uu.seUppsala University Publications
Change search
Refine search result
12 51 - 98 of 98
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 51.
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    On providing sink anonymity for wireless sensor networks2016In: Security and Communication Networks, ISSN 1939-0114, E-ISSN 1939-0122, Vol. 9, no 2, p. 77-86Article in journal (Refereed)
  • 52.
    Ngai, Edith C.-H.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Brandauer, Stephan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Shrestha, Amendra
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Vandikas, Konstantinos
    Ericsson Res, Kista, Sweden..
    Personalized Mobile-Assisted Smart Transportation2016In: 2016 Digital Media Industry And Academic Forum (DMIAF), 2016, p. 158-160Conference paper (Refereed)
    Abstract [en]

    Digital media covers larger parts of our daily lives nowadays. Mobile services enable a better connected society where citizens can easily access public services, discover events, and obtain important information in the city. We observe the popularity of mobile car sharing applications, such as Uber and Didi Dache. Mobile social applications provide new ways of developing and optimizing public transportation. In this paper, we present a mobile platform for timetable-free traveling. It can capture the traffic demand of citizens in real-time, and support efficient planning and scheduling for vehicles on-demand. At the moment, the platform is targeted for public bus services, but it has great potential to be extended for self-driving vehicles in the future.

  • 53.
    Ngai, Edith C.-H.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Gelenbe, Erol
    Humber, Gregory
    Information-Aware Traffic Reduction for Wireless Sensor Networks2009In: Proc. 34th Conference on Local Computer Networks, Piscataway, NJ: IEEE , 2009, p. 451-458Conference paper (Refereed)
  • 54.
    Ngai, Edith C.-H.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Gunningberg, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Quality-of-Information aware data collection for mobile sensor networks2012In: Proc. 10th International Conference on Pervasive Computing and Communications Workshops, IEEE Communications Society, 2012, p. 38-43Conference paper (Refereed)
  • 55.
    Ngai, Edith C.-H.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Gunningberg, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Quality-of-information-aware data collection for mobile sensor networks2014In: Pervasive and Mobile Computing, ISSN 1574-1192, E-ISSN 1873-1589, Vol. 11, p. 203-215Article in journal (Refereed)
    Abstract [en]

    Quality of information (QoI) in sensor networks measures information attributes such as precision, timeliness, completeness, and relevance of data ultimately delivered to users. It is a challenge to provide the required QoI in mobile sensor networks given the large scale and complexity of the networks with heterogeneous mobile and sensing devices. In this paper, we provide a comprehensive study on major QoI metrics for mobile sensor networks and discuss how QoI-aware data collection can be achieved. The cases with mobile sensors, mobile sinks, and mobile mules carrying data and their impact on QoI are discussed in detail. Mobility creates challenges in terms of timeliness but also opportunities in increased coverage and relevance. In a case study, we design a QoI-aware publish/subscribe system for mobile sensor networks. Users can subscribe to obtain information about events of interest by specifying the target area, sensing context, etc. The subscriptions and the sensing data are delivered to relevant sensors and users by location-based routing. We also discuss techniques that can be applied to further enhance the QoI in our publish/subscribe system. Simulation results demonstrate that the users can receive their subscribed data successfully with low communication overhead. Our publish/subscribe system can also handle mobility of clients smoothly without causing any data loss.

