News and Announcements

  • 11/2018
    One paper on real-time systems is accepted by IEEE TPDS.
  • 11/2018
    Attended NSF CPS PI Meeting 2018 and presented our work on battery management.
  • 11/2018
    One UK patent on battery management is granted.
  • 11/2018
    One paper on battery management is accepted by DATE'19.
  • 10/2018
    Dr. Eugene Chai from NEC Labs America visited us.
  • 10/2018
    One paper on vehicle diagnostics is accepted by ACM MOBICOM'19.
  • 10/2018
    One paper on battery management is accepted by ACM TOSN.
  • 09/2018
    Attended the Workshop on Next Genereation Cyber-Physical Systems at University of Virginia.
  • 08/2018
    Dr. Yuanchao Shu from Microsoft Research visited us.
  • 08/2018
    Dr. Xiaoen Ju from Google visited us.
  • 06/2018
    Visited UCSD.
  • 05/2018
    Visited GM at Detroit.
  • 05/2018
    One paper on supercapacitor charging is accepted by IEEE TEC.
  • 04/2018
    Dr. Shige Wang from GM visited us.
  • 03/2018
    One paper on faulty data detection is accepted by IEEE ICDCS'18.
  • 02/2018
    Dr. Cong Liu from UTDallas visited us.
  • 01/2018
    Dr. Huan Feng from Facebook visited us.

Academic Positions

  • Present 2017

    Assistant Professor

    University of Colorado Denver, Denver, CO, U.S.

  • 2017 2014

    Research Fellow

    University of Michigan, Ann Arbor, MI, U.S.

  • 2014 2012

    Research Scientist

    Singapore University of Technology and Design, Singapore

  • 2012 2009

    Research Assistant

    University of Victoria, Victoria, BC, Canada

Education & Training

  • Ph.D.

    Ph.D. in Computer Science

    Nankai University, Tianjin, China

  • B.Eng.

    B.Eng. in Computer Science

    Tianjin University, Tianjin, China

Honors and Awards

  • ACM MobiSys'17
    Best Poster Award
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    Charge My Phone As I Instruct.
    Liang He, Yu-Chih Tung, and Kang G. Shin
    The 15th ACM International Conference on Mobile Systems, Applications, and Services, Niagara Falls, NY, USA, 2017.
  • EAI QShine'14
    Best Paper Award
    image
    Exploiting Time of Charge to Achieve Collision-Free Communications in WRSN.
    Yuelong Tian, Peng Cheng, Liang He, Yu Gu, and Jiming Chen.
    The 10th International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, Rhodes, Greece, August, 2014.
  • IEEE GLOBECOM'11
    Best Paper Award
    image
    Analysis on Data Collection with Multiple Mobile Elements in Wireless Sensor Networks.
    Liang He, Jianping Pan, and Jingdong Xu.
    The 2011 IEEE Global Communications Conference (IEEE GLOBECOM'11), Houston, USA, Dec. 2011.
  • IEEE WCSP'11
    Best Paper Award
    image
    Adaptive Mobility-Assisted Data Collection in Wireless Sensor Networks.
    Liang He, Jun Tao, Jianping Pan, and Jingdong Xu.
    The 2011 International Conference on Wireless Communications and Signal Processing (IEEE WCSP'11), Nanjing, China, Nov. 2011.

Research Projects

  • image

    Diagnosing Vehicles with Cyber-Physical Approaches

    Diagnosing vehicles by exploiting their physical behaviors in the cyber space.

    In this project, we aim to improve the reliability and safety of vehcile systems by designing and implementing novel cyber-physical solutions for on-board diagnostics. This project is in close collaboration with General Motors, SETI Institute, Microsoft Research, and the HyberLynx team at CUDenver. This project is partly supported by the Comcast Media and Technology Center at CUDenver.

    Related Publications at: MobiCom'19.

  • image

    Relaxation-Assisted Battery Management

    Resting batteries to improve their performance in reliability, capacity, and lifetime.

    The prevalence of battery-powered systems such as electric vehicles, smartphones, and IoT devices has made batteries crucial to everyone’s daily life and business. Battery health, however, degrades over time, not only decreasing system reliability such as unexpected system shutoffs, but also causing overheating/gassing which, in turn, increases safety risks such as thermal runaway or even battery fire/explosion. To address these problems, we must monitor, prognose, and optimize battery health throughout the physical system life. However, existing battery management systems (BMSes) are usually treated as complementary system components attached/embedded to/in batteries, and are unable to make optimal health management decisions adaptively based on system dynamics or user requirements. Our approach tightly integrates the cyber (battery management software) and the physical (sensing of battery state) to enable significant improvements in battery life and performance. Specifically, we will develop R-AWARE, a recovery period-assisted battery health management that schedules system operation while considering both system/user requirements and battery health. R-AWARE will improve battery health via relaxation-aware battery scheduling of battery charging/discharging, and recovery-based thermal control. It will advance the science of CPS by uncovering a thorough understanding of battery recovery and exploiting it via a recovery-aware scheduler during system operation. This project is partly supported by NSF under CNS-1739577.

    Related Publications at: TEC'18, MobiSys'17, TMC'17, ICCPS'17, ICCPS'16.

  • image

    Reconfigurable Battery Packs

    Actively adjusting the connectivity among invidivual battery cells in large-scale battery packs.

    Recent progress in battery technology has made it possible to use batteries to power various physical platforms, such as ground/air/water vehicles. These platforms require hundreds/thousands of battery cells to meet their power and energy needs. Of these, automobiles, locomotives, and unmanned air vehicles (UAVs) face the most stringent environmental challenges. In particular, and of special importance to the automotive industry, is the transition from conventional powertrains to (plug-in) hybrid and electric vehicles (EVs), all of which are subject to environmental and operational variations. Current state-of-the-art still needs significant improvements in the architecture and algorithms of battery management before achieving the desired levels of efficiency and performance. To meet this need, we aim to (i) design a dynamically reconfigurable energy storage system to withstand harsh internal and external stresses; (ii) develop cell-level thermal management algorithms; (iii) develop efficient, dependable charge and discharge scheduling algorithms; (iv) develop comprehensive, diagnostic/prognostic algorithms with system parameters adjusted for making optimal decisions; and (v) build a testbed, implement and evaluate the proposed architecture and algorithms on the testbed. This project is supported by NSF under CNS-1446117.

