit by locally regulating packet receiving operations. We adopt this 1 → 0 as the basic signal, and leverage the time length in between two signals to encode information. We demonstrate that OBC can be used to convey coordination information with close to 100% accuracy. We have implemented and evaluated BackPSM on a testbed. The results show that BackPSM can decode the traffic pattern of peers reliably using OBC, and establish collision-free schedules fast to achieve out-of-band coordination of client communications. BackPSM reduces screen-off energy by up to 60% and outperforms the state-of-the-art strategies by 16%-42%.

ACS Style

Xianjin Xia; Shining Li; Yu Zhang; Bingqi Li; Yuanqing Zheng; Tao Gu. Enabling Out-of-Band Coordination of Wi-Fi Communications on Smartphones. IEEE/ACM Transactions on Networking 2019, 27, 518 -531.

AMA Style

Xianjin Xia, Shining Li, Yu Zhang, Bingqi Li, Yuanqing Zheng, Tao Gu. Enabling Out-of-Band Coordination of Wi-Fi Communications on Smartphones. IEEE/ACM Transactions on Networking. 2019; 27 (2):518-531.

Chicago/Turabian Style

Xianjin Xia; Shining Li; Yu Zhang; Bingqi Li; Yuanqing Zheng; Tao Gu. 2019. "Enabling Out-of-Band Coordination of Wi-Fi Communications on Smartphones." IEEE/ACM Transactions on Networking 27, no. 2: 518-531.

Journal article
Published: 09 January 2019 in Sensors
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Perimeter barriers can provide intrusion detection for a closed area. It is efficient for practical applications, such as coastal shoreline monitoring and international boundary surveillance. Perimeter barrier coverage construction in some regions of interest with irregular boundaries can be represented by its minimum circumcircle and every point on the perimeter can be covered. This paper studies circle barrier coverage in Bistatic Radar Sensor Network (BRSN) which encircles a region of interest. To improve the coverage quality, it is required to construct a circle barrier with a predefined width. Firstly, we consider a BR deployment problem to constructing a single BR circular barrier with minimum threshold of detectability. We study the optimized BR placement patterns on the single circular ring. Then the unit costs of the BR sensor are taken into account to derive the minimum cost placement sequence. Secondly, we further consider a circular BR barrier with a predefined width, which is wider than the breadth of Cassini oval sensing area with minimum threshold of detectability. We propose two segment strategies to efficiently divide a circular barrier to several adjacent sub-ring with some appropriate width: Circular equipartition strategy and an adaptive segmentation strategy. Finally, we propose approximate optimization placement algorithms for minimum cost placement of BR sensor for circular barrier coverage with required width and detection threshold. We validate the effectiveness of the proposed algorithms through theory analysis and extensive simulation experiments.

ACS Style

Xianghua Xu; Chengwei Zhao; Tingcong Ye; Tao Gu. Minimum Cost Deployment of Bistatic Radar Sensor for Perimeter Barrier Coverage. Sensors 2019, 19, 225 .

AMA Style

Xianghua Xu, Chengwei Zhao, Tingcong Ye, Tao Gu. Minimum Cost Deployment of Bistatic Radar Sensor for Perimeter Barrier Coverage. Sensors. 2019; 19 (2):225.

Chicago/Turabian Style

Xianghua Xu; Chengwei Zhao; Tingcong Ye; Tao Gu. 2019. "Minimum Cost Deployment of Bistatic Radar Sensor for Perimeter Barrier Coverage." Sensors 19, no. 2: 225.

Conference paper
Published: 01 January 2019 in Proceedings of the 52nd Hawaii International Conference on System Sciences
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ACS Style

Mohammad Saidur Rahman; Ibrahim Khalil; Xun Yi; Tao Gu. A Novel Privacy Preserving Search Technique for Stego Data in Untrusted Cloud. Proceedings of the 52nd Hawaii International Conference on System Sciences 2019, 1 .

AMA Style

Mohammad Saidur Rahman, Ibrahim Khalil, Xun Yi, Tao Gu. A Novel Privacy Preserving Search Technique for Stego Data in Untrusted Cloud. Proceedings of the 52nd Hawaii International Conference on System Sciences. 2019; ():1.