  • 56.
    Ngai, Edith C.-H.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Huang, He
    Liu, Jiangchuan
    Srivastava, Mani B.
    OppSense: Information sharing for mobile phones in sensing field with data repositories2011In: Proc. 8th IEEE Conference on Sensor, Mesh and Ad Hoc Communications and Networks, Piscataway, NJ: IEEE , 2011, p. 107-115Conference paper (Refereed)
  • 57.
    Ngai, Edith C.-H.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Liu, Jiangchuan
    Lyu, Michael R.
    An adaptive delay-minimized route design for wireless sensor–actuator networks2009In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 58, no 9, p. 5083-5094Article in journal (Refereed)
  • 58.
    Ngai, Edith C.-H.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Rodhe, Ioana
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    On providing location privacy for mobile sinks in wireless sensor networks2013In: Wireless networks, ISSN 1022-0038, E-ISSN 1572-8196, Vol. 19, no 1, p. 115-130Article in journal (Refereed)
  • 59.
    Ngai, Edith C.-H.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Rodhe, Ioana
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    On Providing Location Privacy for Mobile Sinks in Wireless Sensor Networks2009In: Proc. 12th ACM International Conference on Modeling, Analysis, and Simulation of Wireless and Mobile Systems, New York: ACM Press , 2009, p. 116-123Conference paper (Refereed)
  • 60.
    Ngai, Edith C.-H.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Srivastava, Mani B.
    Liu, Jiangchuan
    Context-aware sensor data dissemination for mobile users in remote areas2012In: Proc. 31st International Conference on Computer Communications: Mini-Conference, Piscataway, NJ: IEEE , 2012, p. 2711-2715Conference paper (Refereed)
  • 61.
    Ngai, Edith
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Dressler, Falko
    Univ Paderborn, Dept Comp Sci, D-33102 Paderborn, Germany.
    Leung, Victor
    Univ British Columbia, Vancouver, BC V6T 1Z4, Canada.
    Li, Mo
    Nanyang Technol Univ, Sch Comp Sci & Engn, Singapore 639798, Singapore.
    Guest Editorial Special Section on Internet-of-Things for Smart Cities and Urban Informatics2017In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 13, no 2, p. 748-750Article in journal (Other academic)
  • 62. Ngai, Edith
    et al.
    Gunningberg, Per
    Quality-of-Information Aware Data Collection for Mobile Sensor Networks2012Conference proceedings (editor) (Refereed)
  • 63.
    Ngai, Edith
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Ohlman, Börje
    Tsudik, Gene
    Uzun, Ersin
    Wählisch, Matthias
    Wood, Christopher A.
    Can we make a cake and eat it too?: A discussion of ICN security and privacy2017In: Computer communication review, ISSN 0146-4833, E-ISSN 1943-5819, Vol. 47, no 1, p. 49-54Article in journal (Other academic)
  • 64.
    Ngai, Edith
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Tsoi, Brittle
    Protecting Receiver Privacy in Routing for Wireless Sensor Networks2009In: Mobile and Wireless Network Security: MWNS 2009, Aachen, Germany: Shaker Verlag , 2009, p. 63-74Conference paper (Refereed)
  • 65.
    Ngai, Edith
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Zhou, Yangfan
    Lyu, Michael R.
    Liu, Jiangchuan
    A delay-aware reliable event reporting framework for wireless sensor–actuator networks2010In: Ad hoc networks, ISSN 1570-8705, E-ISSN 1570-8713, Vol. 8, no 7, p. 694-707Article in journal (Refereed)
  • 66. Niroumand, Kamyar
    et al.
    McNamara, Liam
    Swedish Institute of Computer Science.
    Goguev, Kiril
    Ngai, Edith
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    SADSense: Personalized Mobile Sensing for Seasonal Effects on Health2014In: Proc. 13th International Symposium on Information Processing in Sensor Networks, Piscataway, NJ: IEEE Press, 2014, p. 295-296Conference paper (Refereed)
  • 67. Pradeep, Guduru K.
    et al.
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    An adaptive cross-layer design for prioritized traffic in wireless communications2010In: Proc. 6th International Conference on Mobile Ad Hoc and Sensor Networks, Piscataway, NJ: IEEE , 2010, p. 203-206Conference paper (Refereed)
  • 68.
    Rensfelt, Olof
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Hermans, Frederik
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Voigt, Thiemo
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Ngai, Edith
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Nordén, Lars-Åke
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Gunningberg, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    SoNIC: Classifying and Surviving Interference in 802.15.4-based Sensor Networks2012Report (Other academic)
  • 69.
    Rodhe, Ioana
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Rohner, Christian
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    On location privacy and quality of information in participatory sensing2012In: Proc. 8th ACM Symposium on QoS and Security for Wireless and Mobile Networks, New York: ACM Press, 2012, p. 55-62Conference paper (Refereed)
    Abstract [en]

    Participatory sensing applications typically bind sensor data to locations. Location privacy preserving mechanisms protecting the location of users introduce therefore an uncertainty in the collected data distributions. We consider two strategies to reconstruct a data distribution after k-anonymity has been applied to the users' location information. We investigate how different parameters for the location privacy preserving mechanism influence both the quality of information and the location privacy of the users. Our results show that the cloak area resulted from applying k-anonymity has a higher impact on both the quality of information and the location privacy than the number of users, k, that are cloaked together.