    Related Publications at: TOSN'18, TSG'18, TCPS'17, TSG'16, RTSS'16, e-Energy'16, ICCPS'15, ICCPS'14, RTSS'13.

  • image

    Mobile Agents in Wireless Sensor Networks

    Scheduling the limited mobility in sensor networks to improve the information gathering and network lifetime.

    In this project, we aim to effectively exploit the limited mobility in wireless sensor networks --- e.g., via robot, drones, and human beings --- to improve the information gathering in the network and replenish the energy supply of nodes thereof. We achieve these objectives with a combination of mathematical modeling, algoroihtm design, and system implementation.

    Related Publications at: TVT'16, TMC'15, TITS'15, TMC'14, MOBIHOC'14, INFOCOM'14, TMC'13, INFOCOM'12.

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Diagnosing Vehicles with Automotive Batteries.

Liang He, Linghe Kong, Ziyang Liu, Yuanchao Shu, and Cong Liu.
Conference PapersThe 25th ACM Annual international Conference on Mobile Computing and Networking (MobiCom'19), 2019.

Faulty Location Data Detection in Crowdsourcing: A Compressive Sensing Approach.

Bowen Wang, Linghe Kong, Liang He, Fan Wu, Jiadi Yu, and Guihai Chen.
Conference PapersThe 38th IEEE International Conference on Distributed Computing (ICDCS'18), Vienna, Austria, 2018.

PPM: Preamble and Postamble Based Multi-Packet Reception for Green ZigBee Communication.

Zhe Wang, Linghe Kong, Guihai Chen, and Liang He.
Conference PapersThe 2018 IEEE Global Communications Conference (GLOBECOM'18), Abu Dhabi, UAE, 2018.

Mrs.Z: Improving ZigBee Throughput via Multi-Rate Transmission.

Yifeng Cao, Linghe Kong, Liang He, Guihai Chen, Min-You Wu, and Tian He.
Conference PapersThe 25th IEEE International Conference on Network Protocols (ICNP'17), Toronto, ON, Canada, 2017.

iCharge: User-Interactive Charging of Mobile Devices.

Liang He, Yu-Chih Tung, and Kang Shin.
Conference PapersThe 15th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys'17), Niagara Falls, NY, USA, 2017.

Abstract

Charging mobile devices “fast” has been the focus of both industry and academia, leading to the deployment of various fast charging technologies. However, existing fast charging solutions are agnostic of users’ available time for charging their devices, causing early termination of the intended/- planned charging. This, in turn, accelerates the capacity fading of device battery and thus shortens the device operation. In this paper, we propose a novel user-interactive charging paradigm, called iCharge, that tailors the device charging to the user’s real-time availability and need. The core of iCharge is a relaxation-aware (R-Aware) charging algorithm that maximizes the charged capacity within the user’s available time and slows down the battery’s capacity fading. iCharge also integrates R-Aware with existing fast charging algorithms via a user-interactive interface, allowing users to choose a charging method based on their availability and need. We evaluate iCharge via extensive laboratory experiments and field-tests on Android phones, as well as user studies. R-Aware is shown to slow down the battery fading by more than 36% on average, and up to 60% in extreme cases, when compared to existing fast charging algorithms. This slowdown of capacity fading translates to, for instance, an up to 2-hour extension of the LTE time for a Nexus 5X phone after its use for 2 years, according to our trace-driven analysis of 976 device charging cases of 7 users over 3 months.

Battery State-of-Health Estimation for Mobile Devices.

Liang He, Eugene Kim, Kang Shin, Guozhu Meng and Tian He.
Conference PapersThe ACM/IEEE 8th International Conference on Cyber-Physical Systems (ICCPS'17), Pittsburgh, PA, USA, 2017.

Abstract

Insucient support of electric current sensing on commodity mobile devices leads to inaccurate estimation of their battery’s stateof-health (SoH), which, in turn, shuts them o‚ff unexpectedly and accelerates their battery fading. In this paper, we design V-BASH, a new battery SoH estimation method based only on their voltages and is compatible to commodity mobile devices. V-BASH is inspired by the physical phenomenon that the relaxing battery voltages correlate to battery SoH. Moreover, it is enabled on mobile devices with a common usage battery of most users frequently taking a long time to charge their devices. The design of V-BASH is guided by 2, 781 empirically collected relaxing voltage traces with 19 mobile device batteries. We evaluate V-BASH using both laboratory experiments and €eld tests on mobile devices, showing a <6% error in SoH estimation.

Accelerated RFID Classification and Counting.

Linsheng Ye, Linghe Kong, Guihai Chen, and Liang He.
Conference PapersThe 2nd International Workshop on Mobile Communications and Networking (IWMCN’17), Waterloo, ON, Canada, 2017.

Offline Guarantee and Online Management of Power Demand and Supply in Cyber-Physical Systems.

Eugene Kim, Jinkyu Lee, Liang He, Youngmoon Lee, and Kang G. Shin.
Conference PapersThe 37nd IEEE Real-Time Systems Symposium (RTSS'16), Porto, Portugal, 2016.

Resting Weak Cells to Improve Battery Packs' Capacity Delivery via Reconfiguration.

Liang He, Sunmin Kim, and Kang G. Shin.
Conference PapersThe 7th ACM International Conference on Future Energy Systems (e-Energy'16), Waterloo, Canada, 2016.

Abstract

Cell imbalance commonly found in large battery packs degrades their capacity delivery, especially for cells connected in series where the weakest cell dominates their overall capacity. In this paper, we present a case study of exploiting system reconfiguration to mitigate the cell imbalance in battery packs. Specifically, instead of using all the cells in a battery pack to support the load, selectively skipping cells to be discharged may actually enhance the pack’s capacity delivery. Based on this observation, we propose CSR, a Cell Skipping-assisted Reconfiguration algorithm that identifies the system configuration with (near)-optimal capacity delivery. We evaluate CSR using large-scale emulation based on empirically collected discharge traces of 40 Lithium-ion cells. CSR is shown to achieve close-to-optimal capacity delivery when the cell imbalance in the battery pack is low and improve the capacity delivery by up to 94% in case of high imbalance.