Chicago/Turabian Style

Mohammad Saidur Rahman; Ibrahim Khalil; Xun Yi; Tao Gu. 2019. "A Novel Privacy Preserving Search Technique for Stego Data in Untrusted Cloud." Proceedings of the 52nd Hawaii International Conference on System Sciences , no. : 1.

Journal article
Published: 09 November 2018 in IEEE Transactions on Mobile Computing
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Light-to-Camera Communications (LCC) have emerged as a new wireless communication technology with great potential to benefit a broad range of applications. However, the existing LCC systems either require cameras directly facing to the lights or can only communicate over a single link, resulting in low throughputs and being fragile to ambient illuminant interference. We present HYCACO, a novel LCC system, which enables multiple light emitting diodes (LEDs) with an unaltered camera to communicate via the non-line-of-sight (NLoS) links. Different from other NLoS LCC systems, the proposed scheme is resilient to the complex indoor luminous environment. HYCACO can decode the messages by exploring the mixed reflected optical signals transmitted from multiple LEDs. By further exploiting the rolling shutter mechanism, we present the optimal optical frequencies and camera exposure duration selection strategy to achieve the best performance. We built a hardware prototype to demonstrate the efficiency of the proposed scheme under different application scenarios. The experimental results show that the system throughput reaches 4.5 kbps on iPhone 6s with three transmitters. With the robustness, improved system throughput and ease of use, HYCACO has great potentials to be used in a wide range of applications such as advertising, tagging objects, and device certifications.

ACS Style

Fan Yang; Shi-Ning Li; Zhe Yang; Cheng Qian; Tao Gu. Spatial Multiplexing for Non-Line-of-Sight Light-to-Camera Communications. IEEE Transactions on Mobile Computing 2018, 18, 2660 -2671.

AMA Style

Fan Yang, Shi-Ning Li, Zhe Yang, Cheng Qian, Tao Gu. Spatial Multiplexing for Non-Line-of-Sight Light-to-Camera Communications. IEEE Transactions on Mobile Computing. 2018; 18 (11):2660-2671.

Chicago/Turabian Style

Fan Yang; Shi-Ning Li; Zhe Yang; Cheng Qian; Tao Gu. 2018. "Spatial Multiplexing for Non-Line-of-Sight Light-to-Camera Communications." IEEE Transactions on Mobile Computing 18, no. 11: 2660-2671.

Conference paper
Published: 05 November 2018 in Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services
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ACS Style

Yao Wang; Wan-Dong Cai; Tao Gu; Wei Shao; Ibrahim Khalil; Xianghua Xu. GazeRevealer. Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services 2018, 254 -263.

AMA Style

Yao Wang, Wan-Dong Cai, Tao Gu, Wei Shao, Ibrahim Khalil, Xianghua Xu. GazeRevealer. Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services. 2018; ():254-263.

Chicago/Turabian Style

Yao Wang; Wan-Dong Cai; Tao Gu; Wei Shao; Ibrahim Khalil; Xianghua Xu. 2018. "GazeRevealer." Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services , no. : 254-263.

Journal article
Published: 02 November 2018 in IEEE Access
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This paper presents the design and implementation of BTrack, a new approach for location tracking on mountain roads. It is as accurate as the GPS on common smartphones, but costs much less energy. To design such a location system, we carried out a nation-wide online survey to confirm the desirability for low power location tracking system, and the result is positive. Then, we proposed BTrack, and it makes two key technical contributions. The first is to propose a dynamic transition matrix Hidden Markov Model to combine the barometer and accelerometer reading hints for estimating the location of the user. The second is to design some novel techniques for parameter estimation, and proposed an adaptive algorithm to reduce the computational complexity. The field studies show that the accuracy of BTrack is no worse than GPS in 56% cases, meanwhile, the energy consumption is only about 30%. Compared to the existing works, BTrack is more suitable for location tracking on mountain roads.

ACS Style

Haibo Ye; Wenhua Yang; Yunyu Yao; Tao Gu; Zhiqiu Huang. BTrack: Using Barometer for Energy Efficient Location Tracking on Mountain Roads. IEEE Access 2018, 6, 66998 -67009.

AMA Style

Haibo Ye, Wenhua Yang, Yunyu Yao, Tao Gu, Zhiqiu Huang. BTrack: Using Barometer for Energy Efficient Location Tracking on Mountain Roads. IEEE Access. 2018; 6 (99):66998-67009.