  • 70. Ruan, Zheng
    et al.
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Liu, Jiangchuan
    Wireless sensor deployment for collaborative sensing with mobile phones2011In: Computer Networks, ISSN 1389-1286, E-ISSN 1872-7069, Vol. 55, no 15, p. 3224-3245Article in journal (Refereed)
  • 71. Ruan, Zheng
    et al.
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Liu, Jiangchuan
    Wireless sensor network deployment in mobile phones assisted environment2010In: Proc. 18th International Workshop on Quality of Service, Piscataway, NJ: IEEE , 2010, p. 9-Conference paper (Refereed)
  • 72.
    Sathyamoorthy, Peramanathan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Hu, Xiping
    Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China.; Chinese Univ Hong Kong, Shatin, Hong Kong, Peoples R China.
    Leung, Victor C. M.
    Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada.
    Profiling energy efficiency and data communications for mobile Internet of Things2017In: Wireless Communications & Mobile Computing, ISSN 1530-8669, E-ISSN 1530-8677, Vol. 17, article id 6562915Article in journal (Refereed)
  • 73.
    Sathyamoorthy, Peramanathan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Ngai, Edith
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Hu, Xiping
    Univ British Columbia, Dept Elect & Comp Engn, Vancouver, BC V5Z 1M9, Canada.
    Leung, Victor
    Univ British Columbia, Dept Elect & Comp Engn, Vancouver, BC V5Z 1M9, Canada.
    Energy Efficiency as an Orchestration Service for Mobile Internet of Things2015Conference paper (Refereed)
    Abstract [en]

    This paper proposes a novel power management solution for resource-constrained devices in the context of Internet of Things (IoT). We focus on smartphones in the IoT, as they are getting increasingly popular and equipped with strong sensing capabilities. Smartphones have complex and asynchronous power consumption incurred by heterogeneous components including their on-board sensors. Their interaction with the cloud allows them to offload computation tasks and access remote data storage. In this work, we aim at monitoring the power consumption behaviours of the smartphones, profiling both individual applications and the system as a whole, to make better decisions in power management. We design a cloud orchestration architecture as an epic predictor of behaviours of smart devices by extracting their application characteristics and resource utilization. We design and implement this architecture to perform energy profiling and data analysis on massive data logs. This cloud orchestration architecture coordinates a number of cloud-based services and supports dynamic workflows between service components, which can reduce energy consumption in the energy profiling process itself. Experimental results showed that small portion of applications dominate the energy consumption of smartphones. Heuristic profiling can effectively reduce energy consumption in data logging and communications without scarifying the accuracy of power monitoring.

  • 74. Shea, Ryan
    et al.
    Liu, Jiangchuan
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Cui, Yong
    Cloud Gaming: Architecture and Performance2013In: IEEE Network, ISSN 0890-8044, E-ISSN 1558-156X, Vol. 27, no 4, p. 16-21Article in journal (Refereed)
  • 75. Song, Zheng
    et al.
    Ngai, Edith
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Ma, Jian
    Gong, Xiangyang
    Liu, Yazhi
    Wang, Wendong
    Incentive mechanism for participatory sensing under budget constraints2014In: Proc. Wireless Communications and Networking Conference 2014, IEEE Communications Society, 2014, p. 3361-3366Conference paper (Refereed)
  • 76. Song, Zheng
    et al.
    Ngai, Edith
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Ma, Jian
    Wang, Wendong
    A novel incentive negotiation mechanism for participatory sensing under budget constraints2014In: Proc. 22nd International Symposium on Quality of Service, IEEE Communications Society, 2014, p. 326-331Conference paper (Refereed)
  • 77. Tian, Ye
    et al.
    Li, Xiong
    Sangaiah, Arun Kumar
    Ngai, Edith
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Song, Zheng
    Zhang, Lanshan
    Wang, Wendong
    Privacy-preserving scheme in social participatory sensing based on Secure Multi-party Cooperation2018In: Computer Communications, ISSN 0140-3664, E-ISSN 1873-703X, Vol. 119, p. 167-178Article in journal (Refereed)
    Abstract [en]

    Social participant sensing has been widely used to collect location related sensory data for various applications. In order to improve the Quality of Information (QoI) of the collected data with constrained budget, the application server needs to coordinate participants with different data collection capabilities and various incentive requirements. However, existing participant coordination methods either require participants to reveal their trajectories to the server which causes privacy leakage, or tradeoff the location accuracy of participants for privacy, thereby leading to lower QoI. In this paper, we propose a privacy-preserving scheme, which allows application server to provide quasi-optimal QoI for social sensing tasks without knowing participants’ trajectories and identity. More specifically, we first suggest a Secure Multi-party Cooperation (SMC) based approach to evaluate participant’s contribution in terms of QoI without disclosing each individual’s trajectory. Second, a fuzzy decision based approach which aims to finely balance data utility gain, incentive budget and inferable privacy protection ability is adopted to coordinate participant in an incremental way. Third, sensory data and incentive are encrypted and then transferred along with participant-chain in perturbed way to protect user privacy throughout the data uploading and incentive distribution procedure. Simulation results show that our proposed method can efficiently select appropriate participants to achieve better QoI than other methods, and can protect each participant’s privacy effectively.