∗-Aware Charging of Lithium-ion Battery Cells.

Liang He, Sunmin Kim, and Kang G. Shin.
Conference PapersThe ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS'16), Vienna, Austria, 2016.

Abstract

Lithium-ion cells are widely used in various platforms, such as electric vehicles (EVs) and mobile devices. Complete and fast charging of cells has always been the goal for sustainable system operation. However, fast charging is not always the best solution, especially in view of a new finding that cells need to rest/relax after being charged with high current to avoid accelerated capacity fading. Fast charging for its typical Charge-and-Go scenario does not allow this needed relaxation. In this paper, we propose ∗-Aware, a novel charging algorithm which maximizes the charged capacity within the user-specified available charging time (i.e., user-awareness) while ensuring enough relaxation (i.e., cell-awareness). We motivate and evaluate ∗-Aware via extensive measurements over 10 months. ∗-Aware is shown to improve the charged capacity by 6.9–50.5% over other charging algorithms that also ensure relaxation, and by almost 3x in some extreme cases. Furthermore, ∗-Aware slows down the capacity fading by 49.55% when compared to fast charging.

Energy Synchronized Task Assignment in Rechargeable Sensor Networks.

Zheng Dong, Cong Liu, Lingkun Fu, Peng Cheng, Liang He, Yu Gu, Wei Gao, Chau Yuen, and Tian He.
Conference PapersThe IEEE International Conference on Sensing, Communication and Networking (SECON'16), London, UK, 2016.

Privacy-Preserving Compressive Sensing for Crowdsensing based Trajectory Recovery.

Linghe Kong, Liang He, Xiaoyang Liu, Yu Gu, Min-You Wu, and Xue Liu.
Conference PapersThe 35th IEEE International Conference on Distributed Computing Systems (ICDCS'15), Columbus, Ohio, USA, 2015.

A Computation Offloading Framework for Soft Real-Time Embedded Systems.

Yuchuan Liu, Cong Liu, Xia Zhang, Wei Gao, Liang He, Yu Gu.
Conference PapersThe 27th Euromicro Conference on Real-Time Systems (ECRTS'15), Lund, Sweden, 2015.

SHARE: SoH-Aware Reconfiguration to Enhance Deliverable Capacity of Large-Scale Battery Packs.

Liang He, Yu Gu, Cong Liu, Ting Zhu, and Kang G. Shin.
Conference PapersThe ACM/IEEE 6th International Conference on Cyber-Physical Systems (ICCPS'15), Seattle, USA, 2015.

Abstract

Unbalanced battery cells are known to significantly degrade the performance and reliability of a large-scale battery system. In this paper, we exploit emerging reconfigurable battery packs to mitigate the cell imbalance via the joint consideration of system reconfigurability and State-of-Health (SoH) of cells. Via empirical measurements and validation, we observe that a significantly larger amount of capacity can be delivered when cells with similar SoH levels are connected in series during discharging, which in turn extends the system operation time. Based on this observation, we propose two SoH-aware reconfiguration algorithms focusing on fully and partially reconfigurable battery packs, and prove their (near) optimality. We evaluate the proposed SoH-aware reconfiguration algorithms using both experiments and simulations. The algorithms are shown to deliver about 10–30% more capacity than SoH-oblivious configuration approaches.

Optimal Reader Location for Collision-Free Communication in WRSN.

Yuelong Tian, Peng Cheng, Liang He, Yu Gu, and Jiming Chen.
Conference PapersThe 2014 IEEE Global Communications Conference (GLOBECOM'14), Austin, TX, USA, 2014.

Exploiting Time of Charge to Achieve Collision-Free Communications in WRSN.

Yuelong Tian, Peng Cheng,Liang He, Yu Gu, and Jiming Chen.
Conference PapersThe 10th International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness (QShine'14), Rhodes, Greece, August, 2014.

Exploiting Sender-based Link Correlation in Wireless Sensor Networks.

Junghyun Jun, Long Cheng, Liang He, Yu Gu, and Ting Zhu.
Conference PapersThe 22nd IEEE International Conference on Network Protocols (ICNP'14), The Research Triangle, NC, October, 2014.

ESync: An Energy Synchronized Charging Protocol for Rechargeable Wireless Sensor Networks.

Liang He, Lingkun Fu, Likun Zheng, Yu Gu, Peng Cheng, Jiming Chen, and Jianping Pan.
Conference PapersThe 15th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc'14), Philadelphia, PA, USA, 2014.

Abstract

Different from energy harvesting which generates dynamic energy supplies, the mobile charger is able to provide stable and reliable energy supply for sensor nodes, and thus enables sustainable system operations. While previous mobile charging protocols either focus on the charger travel distance or the charging delay of sensor nodes, in this work we propose a novel Energy Synchronized Charging (ESync) protocol, which simultaneously reduces both of them. Observing the limitation of the Traveling Salesman Problem (TSP)-based solutions when nodes energy consumptions are diverse, we construct a set of nested TSP tours based on their energy consumptions, and only nodes with low remaining energy are involved in each charging round. Furthermore, we propose the concept of energy synchronization to synchronize the charging requests sequence of nodes with their sequence on the TSP tours. Experiment and simulation demonstrate ESync can reduce charger travel distance and nodes charging delay by about 30% and 40% respectively.

Analysis Techniques for Supporting Harmonic Real-Time Tasks with Suspensions.

Cong Liu, Jian-jia Chen, Liang He, Yu Gu.
Conference PapersThe 26th Euromicro Conference on Real-Time Systems (ECRTS'14), Madrid, Spain, Junly, 2014.

REPC: Reliable and Efficient Participatory Computing for Mobile Devices.

Zheng Dong, Linghe Kong, Peng Cheng, Liang He, Yu Gu, Lu Fang, Ting Zhu, and Cong Liu.
Conference PapersThe 11th IEEE International Conference on Sensing, Communication and Networking (SECON'14), Singapore, June, 2014.

Reconfiguration-Assisted Charging in Large-Scale Lithium-ion Battery Systems.