Chicago/Turabian Style

Haibo Ye; Wenhua Yang; Yunyu Yao; Tao Gu; Zhiqiu Huang. 2018. "BTrack: Using Barometer for Energy Efficient Location Tracking on Mountain Roads." IEEE Access 6, no. 99: 66998-67009.

Journal article
Published: 23 October 2018 in IEEE Internet of Things Journal
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Recent years have witnessed advances of Internet of Things (IoT) technologies and their applications to enable contactless sensing and elderly care in smart homes. Continuous and real-time respiration monitoring is one of the important applications to promote assistive living for elders during sleep and attracted wide attention in both academia and industry. Most of the existing respiration monitoring systems require expensive and specialized devices to sense chest displacement. However, chest displacement is not a direct indicator of breathing and thus false detection may often occur. In this paper, we design and implement a real-time and contactless respiration monitoring system by directly sensing the exhaled airflow from breathing using ultrasound signals with off-the-shelf speaker and microphone. Exhaled airflow from breathing can be regarded as air turbulence, which scatters the sound wave and results in Doppler effect. Our system works as an acoustic radar which transmits sound wave and detects the Doppler effect caused by breathing airflow. We mathematically model the relationship between the Doppler frequency change and the direction of breathing airflow. Based on this model, we design a Minimum Description Length (MDL) based algorithm to effectively capture the Doppler effect caused by exhaled airflow. We conduct extensive experiments with 25 participants (7 elders, 2 young kids and 16 adults, including 11 females and 14 males) in four different rooms. The participants take four different sleep postures (lying on one’s back, on right/left side and on one’s stomach) in different positions of the bed. Experiment results show that our system achieves a median error lower than 0.3 breaths/min (2%) for respiration monitoring and can accurately identify Apnea. The results also demonstrate that the system is robust to different respiration styles (shallow, normal and deep), respiration rate variation, ambient noise, sensing distance variation (within 0.7 m) and transmitted signal frequency variation.

ACS Style

Tianben Wang; Daqing Zhang; Leye Wang; Yuanqing Zheng; Tao Gu; Bernadette Dorizzi; Xingshe Zhou. Contactless Respiration Monitoring Using Ultrasound Signal With Off-the-Shelf Audio Devices. IEEE Internet of Things Journal 2018, 6, 2959 -2973.

AMA Style

Tianben Wang, Daqing Zhang, Leye Wang, Yuanqing Zheng, Tao Gu, Bernadette Dorizzi, Xingshe Zhou. Contactless Respiration Monitoring Using Ultrasound Signal With Off-the-Shelf Audio Devices. IEEE Internet of Things Journal. 2018; 6 (2):2959-2973.

Chicago/Turabian Style

Tianben Wang; Daqing Zhang; Leye Wang; Yuanqing Zheng; Tao Gu; Bernadette Dorizzi; Xingshe Zhou. 2018. "Contactless Respiration Monitoring Using Ultrasound Signal With Off-the-Shelf Audio Devices." IEEE Internet of Things Journal 6, no. 2: 2959-2973.

Journal article
Published: 16 October 2018 in IEEE Transactions on Mobile Computing
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Cross-Technology Interference affects the operation of low-power ZigBee networks, especially under severe WiFi interference. Accurate corruption estimation is very important to improve the resilience of ZigBee transmissions. However, there are many limitations in existing approaches such as low accuracy, high overhead, and requirement of hardware modification. In this paper, we propose an accurate corruption estimation approach, AccuEst, which utilizes per-byte SINR (Signal-to-Interference-and-Noise Ratio) to detect corruption. We combine the use of pilot symbols with per-byte SINR to improve corruption detection accuracy, especially in highly noisy environments (i.e., noise and interference are at the same level). We extract pilot symbols by leveraging protocol signatures. In addition, we design an adaptive pilot instrumentation scheme to strike a good balance between accuracy and overhead. We implement AccuEst on the TinyOS 2.1.1/TelosB platform and evaluate its performance through extensive experiments. Results show that AccuEst improves corruption detection accuracy by 79.4% on average compared with state-of-the-art approach (i.e., CARE) in highly noisy environments. In addition, AccuEst reduces pilot overhead by 83.7% on average compared to the traditional pilot-based approach. We implement AccuEst in a coding-based transmission protocol, and results show that with AccuEst, the packet delivery ratio is improved by 22.1% on average.