  • 78. Tian, Ye
    et al.
    Wang, Wendong
    Wu, Jie
    Kou, Qinli
    Song, Zheng
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Privacy-preserving social tie discovery based on cloaked human trajectories2017In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 66, no 2, p. 1619-1630Article in journal (Refereed)
  • 79. Tong, Xiaoyu
    et al.
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    A ubiquitous publish/subscribe platform for wireless sensor networks with mobile mules2012In: Proc. 8th International Conference on Distributed Computing in Sensor Systems, IEEE Computer Society, 2012, p. 99-108Conference paper (Refereed)
  • 80.
    Tu, Wei
    et al.
    Wuhan Univ, Coll Comp, Wuhan, Peoples R China..
    Wei, Lei
    Hunan Univ, Coll Comp Sci & Elect Engn, Changsha, Hunan, Peoples R China..
    Hu, Wenyan
    Carnegie Mellon Univ, Sch Comp Sci, Pittsburgh, PA 15213 USA..
    Sheng, Zhengguo
    Univ Sussex, Dept Engn & Design, Brighton, E Sussex, England..
    Nicanfar, Hasen
    Univ British Columbia, Dept Elect & Comp Engn, Vancouver, BC, Canada..
    Hu, Xiping
    Univ British Columbia, Dept Elect & Comp Engn, Vancouver, BC, Canada..
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Leung, Victor C. M.
    Univ British Columbia, Dept Elect & Comp Engn, Vancouver, BC, Canada..
    A Survey on Mobile Sensing Based Mood-Fatigue Detection for Drivers2016In: SMART CITY 360 / [ed] LeonGarcia, A Lenort, R Holman, D Stas, D Krutilova, V Wicher, P Caganova, D Spirkova, D Golej, J Nguyen, K, SPRINGER INT PUBLISHING AG , 2016, p. 3-15Conference paper (Refereed)
    Abstract [en]

    The rapid development of the Internet of Things (IoT) has provided innovative solutions to reduce traffic accidents caused by fatigue driving. When drivers are in bad mood or tired, their vigilance level decreases, which may prolong the reaction time to emergency situation and lead to serious accidents. With the help of mobile sensing and mood-fatigue detection, drivers' moodfatigue status can be detected while driving, and then appropriate measures can be taken to eliminate the fatigue or negative mood to increase the level of vigilance. This paper presents the basic concepts and current solutions of moodfatigue detection and some common solutions like mobile sensing and cloud computing techniques. After that, we introduce some emerging platforms which designed to promote safe driving. Finally, we summarize the major challenges in mood-fatigue detection of drivers, and outline the future research directions.

  • 81.
    Wang, Wendong
    et al.
    Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, XiTuCheng Rd 10, Beijing 100876, Peoples R China.
    Xi, Teng
    Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, XiTuCheng Rd 10, Beijing 100876, Peoples R China.
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Song, Zheng
    Virginia Tech, Dept Comp Sci, Blacksburg, VA 24060 USA.
    Energy-efficient collaborative outdoor localization for participatory sensing2016In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 16, no 6, article id 762Article in journal (Refereed)
    Abstract [en]

    Location information is a key element of participatory sensing. Many mobile and sensing applications require location information to provide better recommendations, object search and trip planning. However, continuous GPS positioning consumes much energy, which may drain the battery of mobile devices quickly. Although WiFi and cell tower positioning are alternatives, they provide lower accuracy compared to GPS. This paper solves the above problem by proposing a novel localization scheme through the collaboration of multiple mobile devices to reduce energy consumption and provide accurate positioning. Under our scheme, the mobile devices are divided into three groups, namely the broadcaster group, the location information receiver group and the normal participant group. Only the broadcaster group and the normal participant group use their GPS. The location information receiver group, on the other hand, makes use of the locations broadcast by the broadcaster group to estimate their locations. We formulate the broadcaster set selection problem and propose two novel algorithms to minimize the energy consumption in collaborative localization. Simulations with real traces show that our proposed solution can save up to 68% of the energy of all of the participants and provide more accurate locations than WiFi and cellular network positioning.