Liang He, Linghe Kong, Siyu Lin, Shaodong Ying, Yu Gu, Tian He, and Cong Liu.
Conference PapersThe 5th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS'14), Berlin, Germany, April, 2014.

Mobile-to-Mobile Energy Replenishment in Mission-Critical Robotic Sensor Networks.

Liang He, Peng Cheng, Yu Gu, Jianping Pan, Ting Zhu, and Cong Liu.
Conference PapersThe 33rd IEEE International Conference on Computer Communnications (INFOCOM'14) , Toronto, Canada, April, 2014.

Abstract

Recently, much research effort has been devoted to employing mobile chargers for energy replenishment of the robots in robotic sensor networks. Observing the discrepancy between the charging latency of robots and charger travel distance, we propose a novel tree-based charging schedule for the charger, which minimizes its travel distance without causing the robot energy depletion. We analytically evaluate its performance and show its closeness to the optimal solutions. Furthermore, through a queue-based approach, we provide theoretical guidance on the setting of the remaining energy threshold at which the robots request energy replenishment. This guided setting guarantees the feasibility of the tree-based schedule to return a depletion-free charging schedule. The performance of the tree-based charging schedule is evaluated through extensive simulations. The results show that the charger travel distance can be reduced by around 20%, when compared with the schedule that only considers the robot charging latency.

A Parallel Identification Protocol for RFID Systems.

Linghe Kong, Liang He, Yu Gu, Min-You Wu, and Tian He.
Conference PapersThe 33rd IEEE International Conference on Computer Communications (INFOCOM'14), Toronto, Canada, April, 2014.

Exploring Adaptive Reconfiguration to Optimize Energy Efficiency in Large-Scale Battery Systems.

Liang He, Lipeng Gu, Linghe Kong, Yu Gu, Cong Liu, and Tian He.
Conference PapersThe 34nd IEEE Real-Time Systems Symposium (RTSS'13), Vancouver, BC, Canada, December, 2013.

Abstract

Large-scale battery packs with hundreds/thousands of battery cells are commonly adopted in many emerging cyberphysical systems such as electric vehicles and smart micro-grids. For many applications, the load requirements on the battery systems are dynamic and could significantly change over time. How to resolve the discrepancies between the output power supplied by the battery system and the input power required by the loads is key to the development of large-scale battery systems. Traditionally, voltage regulators are often adopted to convert the voltage outputs to match loads’ required input power. Unfortunately, the efficiency of utilizing such voltage regulators degrades significantly when the difference between supplied and required voltages becomes large or the load becomes light. In this paper, we propose to address this problem via an adaptive reconfiguration framework for the battery system. By abstracting the battery system into a graph representation, we develop two adaptive reconfiguration algorithms to identify the desired system configurations dynamically in accordance with real-time load requirements. We extensively evaluate our design with empirical experiments on a prototype battery system, electric vehicle driving trace-based emulation, and battery discharge trace-based simulations. The evaluation results demonstrate that, depending on the system states, our proposed adaptive reconfiguration algorithms are able to achieve 1× to 5× performance improvement with regard to the system operation time.

On-Demand Charging in Wireless Sensor Networks: Theories and Applications.

Liang He, Yu Gu, Jianping Pan, and Ting Zhu.
Conference PapersThe 10th IEEE International Conferece on Mobile Ad-hoc and Sensor Systems (MASS'13), Hangzhou, China, October, 2013.

Evaluating Service Disciplines for Mobile Elements in Wireless Ad Hoc Sensor Networks.

Liang He, Zhe Yang, Jianping Pan, Lin Cai, and Jingdong Xu.
Conference PapersThe 31st IEEE International Conference on Computer Communications (INFOCOM'12), Orlando, USA, 2012.

Abstract

The introduction of mobile elements in wireless sensor networks creates a new dimension to reduce and balance the energy consumption for resource-constrained sensor nodes; however, it also introduces extra latency in the data collection process due to the limited mobility of mobile elements. Therefore, how to arrange and schedule the movement of mobile elements throughout the sensing field is of ultimate importance. In this paper, the online scenario where data collection requests arrive progressively is investigated, and the data collection process is modeled as an M/G/1/c–NJN queuing system, where NJN stands for nearest-job-next, a simple and intuitive service discipline. Based on this model, the performance of data collection is evaluated through both theoretical analysis and extensive simulation. The NJN discipline is further extended by considering the possibility of requests combination (NJNC). The simulation results validate our analytical models and give more insights when comparing with the first-come-first-serve (FCFS) discipline. In contrast to the conventional wisdom of the starvation problem, we reveal that NJN and NJNC have a better performance than FCFS, in both the average and more importantly the worst cases, which gives the much needed assurance to adopt NJN and NJNC in the design of more sophisticated data collection schemes for mobile elements in wireless ad hoc sensor networks, as well as many other similar scheduling application scenarios.

Sweeping and Active Skipping in Wireless Sensor Networks with Mobile Elements.

Jun Tao, Liang He, Yanyan Zhuang, Jianping Pan, and Maryam Ahmadi.
Conference PapersIEEE Global Communications Conference (GLOBECOM’12), California, USA, 2012.

A Partition-Based Data Collection Scheme in Wireless Sensor Networks with a Mobile Sink.

Maryam Ahmadi, Liang He, Jianping Pan, and Jingdong Xu.
Conference PapersThe 47th IEEE International Conference on Communications (ICC’12), Ottawa, Canada, 2012.

Analysis on Data Collection with Multiple Mobile Elements in Wireless Sensor Networks.

Liang He, Jianping Pan, and Jingdong Xu.
Conference PapersThe 2011 IEEE Global Communications Conference (IEEE GLOBECOM'11), Houston, USA, Dec. 2011.

Adaptive Mobility-Assisted Data Collection in Wireless Sensor Networks .

Liang He, Jun Tao, Jianping Pan, and Jingdong Xu.
Conference PapersThe 2011 International Conference on Wireless Communications and Signal Processing (IEEE WCSP'11), Nanjing, China, Nov. 2011.

Reducing Data Collection Latency in Wireless Sensor Networks with Mobile Elements.