ACS Style

Gonglong Chen; Wei Dong; Zhiwei Zhao; Tao Gu. Accurate Corruption Estimation in ZigBee under Cross-Technology Interference. IEEE Transactions on Mobile Computing 2018, 18, 2243 -2256.

AMA Style

Gonglong Chen, Wei Dong, Zhiwei Zhao, Tao Gu. Accurate Corruption Estimation in ZigBee under Cross-Technology Interference. IEEE Transactions on Mobile Computing. 2018; 18 (10):2243-2256.

Chicago/Turabian Style

Gonglong Chen; Wei Dong; Zhiwei Zhao; Tao Gu. 2018. "Accurate Corruption Estimation in ZigBee under Cross-Technology Interference." IEEE Transactions on Mobile Computing 18, no. 10: 2243-2256.

Conference paper
Published: 18 September 2018 in Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
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Person identification technology recognizes individuals by exploiting their unique, measurable physiological and behavioral characteristics. However, the state-of-the-art person identification systems have been shown to be vulnerable, e.g., anti-surveillance prosthetic masks can thwart face recognition, contact lenses can trick iris recognition, vocoder can compromise voice identification and fingerprint films can deceive fingerprint sensors. EEG (Electroencephalography)-based identification, which utilizes the user's brainwave signals for identification and offers a more resilient solution, has recently drawn a lot of attention. However, the state-of-the-art systems cannot achieve similar accuracy as the aforementioned methods. We propose MindID, an EEG-based biometric identification approach, with the aim of achieving high accuracy and robust performance. At first, the EEG data patterns are analyzed and the results show that the Delta pattern contains the most distinctive information for user identification. Next, the decomposed Delta signals are fed into an attention-based Encoder-Decoder RNNs (Recurrent Neural Networks) structure which assigns varying attention weights to different EEG channels based on their importance. The discriminative representations learned from the attention-based RNN are used to identify the user through a boosting classifier. The proposed approach is evaluated over 3 datasets (two local and one public). One local dataset (EID-M) is used for performance assessment and the results illustrate that our model achieves an accuracy of 0.982 and significantly outperforms the state-of-the-art and relevant baselines. The second local dataset (EID-S) and a public dataset (EEG-S) are utilized to demonstrate the robustness and adaptability, respectively. The results indicate that the proposed approach has the potential to be widely deployed in practical settings.

ACS Style

Xiang Zhang; Lina Yao; Salil S. Kanhere; Yunhao Liu; Tao Gu; Kaixuan Chen. MindID. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2018, 2, 1 -23.

AMA Style

Xiang Zhang, Lina Yao, Salil S. Kanhere, Yunhao Liu, Tao Gu, Kaixuan Chen. MindID. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 2018; 2 (3):1-23.

Chicago/Turabian Style

Xiang Zhang; Lina Yao; Salil S. Kanhere; Yunhao Liu; Tao Gu; Kaixuan Chen. 2018. "MindID." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, no. 3: 1-23.

Journal article
Published: 25 May 2018 in Sensors
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The altitude of a moving user is important context information for mobile technologies and applications. However, with the increasing pervasiveness of smartphones and abundant mobile applications, developers and users have gradually discovered that the height is more useful than altitude in many situations. The height is often a relative value, which is the vertical distance to the ground rather than the vertical distance to sea level, and we believe that it is useful in many applications, such as localization/navigation, sport/health and tourism/travel. In this paper, we first carried out a nation-wide online survey to confirm the desirability for the height information in mobile applications, and the result is positive. Then, we proposed HiMeter, an effective and accurate approach to calculating the height of the smartphone. HiMeter makes use of a low-power barometer on the smartphone and does not require GPS or back-server support. We concentrate on the vertical moving pattern of the user and designed several novel techniques, resulting in HiMeter not needing any reference points, and the complex process of calculating the absolute altitude can be avoided. The field studies show that HiMeter can achieve an accuracy of within 5 m in 90% of cases indoors and an accuracy of 10 m in 83% of cases outdoors. Compared to the existing works, HiMeter is more accurate and practical and is more suitable for usage in many mobile applications.

ACS Style

Haibo Ye; Kai Dong; Tao Gu. HiMeter: Telling You the Height Rather than the Altitude. Sensors 2018, 18, 1712 .