  • 82.
    Wang, Xiaojie
    et al.
    NeuSoft Corp, Shenyang, Liaoning, Peoples R China; Dalian Univ Technol, Sch Software, Dalian, Peoples R China.
    Ning, Zhaolong
    Dalian Univ Technol, Sch Software, Dalian, Peoples R China; Kyushu Univ, Fukuoka, Fukuoka, Japan.
    Hu, Xiping
    Chinese Acad Sci, Shenzhen Inst Adv Technol, Beijing, Peoples R China.
    Ngai, Edith
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. Imperial Coll London, London, England.
    Wang, Lei
    Dalian Univ Technol, Sch Software, Dalian, Peoples R China; Bell Labs Res China, Shanghai, Peoples R China; Samsung, Seoul, South Korea; Washington State Univ, Vancouver, WA USA.
    Hu, Bin
    Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou, Gansu, Peoples R China; Tsinghua Univ, Beijing, Peoples R China; Swiss Fed Inst Technol, Zurich, Switzerland; ACM China, Beijing, Peoples R China.
    Kwok, Ricky
    Univ Hong Kong, Hong Kong, Hong Kong, Peoples R China; HKIE, Hong Kong, Hong Kong, Peoples R China; IET, Hong Kong, Hong Kong, Peoples R China.
    A City-Wide Real-Time Traffic Management System: Enabling Crowdsensing in Social Internet of Vehicles2018In: IEEE Communications Magazine, ISSN 0163-6804, E-ISSN 1558-1896, Vol. 56, no 9, p. 19-25Article in journal (Refereed)
    Abstract [en]

    As an emerging platform based on ITS, SIoV is promising for applications of traffic management and road safety in smart cities. However, the end-to-end delay is large in store-carry-and-forward-based vehicular networks, which has become the main obstacle for the implementation of large-scale SIoV. With the extensive applications of mobile devices, crowdsensing is promising to enable real-time content dissemination in a city-wide traffic management system. This article first provides an overview of several promising research areas for traffic management in SIoV. Given the significance of traffic management in urban areas, we investigate a crowdsensing-based framework to provide timely response for traffic management in heterogeneous SIoV. The participant vehicles based on D2D communications integrate trajectory and topology information to dynamically regulate their social behaviors according to network conditions. A real-world taxi trajectory analysis-based performance evaluation is provided to demonstrate the effectiveness of the designed framework. Furthermore, we discuss several future research challenges before concluding our work.

  • 83.
    Xi, Teng
    et al.
    Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing, Peoples R China..
    Ngai, Edith
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Song, Zheng
    Virginia Tech, Dept Comp Sci, Blacksburg, VA USA..
    Tian, Ye
    Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing, Peoples R China..
    Gong, Xiangyang
    Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing, Peoples R China..
    Wang, Wendong
    Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing, Peoples R China..
    Collaborative Localization in Participatory Sensing with Load Balancing2015In: 2015 IEEE 23Rd International Symposium On Quality Of Service (IWQOS), 2015, p. 61-62Conference paper (Refereed)
    Abstract [en]

    The increasingly popular smartphones enable participatory sensing systems to collect location-based sensing data for different tasks. However, GPS positioning is very energy consuming, which could drain a mobile device's battery quickly. High energy consumption may threaten the participants and reduce the sustainability of the participatory sensing systems. In this paper, we propose a collaborative localization strategy with load balancing. Simulations with real traces showed that our proposed solution can save more than 80% of the energy consumption for localization in the entire network with load balancing.

  • 84. Xi, Teng
    et al.
    Wang, W.
    Ngai, Edtih
    Song, Z.
    Tian, Y.
    Gong, X.
    Energy-efficient Collaborative Localization for Participatory Sensing System2015In: 2015 IEEE Global Communications Conference (Globecom), 2015Conference paper (Refereed)
    Abstract [en]

    Location based services are getting increasingly popular in participatory sensing systems. They make use of location information on the mobile devices to support applications that improve personal health, object search, and entertainment. However, GPS positioning consumes a lot of energy, which can drain a mobile device's battery. Although WiFi localization and cell tower localization have been suggested as alternatives, they have lower localization accuracy and limited coverage. In this paper, we suggest a novel solution for multiple mobile devices to perform collaborative localization to reduce energy consumption and provide accurate localization. We divide the mobile devices into two groups, the aggregator group and the collector group. The aggregator group turns on their GPS periodically, while the collector group uses the locations of the aggregators to estimate their own locations. We formulate the aggregator set selection problem and propose two novel algorithms to minimize the energy consumption in collaborative localization. Simulations with real traces showed that our proposed solution can save up to 88% of the energy of the entire network.