Liang He, Jianping Pan, and Jingdong Xu.
Conference PapersThe 3rd International Workshop on Wireless sensor, Actuator and Robot networks (WiSARN’11), Shanghai, China, 2011.

An On-Demand Data Collection Scheme for Wireless Sensor Networks with Mobile Elements.

Liang He, Jianping Pan, and Jingdong Xu.
Conference PapersThe 46th IEEE International Conference on Communications (ICC’11), Kyoto, Japan, 2011.

Evaluating On-Demand Data Collection with Mobile Elements in Wireless Sensor Networks.

Liang He, Yanyan Zhuang, Jianping Pan, and Jingdong Xu.
Conference PapersThe 72nd IEEE Vehicular Technology Conference (VTC2010-FALL), Ottawa, Canada, 2010.

Optimize the Data Collection Path in WSNs Based on the Neighbor Count of Path Points.

Liang He, Guowei Huang, Yu Hua, Jing Yu, and Jingdong Xu.
Conference PapersIn CMC’10, Shenzhen, China, 2010.

LQATC: Link Quality Assured Topology Control Algorithm in Sensor Networks.

Liang He, Boyang Yu, and Jingdong Xu.
Conference PapersIn WiCOM’10, Chengdu, China, 2010.

Optimize Multiple Mobile Elements Touring in Wireless Sensor Networks.

Liang He, Jingdong Xu, and Yuntao Yu.
Conference PapersIn ISPA’09, Chengdu, China, 2009.

Genetic Algorithm based Length Reduction of a Mobile BS Path in WSNs.

Liang He, Jingdong Xu, Yuntao Yu, Miao Li, and Wenyao Zhao.
Conference PapersIn ICIS’09, Shanghai, China, 2009.

Optimizing the Path-Points Identification for Data Mules in Mobile WSNs.

Liang He, Jingdong Xu, Yuntao Yu, and Boxing Liu.
Conference PapersIn FCST’09, Shanghai, China, 2009.

Reducing the Path Length of a Mobile BS in WSNs.

Jingdong Xu, Liang He, Zhi Chen, Guowei Huang, and Tiantian Yuan.
Conference PapersIn FBIE’08, Wuhan, China, 2008.

Deep Analysis of Intending Peer-to-Peer Botnet.

Dafan Dong, Ying Wu, Liang He, Guowei Huang, and Gongyi Wu.
Conference PapersIn GCC’08, Shenzhen, China, 2008.

A General Analysis Framework for Soft Real-Time Tasks.

Zheng Dong, Cong Liu, Soroush Bateni, Zelun Kong, Liang He, Lingming Zhang, Ravi Prakash, and Yuqun Zhang.
Journal PaperTransactions on Parallel and Distributed Systems (TPDS), early access, 2018.

Extending Battery System Operation via Adaptive Reconfiguration.

Liang He, Linghe Kong, Yu Gu, Cong Liu, Tian He, and Kang G. Shin.
Journal PaperACM Transactions on Sensor Networks (TOSN), in press.

SoH-Aware Charging of Supercapacitors with Energy Efficiency Maximization.

Heng Li, Jun Peng, Yanhui Zhou, Jianping He, Zhiwu Huang, Liang He, and Jianping Pan.
Journal PaperIEEE Transactions on Energy Conversion (TEC), Vol. 33, No. 4, 2018.

On-Demand Mobile Data Collection in Cyber-Physical Systems.

Liang He, Linghe Kong, Jun Tao, Jingdong Xu, and Jianping Pan.
Journal PaperWireless Communications and Mobile Computing, Vol. 2018, No. 5913981, 2018.

SoH-Aware Reconfiguration in Battery Packs.

Liang He, Zhe Yang, Yu Gu, Cong Liu, Tian He, and Kang G. Shin.
Journal PaperIEEE Transactions on Smart Grid (TSG), Vol. 9, No. 4, pp. 3727-3735, 2018.

Abstract

Cell imbalance, a notorious but widely found issue, degrades the performance and reliability of large battery packs, especially for cells connected in series where their overall capacity delivery is dominated by the weakest cell. In this paper, we exploit the emerging reconfigurable battery packs to mitigate the cell imbalance via the joint consideration of system reconfigurability and State-of-Health (SoH) of cells. Via empirical measurements and validation, we observe that more capacity can be delivered when cells with similar SoH are connected in series during discharging. Based on this observation, we propose two SoHaware reconfiguration algorithms focusing on fully and partially reconfigurable battery packs, and prove their (near) optimality in capacity delivery. We evaluate the proposed reconfiguration algorithms analytically, experimentally, and via emulations, showing 10–60% improvement in capacity delivery when compared with SoH-oblivious approaches, especially when facing severe cell imbalance.

Low-Overhead WiFi Fingerprinting.

Junghyun Jun, Liang He, Yu Gu, Wenchao Jiang, Gaurav Kushwaha, Vipin A, Long Cheng, Cong Liu, and Ting Zhu,
Journal PaperIEEE Transactions on Mobile Computing (TMC), Vol. 17, No. 3, pp. 590-603, 2018.

Transmit Power Control for D2D Underlaid Cellular Networks Based on Statistical Features.

Peng Sun, Kang G. Shin, Hailin Zhang, and Liang He.
Journal PaperIEEE Transactions on Vehicular Technology (TVT), Vol. 66, No. 5, pp. 4110-4119, 2017.

A Case Study on Improving Capacity Delivery of Battery Packs via Reconfiguration.

Liang He, Sunmin Kim, and Kang G. Shin.
Journal PaperACM Transactions on Cyber-Physical Systems (TCPS), Vol. 1, No. 2, Feb. 2017.

Abstract

Cell imbalance in large battery packs degrades their capacity delivery, especially for cells connected in series where the weakest cell dominates their overall capacity. In this article, we present a case study of exploiting system reconfigurations to mitigate the cell imbalance in battery packs. Specifically, instead of using all the cells in a battery pack to support the load, selectively skipping cells to be discharged may actually enhance the pack’s capacity delivery. Based on this observation, we propose CSR, a Cell Skipping-assisted Reconfiguration algorithm that identifies the system configuration with (near)-optimal capacity delivery. We evaluate CSR using large-scale emulation based on empirically collected discharge traces of 40 lithium-ion cells. CSR achieves close-to-optimal capacity delivery when the cell imbalance in the battery pack is low and improves the capacity delivery by about 20% and up to 1x in the case of a high imbalance.