AMA Style

Haibo Ye, Kai Dong, Tao Gu. HiMeter: Telling You the Height Rather than the Altitude. Sensors. 2018; 18 (6):1712.

Chicago/Turabian Style

Haibo Ye; Kai Dong; Tao Gu. 2018. "HiMeter: Telling You the Height Rather than the Altitude." Sensors 18, no. 6: 1712.

Preprint
Published: 17 May 2018
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Multimodal features play a key role in wearable sensor-based human activity recognition (HAR). Selecting the most salient features adaptively is a promising way to maximize the effectiveness of multimodal sensor data. In this regard, we propose a "collect fully and select wisely" principle as well as an interpretable parallel recurrent model with convolutional attentions to improve the recognition performance. We first collect modality features and the relations between each pair of features to generate activity frames, and then introduce an attention mechanism to select the most prominent regions from activity frames precisely. The selected frames not only maximize the utilization of valid features but also reduce the number of features to be computed effectively. We further analyze the accuracy and interpretability of the proposed model based on extensive experiments. The results show that our model achieves competitive performance on two benchmarked datasets and works well in real life scenarios.

ACS Style

Kaixuan Chen; Lina Yao; Xianzhi Wang; Dalin Zhang; Tao Gu; Zhiwen Yu; Zheng Yang. Interpretable Parallel Recurrent Neural Networks with Convolutional Attentions for Multi-Modality Activity Modeling. 2018, 1 .

AMA Style

Kaixuan Chen, Lina Yao, Xianzhi Wang, Dalin Zhang, Tao Gu, Zhiwen Yu, Zheng Yang. Interpretable Parallel Recurrent Neural Networks with Convolutional Attentions for Multi-Modality Activity Modeling. . 2018; ():1.

Chicago/Turabian Style

Kaixuan Chen; Lina Yao; Xianzhi Wang; Dalin Zhang; Tao Gu; Zhiwen Yu; Zheng Yang. 2018. "Interpretable Parallel Recurrent Neural Networks with Convolutional Attentions for Multi-Modality Activity Modeling." , no. : 1.

Conference paper
Published: 01 April 2018 in IEEE INFOCOM 2018 - IEEE Conference on Computer Communications
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Wireless network simulation is a fundamental service aiming at providing controlled and repeatable environment for protocol design, performance testing, etc. The existing simulators focus on reproducing the packet behaviors on individual links. However, as observed in some recent works, individual link behaviors alone are not enough to characterize the protocol performance. As a result, while the existing works can mimic the link behaviors very closely, they often fail to simulate protocol level performance. In this paper, we propose a novel performance-aware simulation approach which can preserve not only the link-level behaviors but also the performance-level behaviors. We first devise an accurate performance model by combining link quality and the spatial-temporal link correlation. Based on the performance modeling, we then propose a Performance Aware Hidden Markov Model (PA-HMM), where the protocol performance is directly fed into the Markov state transitions. PA-HMM is able to simulate both link-level behaviors and high-level protocol performance. We conduct extensive testbed and simulation experiments with broadcast and anycast protocols. The results show that compared to the state-of-the-art work, 1) the performance model is able to accurately characterize wireless communication performance and 2) the protocol performance is closely simulated as compared to the empirical results.

ACS Style

Zhiwei Zhao; Wei Dong; Geyong Min; Gonglong Chen; Tao Gu; Jiajun Bu. Towards Repeatable Wireless Network Simulation Using Performance Aware Markov Model. IEEE INFOCOM 2018 - IEEE Conference on Computer Communications 2018, 2168 -2176.

AMA Style

Zhiwei Zhao, Wei Dong, Geyong Min, Gonglong Chen, Tao Gu, Jiajun Bu. Towards Repeatable Wireless Network Simulation Using Performance Aware Markov Model. IEEE INFOCOM 2018 - IEEE Conference on Computer Communications. 2018; ():2168-2176.

Chicago/Turabian Style

Zhiwei Zhao; Wei Dong; Geyong Min; Gonglong Chen; Tao Gu; Jiajun Bu. 2018. "Towards Repeatable Wireless Network Simulation Using Performance Aware Markov Model." IEEE INFOCOM 2018 - IEEE Conference on Computer Communications , no. : 2168-2176.