  • 85.
    Xi, Teng
    et al.
    Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing, Peoples R China.
    Wang, Wendong
    Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing, Peoples R China.
    Ngai, Edith C-H
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Liu, Xiuming
    Uppsala Univ, Div Comp Syst, Dept Informat Technol, Uppsala, Sweden.
    Spatio-Temporal Aware Collaborative Mobile Sensing with Online Multi-Hop Calibration2018In: Proceedings of the 2018 the Nineteenth International Symposium on Mobile Ad Hoc Networking and Computing (MOBIHOC '18), Association for Computing Machinery (ACM), 2018, p. 310-311Conference paper (Refereed)
    Abstract [en]

    Real-time accurate air quality data is very important for pollution exposure monitoring and urban planning. However, there are limited high-quality air quality monitoring stations (AQMS) in cities due to their high equipment costs. To provide real-time and accurate data covering large area, this paper proposes a novel scheme that jointly considers online multi-hop calibration and spatio-temporal coverage in route selection for mobile sensors. A novel sensor carrier selection problem (SCSP) is formulated, which aims to maximize the spatio-temporal coverage ratio and guarantee the accuracy of measurements through sensor calibration. An online Bayesian based collaborative calibration (OBCC) scheme is proposed to relax the multi-hop calibration constraint in the SCSP. Based on the OBCC, a multi-hop calibration judgment algorithm (MCJA) is proposed to decide whether the data accuracy of a given set of routes can be guaranteed through collaborative calibration. Furthermore, a heuristic sensor route selection algorithm (SRSA) is then developed to solve the SCSP.

  • 86. Xiong, Junjie
    et al.
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Zhou, Yangfan
    Lyu, Michael R.
    RealProct: Reliable protocol conformance testing with real nodes for wireless sensor networks2011In: Proc. 10th International Conference on Trust, Security and Privacy in Computing and Communications, IEEE Computer Society, 2011Conference paper (Refereed)
  • 87. Xu, Gang
    et al.
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Liu, Jiangchuan
    Information-centric collaborative data collection for mobile devices in wireless sensor networks2014In: Proc. International Conference on Communications: ICC 2014, IEEE Communications Society, 2014, p. 36-41Conference paper (Refereed)
  • 88. Xu, Gang
    et al.
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Liu, Jiangchuan
    Ubiquitous transmission of multimedia sensor data in Internet of Things2018In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 5, no 1, p. 403-414Article in journal (Refereed)
    Abstract [en]

    The Internet of Things (IoT) enables environmental monitoring by collecting data from sensing devices, including cameras and microphones. The popularity of smartphones enables mobile users to communicate and collect data from their surrounding sensing devices. The mobile devices can obtain useful environmental data from nearby sensors through short-range communication such as Bluetooth. Nevertheless, the limited contact time and the wireless capacity constrain the amount of data to be collected. With the increasing amount of multimedia big data such as videos and pictures from cameras, it is crucial for mobile users to collect prioritized data that can maximize their data utility. In this paper, we propose a distributed algorithm to provide information-centric ubiquitous data collection of multimedia big data by mobile users in the IoT. The algorithm can handle transmissions of multimedia big data recorded by the surrounding cameras and sensors, and prioritize the transmissions of the most important and relevant data. The mobile users construct data collection trees adaptively according to their dynamic moving speeds and the value of information carried by the multimedia and sensor data. The distributed algorithm can support smooth data collection and coordination of multiple mobile users. We provide both numerical analysis and extensive simulations to evaluate the information value, energy efficiency and scalability of our solution. The results showed that our distributed algorithm can improve the value of information up to 50% and reduce energy consumption to half compared with existing approach. Our algorithm also scales perfectly well with increasing number of mobile users and dynamic moving speeds.

  • 89. Yang, Y.
    et al.
    Tian, Y.
    Ngai, Edith
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Zhang, L.
    Teng, Y.
    Wang, W.
    Vulnerable Friend Identification: Who Should You Beware of Most in Online Social Networks2015In: 2015 IEEE Global Communications Conference (Globecom), 2015Conference paper (Refereed)
    Abstract [en]

    Web users are immersed in their roles as information producers and propagation pushers. They are unaware of being potential threats to privacy-protection towards themselves and their friends. It is necessary to know who they should beware of most in their friend-networks once their privacy information is divulged inadvertently. In this paper, we aim to identify the vulnerable friend who maximizes the dissemination of privacy information. First we develop a Privacy Receiving-Disseminating (PRD) model to simulate the iterative course of privacy information dissemination within social graph. The subgraph constituted of those users who are involved in the dissemination, called Ultimate Circle of Disseminating (UCD), is then detected by an iterative algorithm. The contribution of each direct friend could be evaluated by comparing the disseminating intensities of detected UCDs before and after unfriending himself. The performance of our work has been validated empirically with the comparison of different unfriending strategies.