Battery-Aware Mobile Data Service.

Liang He, Guozhu Meng, Yu Gu, Cong Liu, Jun Sun, Ting Zhu, Yang Liu, and Kang. G. Shin.
Journal PaperIEEE Transactions on Mobile Computing (TMC), Vol. 16, No. 6, pp. 1544-1558, 2017.

Abstract

Significant research has been devoted to reduce the energy consumption of mobile devices, but how to increase their energy supply has received far less attention. Moreover, reducing the energy consumption alone does not always extend the device operation time due to a unique battery property — the capacity it delivers hinges critically upon how it is discharged. In this paper, we propose B-MODS, a novel design of battery-aware mobile data service on mobile devices. B-MODS constructs battery-friendly discharge patterns utilizing the recovery effect so as to increase the capacity delivered from batteries while meeting data service requirements. We implement B-MODS as an application layer library on the Android platform. Our experiments with diverse mobile devices under various application scenarios have shown that B-MODS increases the capacity delivery from the battery by up to 49.5%, with which an increase in the user-perceived data service utilities of up to 28.6% is observed.

ESync: Energy Synchronized Mobile Charging in Rechargeable Wireless Sensor Networks.

Lingkun Fu, Liang He, Peng Cheng, Yu Gu, Jianping Pan, and Jiming Chen.
Journal PaperIEEE Transactions on Vehicular Technology (TVT), Vol. 65, No. 9, pp. 7415-7431, 2016.

RAC: Reconfiguration-Assisted Charging in Large-Scale Lithium-ion Battery Systems.

Liang He, Linghe Kong, Siyu Lin, Shaodong Ying, Yu Gu, Tian He, and Cong Liu.
Journal PaperIEEE Transactions on Smart Grid (TSG), Vol. 7, No. 3, pp. 1420-1429, 2016.

Abstract

Large-scale lithium-ion battery packs are widely adopted in systems such as electric vehicles and energy backup in power grids. Due to factors such as manufacturing difference and heterogeneous discharging conditions, cells in the battery pack may have different statuses, such as diverse voltage levels. This cell diversity is commonly known as the cell imbalance issue. For the charging of battery packs, the cell imbalance not only early on terminates the charging process before all cells are fully charged, but also leads to different desired charging currents among cells. In this paper, based on the advancement in recon- figurable battery systems, we demonstrate how to utilize system reconfigurability to mitigate the impact of cell imbalance on an efficient charging process. With the proposed reconfigurationassisted charging (RAC), cells in the system are categorized according to their real-time voltages, and the charging process is performed in a category-by-category manner. To charge cells in a given category, a graph-based algorithm is presented to charge cells with their desired charging currents, respectively. We evaluate RAC through both experiments and simulations. The results demonstrate that the RAC increases the capacity charged into cells by about 25% and yields a dramatically reduced variance.

Evaluating the On-Demand Mobile Charging in Wireless Sensor Networks.

Liang He, Linghe Kong, Yu Gu, Jianping Pan, and Ting Zhu.
Journal PaperIEEE Transactions on Mobile Computing (TMC), Vol.14, No. 9, pp. 1861–1875, 2015.

Abstract

Recently, adopting mobile energy chargers to replenish the energy supply of sensor nodes in wireless sensor networks has gained increasing attention from the research community. Different from energy harvesting systems, the utilization of mobile energy chargers is able to provide more reliable energy supply than the dynamic energy harvested from the surrounding environment. While pioneering works on the mobile recharging problem mainly focus on the optimal offline path planning for the mobile chargers, in this work, we aim to lay the theoretical foundation for the on-demand mobile charging (DMC) problem, where individual sensor nodes request charging from the mobile charger when their energy runs low. Specifically, in this work, we analyze the on-demand mobile charging problem using a simple but efficient Nearest-Job-Next with Preemption (NJNP) discipline for the mobile charger, and provide analytical results on the system throughput and charging latency from the perspectives of the mobile charger and individual sensor nodes, respectively. To demonstrate how the actual system design can benefit from our analytical results, we present two examples on determining the essential system parameters such as the optimal remaining energy level for individual sensor nodes to send out their recharging requests and the minimal energy capacity required for the mobile charger. Through extensive simulation with real-world system settings, we verify that our analytical results match the simulation results well and the system designs based on our analysis are effective.

Achieving Collision-Free Communication by Time of Charge in WRSN.

Yuelong Tian, Peng Cheng, Liang He, Yu Gu, and Jiming Chen.
Journal PaperMobile Networks and Applications, pp. 1–11, 2015.

Finite-State Markov Modeling for High-Speed Railway Fading Channels.

Siyu Lin, Linghe Kong, Liang He, Ke Guan, Bo Ai, Zhangdui Zhong, and Cesar Briso-Rodriguez.
Journal PaperIEEE Antennas and Wireless Propagation Letters, Vol. 14, pp. 954–957, 2015.

Design of a Mobile Charging Service for Electric Vehicles in an Urban Environment.

Shisheng Huang, Liang He, Yu Gu, Kristin Wood, and Saif Benjaafar.
Journal PaperIEEE Transactions on Intelligent Transportation Systems (TITS). No. 99, pp. 1-12, 2014.

Temperature-Assisted Clock Synchronization and Self-Calibration for Sensor Networks.

Zhe Yang, Liang He, Lin Cai, and Jianping Pan.
Journal PaperIEEE Transactions on Wireless Communications (TWC), Vol. 13, No. 6, pp. 3419-3429, 2014.

Opportunistic Flooding in Low-Duty-Cycle Wireless Sensor Networks with Unreliable Links.

Shuo Guo, Liang He, Yu Gu, Bo Jiang, and Tian He.
Journal PaperIEEE Transactions on Computers (TC), Vol. 63, No. 11, pp. 2787-2802, 2014.

Achieving Energy Synchronized Communication in Energy-Harvesting Wireless Sensor Networks.

Yu Gu, Liang He, Ting Zhu, and Tian He.
Journal PaperACM Transactions on Embedded Computing Systems (TECS), Vol. 13, No. 68, 2014.

Evaluating Service Disciplines for On-Demand Mobile Data Collection in Sensor Networks.

Liang He, Zhe Yang, Jianping Pan, Lin Cai, Jingdong Xu, and Yu Gu.
Journal PaperIEEE Transactions on Mobile Computing (TMC), Vol. 13, No. 4, pp. 797-810, 2014.

Abstract

Mobility-assisted data collection in sensor networks creates a new dimension to reduce and balance the energy consumption for sensor nodes. However, it also introduces extra latency in the data collection process due to the limited mobility of mobile elements. Therefore, how to schedule the movement of mobile elements throughout the field is of ultimate importance. In this paper, the on-demand scenario where data collection requests arrive at the mobile element progressively is investigated, and the data collection process is modelled as an M=G=1=c-NJN queuing system with an intuitive service discipline of nearest-job-next (NJN). Based on this model, the performance of data collection is evaluated through both theoretical analysis and extensive simulation. NJN is further extended by considering the possible requests combination (NJNC). The simulation results validate our models and offer more insights when compared with the first-come-first-serve (FCFS) discipline. In contrary to the conventional wisdom of the starvation problem, we reveal that NJN and NJNC have better performance than FCFS, in both the average and more importantly the worst cases, which offers the much needed assurance to adopt NJN and NJNC in the design of more sophisticated data collection schemes, as well as other similar scheduling scenarios.

A Progressive Approach to Reducing Data Collection Latency in Wireless Sensor Networks with Mobile Elements.

Liang He, Jianping Pan, and Jingdong Xu.
Journal PaperIEEE Transactions on Mobile Computing (TMC), Vol. 12, No. 7, pp. 1308-1320, 2013.

Abstract

The introduction of mobile elements has created a new dimension to reduce and balance the energy consumption in wireless sensor networks. However, data collection latency may become higher due to the relatively slow travel speed of mobile elements. Thus, the scheduling of mobile elements, i.e., how they traverse through the sensing field and when they collect data from which sensor, is of ultimate importance and has attracted increasing attention from the research community. Formulated as the traveling salesman problem with neighborhoods (TSPN) and due to its NP-hardness, so far only approximation and heuristic algorithms have appeared in the literature, but the former only have theoretical value now due to their large approximation factors. In this paper, following a progressive optimization approach, we first propose a combine-skip-substitute (CSS) scheme, which is shown to be able to obtain solutions within a small range of the lower bound of the optimal solution. We then take the realistic multirate features of wireless communications into account, which have been ignored by most existing work, to further reduce the data collection latency with the multirate CSS (MR-CSS) scheme. Besides the correctness proof and performance analysis of the proposed schemes, we also show their efficiency and potentials for further extensions through extensive simulation.

Data Collection Latency in Wireless Sensor Networks with Multiple Mobile Elements.

Liang He, Jianping Pan, and Jingdong Xu.
Journal PaperAd Hoc & Sensor Wireless Networks (AHSWN), Vol. 18, No. 1-2, pp. 109-129, 2013.

Optimizing Data Collection Path in Sensor Networks with Mobile Elements.

Liang He, Zhi Chen, and Jingdong Xu.
Journal PaperInternational Journal of Automation and Computing, Vol. 8, No. 1, 2011.

Improved Topology Control Method in WSN.

Jingdong Xu, Liang He, Boyang Yu, Yuntao Yu, and Song Li.
Journal PaperComputer Engineering, Vol. 36, No. 16, pp: 85–87, 2010.

Improved Residual Energy Scan Monitoring Mechanism of for Sensors Nodes in WSN.

Jingdong Xu, Liang He, Xuefei Wang, Boxing Liu, and Xing Jin.
Journal PaperComputer Engineering, Vol. 36, No. 14, pp: 74–77, 2010.

Design of Wireless Sensor Network Based on ZigBee.

Jingdong Xu, Wenyao Zhao, Miao Li, and Liang He.
Journal PaperComputer Engineering, Vol. 36, No. 10, pp: 110–112, 2010.

Charge My Phone As I Instruct.

Liang He, Yu-Chih Tung, and Kang G. Shin
Demos and postersThe 15th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys'17), Niagara Falls, NY, USA, 2017.

Robust and undemanding wifi-fingerprint based indoor localization with independent access pointst.

Junghyun Jun, Suryadip Chakraborty, Liang He, Yu Gu, and Dharma P. Agrawal
Demos and postersProceedings of the Microsoft Indoor Localization Competition (IPSN), Seattle, WA, USA, 2015.

An Energy Synchronized Charging Protocol for Rechargeable Wireless Sensor Networks.

Lingkun Fu, Hao Liu, Liang He, Yu Gu, Peng Cheng, and Jiming Chen.
Demos and postersIn The 15th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc'14), Philadelphia, PA, USA, 2014.

Reconfiguration-based Energy Optimization in Battery Systems: a Testbed Prototype.

Liang He, Shaodong Ying and Yu Gu
Demos and postersIn The 34nd IEEE Real-Time Systems Symposium (RTSS'13), Vancouver, Canada, December, 2013.

Exploring Smartphone-based Participatory Computing to Improve Pervasive Surveillance.

Zheng Dong, Banghui Lu, Liang He, Peng Cheng, Yu Gu and Lu Fang.
Demos and postersIn the 11th ACM Conference on Embedded Networked Sensor System (SenSys'13), Rome, Italy, November, 2013.

Energy Synchronized Charging in Sensor Networks.

Liang He, Yu Gu, and Tian He.
Demos and postersThe 10th ACM Conference on Embedded Networked Sensor Systems (SenSys'12), Toronto, Canada, 2012.