  • 90. Zahedi, Sadaf
    et al.
    Ngai, Edith
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Gelenbe, Erol
    Mylaraswamy, Dinkar
    Srivastava, Mani B.
    Information Quality Aware Sensor Network Services2008In: Proc. 42nd Asilomar Conference on Signals, Systems and Computers, Piscataway, NJ: IEEE , 2008, p. 1155-1159Conference paper (Refereed)
  • 91.
    Zhang, Cong
    et al.
    Simon Fraser Univ, Sch Comp Sci, Burnaby, BC V5A 1S6, Canada..
    Liu, Jiangchuan
    Simon Fraser Univ, Sch Comp Sci, Burnaby, BC V5A 1S6, Canada..
    Chen, Fei
    Jiangnan Univ, Sch Digital Media, Wuxi, Peoples R China..
    Cui, Yong
    Tsinghua Univ, Dept Comp Sci, Beijing, Peoples R China..
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Dependency-Aware Caching for HTTP Adaptive Streaming2016In: 2016 Digital Media Industry And Academic Forum (DMIAF), 2016, p. 89-93Conference paper (Refereed)
    Abstract [en]

    There has been significant interest in the use of HTTP adaptive streaming for live or on-demand video over the Internet in recent years. To mitigate the streaming transmission delay and reduce the networking overhead, an effective and critical approach is to utilize cache servers between the origin servers and the heterogeneous clients. As the underlying protocol for web transactions, HTTP has great potentials to explore the resources within state-of-the-art CDNs tor caching; yet distinct challenges arise in the HTTP adaptive streaming context. After examining a long-term and large-scale adaptive streaming dataset as well as statistical analysis, we demonstrate that the switching requests among the different qualities frequently emerge and constitute a significant portion in a per-day view. Consequently, they have substantially affected the performance of cache servers and Quality-of-Experience (QoE) of viewers. In this paper, we propose a novel cache model that captures the dependency among the segments in the cache server for adaptive HTTP streaming. Our work does not assume any specific selection algorithm on the client's side and hence can be easily incorporated into existing streaming cache system. Its centralized nature is also well accommodated by the latest DASH specification. The performance evaluation shows our dependency-aware strategy can significantly improved the cache hit-ratio and QoE of HTTP streaming as compared to previous methods.

  • 92. Zhang, Cong
    et al.
    Liu, Jiangchuan
    Chen, Fei
    Cui, Yong
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Hu, Yuemin
    Dependency- and similarity-aware caching for HTTP adaptive streaming2018In: Multimedia tools and applications, ISSN 1380-7501, E-ISSN 1573-7721, Vol. 77, no 1, p. 1453-1474Article in journal (Refereed)
    Abstract [en]

    There has been significant interest in the use of HTTP adaptive streaming for live or on-demand video over the Internet in recent years. To mitigate the streaming transmission delay and reduce the networking overhead, an effective and critical approach is to utilize cache services between the origin servers and the heterogeneous clients. As the underlying protocol for web transactions, HTTP has great potentials to explore the resources within state-of-the-art CDNs for caching; yet distinct challenges arise in the HTTP adaptive streaming context. After examining a long-term and large-scale adaptive streaming dataset as well as statistical analysis, we demonstrate that the switching requests among the different qualities frequently emerge and constitute a significant portion in a per-day view. Consequently, they have substantially affected the performance of cache servers and Quality-of-Experience (QoE) of viewers. In this paper, we propose a novel cache model that captures the dependency among the segments in the cache server for adaptive HTTP streaming. Our work does not assume any specific selection algorithm on the client's side and hence can be easily incorporated into existing streaming cache systems. Its centralized nature is also well accommodated by the latest DASH specification. Moreover, we extend our work to the multi-server caching context and present a similarity-aware allocation mechanism to enhance the caching efficiency. The performance evaluation shows our dependency- and similarity-aware strategy can significantly improve the cache hit-ratio and QoE of HTTP streaming as compared to previous approaches.