Graduate Students

    • Aishwarya Mulkalwar, CSE, since Spring 2018
    • Debajit Kumar Sandilya, CSE, since Fall 2018

Undergraduate Students

    • Andrew Gras, EE, since Summer 2018
    • Aaron Zapiler, ME, since Fall 2018
    • Chanhee Shin, CSE, since Fall 2018
    • Kevin Macfarlane, CSE, since Fall 2018
    • Michael Hedrick, CSE, since Fall 2018
    • Cole Christenson, CSE, since Fall 2018
    • Alex Tarasov, CSE, since Fall 2018
    • Jennifer Guidotti, CSE, since Fall 2018

Editorship

    • Guest Editor: Concurrency and Computation: Practice and Experience

Organizing Committee Membership

    • Regional Program Chair, The 8th Annual IEEE Int. Conf. on CYBER Technology in Automation, Control, and Intelligent Systems (IEEE-CYBER 2018)
    • Publicity Co-Chair, The 7th International Workshop on Wireless Sensor, Actuator and Robot Networks (WiSARN 2013-SPRING)
    • Publicity Co-Chair, The 6th International Workshop on Wireless Sensor, Actuator and Robot Networks (WiSARN 2012-Fall)
  • 2018 10/19

    Self-organizing UAV Networks for Providing On-demand Sensing and LTE Connectivity to First Responders

    Dr. Eugene Chai, NEC Lab America

    Abstract: Autonomous multi-UAV networks will revolutionize the design of systems solutions for civil, entertainment, public services, security and other critical application areas. At NEC Labs, we are particularly interested in the application of such multi-UAV networks to public safety networks. Our goal is simple: how do we design, implement and deploy a reliable and flexible multi-UAV network that can meet the demands of first-responder networks? In this talk, I will introduce SkyLiTE, our multi-UAV network that is designed for public safety applications. SkyLiTE is one of the first efforts at a fully autonomous, untethered multi-UAV network that can be deployed on demand in challenging scenarios to achieve public safety mission objectives. Our SkyLiTE prototype consists of three important components: SkyHAUL, which is a high bandwidth, millimeter wave backhaul network that achieves 1Gbps of bandwidth across the entire multi-UAV network; SkyCORE, a UAV-optimized, lightweight LTE Evolved Packet Core network; and SkyRAN, a full-fledged LTE radio access network. SkyLiTE is deployed either to complement and augment existing terrestrial cellular networks in public safety scenarios, or as a standalone LTE network in areas not covered by fixed infrastructure.

  • 2018 08/31

    All Your GPS Are Belong To Us: Towards Stealthy Manipulation of Road Navigation Systems

    Dr. Yuanchao Shu, Microsoft Research

    Abstract: Mobile navigation services are used by billions of users around globe today. While GPS spoofing is a known threat, it is not yet clear if spoofing attacks can truly manipulate road navigation systems. In this work, we explore the feasibility of a stealthy manipulation attack against road navigation systems. The goal is to trigger the fake turn-by-turn navigation to guide the victim to a wrong destination without being noticed. Our key idea is to slightly shift the GPS location so that the fake navigation route matches the shape of the actual roads and trigger physically possible instructions. To demonstrate the feasibility, we perform controlled measurements by implementing a portable GPS spoofer and testing on real cars. The complete attack is validated by extensive trace-driven simulation and real-world driving tests. Deceptive user studies using a driving simulator also show that 95% of the participants follow the navigation to the wrong destination without recognizing the attack.

  • 2018 04/09

    Addressing Architecture Challenges for Real-Time Vision Processing in Automated Driving Systems

    Dr. Shige Wang, General Motors

    Abstract: Vision processing is a key component in automated driving systems. Most vision processing algorithms today, however, are not designed for safety-critical real-time applications. Considering these algorithms are typically both data- and computation-intensive and require advanced hardware platform, applying them to automated driving brings new architecture challenges. In this talk, I will discuss some architecture challenges and potential solutions to support the vision processing for real-time vehicle controls.

  • 2018 02/12

    Predictable GPGPU Computing in Safety-Critical Cyber-Physical Systems

    Dr. Cong Liu, University of Texas at Dallas

    Abstract: Graphic processing units (GPUs) have seen wide-spread use in several computing domains as they have the power to enable orders of magnitude faster and more energy-efficient execution of many applications. Unfortunately, it is not straightforward to reliably adopt GPUs in many safety-critical cyber-physical systems that require predictable timing correctness, one of the most important tenets in certification required for such systems. A key example is the advanced automotive system where timeliness of computations is an essential requirement of correctness due to the interaction with the physical world. In this talk, I will describe several system-level and algorithmic challenges and our developed solutions on ensuring predictable timing correctness in GPU-accelerated systems.

  • 2018 01/29

    Emerging Threats in the Mobile Ecosystem

    Dr. Huan Feng, Facebook

    Abstract: During the past decade, we are moving swiftly towards a mobile-centered world. This thriving mobile ecosystem builds upon the interplay of three important parties: the mobile user, OS, and app. These parties interact via designated interfaces many of which are newly invented for or introduced to the mobile platform. Nevertheless, as these new ways of interactions arise in the mobile ecosystem, what is enabled by these communication interfaces often violates the expectations of the communicating parties. This shakes the foundation of the mobile ecosystem and results in significant security and privacy hazards. In this talk, we describe our attempts to fill this gap by: 1.) securing the conversations between trusted parties, 2.) regulating the interactions between partially trusted parties, and 3.) defending the communications between untrusted parties. First, we deal with the case of two opposing parties, mobile OS and app, and analyze the Inter-Process Communication protocol (Binder) between them. We found that the OS is frequently making unrealistic assumptions on the validity (sanity) of transactions from apps, thus creating significant security hazards. We analyzed the root cause of this emerging attack surface and secured this interface by developing effective precautionary testing framework and runtime diagnostic tool. Then, we study the deficiency of how existing mobile user interact with app, a party he can only partially trust. We found that in the current mobile ecosystem, information about the same user in different apps can be easily shared and aggregated, which clearly violates the conditional trust mobile user has on each app. We address this issue by providing an OS-level extension that allows the user to track and control, during runtime, the potential flow of his information across apps. Last, we elaborate on how to secure the voice interaction channel between two trusted parties, mobile user and OS. The open nature of the voice channel makes applications that depend on voice interactions, such as voice assistants, difficult to secure and exposed to various attacks. We solve this problem by proposing the first system that provides continuous and usable authentication for voice commands. It takes advantage of the neck-surface acceleration to filter only those commands that originate from the voice of the owner.