  • 93. Zhang, Jiao
    et al.
    Hu, Xiping
    Ning, Zhaolong
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Zhou, Li
    Wei, Jibo
    Cheng, Jun
    Hu, Bin
    Energy-latency tradeoff for energy-aware offloading in mobile edge computing networks2018In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 5, no 4, p. 2633-2645Article in journal (Refereed)
  • 94.
    Zhang, Jiao
    et al.
    Natl Univ Def Technol, Coll Elect Sci, Changsha 410073, Hunan, Peoples R China;Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China.
    Hu, Xiping
    Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China.
    Ning, Zhaolong
    Dalian Univ Technol, Key Lab Ubiquitous Network & Serv Software Liaoni, Sch Software, Dalian 116620, Peoples R China.
    Ngai, Edith
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Zhou, Li
    Natl Univ Def Technol, Coll Elect Sci, Changsha 410073, Hunan, Peoples R China.
    Wei, Jibo
    Natl Univ Def Technol, Coll Elect Sci, Changsha 410073, Hunan, Peoples R China.
    Cheng, Jun
    Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China.
    Hu, Bin
    Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 410073, Gansu, Peoples R China.
    Leung, Victor C. M.
    Univ British Columbia, Dept Elect & Comp Engn, Vancouver, BC V6T 1Z4, Canada.
    Joint Resource Allocation for Latency-Sensitive Services Over Mobile Edge Computing Networks With Caching2019In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 6, no 3, p. 4283-4294Article in journal (Refereed)
    Abstract [en]

    Mobile edge computing (MEC) has risen as a promising paradigm to provide high quality of experience via relocating the cloud server in close proximity to smart mobile devices (SMDs). In MEC networks, the MEC server with computation capability and storage resource can jointly execute the latency-sensitive offloading tasks and cache the contents requested by SMDs. In order to minimize the total latency consumption of the computation tasks, we jointly consider computation offloading, content caching, and resource allocation as an integrated model, which is formulated as a mixed integer nonlinear programming (MINLP) problem. We design an asymmetric search tree and improve the branch and bound method to obtain a set of accurate decisions and resource allocation strategies. Furthermore, we introduce the auxiliary variables to reformulate the proposed model and apply the modified generalized benders decomposition method to solve the MINLP problem in polynomial computation complexity time. Simulation results demonstrate the superiority of the proposed schemes.

  • 95. Zhang, Jiao
    et al.
    Zhou, Li
    Tang, Qi
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Hu, Xiping
    Zhao, Haitao
    Wei, Jibo
    Stochastic computation offloading and trajectory scheduling for UAV-assisted mobile edge computing2019In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 6, no 2, p. 3688-3699Article in journal (Refereed)
  • 96. Zhang, Lei
    et al.
    Fu, Di
    Liu, Jiangchuan
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Zhu, Wenwu
    On energy-efficient offloading in mobile cloud for real-time video applications2017In: IEEE transactions on circuits and systems for video technology (Print), ISSN 1051-8215, E-ISSN 1558-2205, Vol. 27, no 1, p. 170-181Article in journal (Refereed)
  • 97. Zhou, Li
    et al.
    Hu, Xiping
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Zhao, Haitao
    Wang, Shan
    Wei, Jibo
    Leung, Victor C. M.
    A dynamic graph-based scheduling and interference coordination approach in heterogeneous cellular networks2016In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 65, no 5, p. 3735-3748Article in journal (Refereed)
  • 98. Zhu, Chunsheng
    et al.
    Leung, Victor C. M.
    Shu, Lei
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Green Internet of Things for Smart World2015In: IEEE Access, E-ISSN 2169-3536, Vol. 3, p. 2151-2162Article in journal (Refereed)
    Abstract [en]

    Smart world is envisioned as an era in which objects (e.g., watches, mobile phones, computers, cars, buses, and trains) can automatically and intelligently serve people in a collaborative manner. Paving the way for smart world, Internet of Things (IoT) connects everything in the smart world. Motivated by achieving a sustainable smart world, this paper discusses various technologies and issues regarding green IoT, which further reduces the energy consumption of IoT. Particularly, an overview regarding IoT and green IoT is performed first. Then, the hot green information and communications technologies (ICTs) (e.g., green radio frequency identification, green wireless sensor network, green cloud computing, green machine to machine, and green data center) enabling green IoT are studied, and general green ICT principles are summarized. Furthermore, the latest developments and future vision about sensor cloud, which is a novel paradigm in green IoT, are reviewed and introduced, respectively. Finally, future research directions and open problems about green IoT are presented. Our work targets to be an enlightening and latest guidance for research with respect to green IoT and smart world.

12 51 - 98 of 98
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf