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Real-time and generic queue time estimation based on mobile crowdsensing

Frontiers of Computer Science 2017年第1期11卷 49-60页

作者： Jiangtao WANG Yasha WANG Daqing ZHANG Leye WANG Chao CHEN Jae Woong LEE Yuanduo HE Key Laboratory of High Confidence Software Technologies Ministry of Education Beijing 100871 China School of Electronics Engineering and Computer Science Peking University Beijing 100871 China Beida (Binhai) Information Research Tianjin 300450 China National Engineering Research Center of Software Engineering Peking University Beijing 100871 China Network & Services Department Institut Mines-Telecom/Telecom SudParis Evry 91011 France Department of Computer Science Chongqing University Chongqing 400044 China Department of Mathematics and Computer Science University of Central Missouri Warrensburg MO 64093 USA

People often have to queue for a busy service in many places around a city, and knowing the queue time can be helpful for making better activity plans to avoid long queues. Traditional solutions to the queue time monitoring are based on pre-deployed infrastructures, such as cameras and infrared sensors, which are costly and fail to deliver the queue time information to scattered citizens. This paper presents CrowdQTE, a mobile crowdsensing system, which utilizes the sensor-enhanced mobile devices and crowd hu- man intelligence to monitor and provide real-time queue time information for various queuing scenarios. When people are waiting in a line, we utilize the accelerometer sensor data and ambient contexts to automatically detect the queueing behav- ior and calculate the queue time. When people are not waiting in a line, it estimates the queue time based on the information reported manually by participants. We evaluate the perfor- mance of the system with a two-week and 12-person deploy- ment using commercially-available smartphones. The results demonstrate that CrowdQTE is effective in estimating queu- ing status.

关键词： mobile crowdsensing queue time estimation opportunistic and participatory sensing

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Secure mobile crowdsensing Based on Deep Learning

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China Communications 2018年第10期15卷 1-11页

作者： Liang Xiao Donghua Jiang Dongjin Xu Wei Su Ning An Dongming Wang Dept. of Communications Engineering Xiamen University Xiamen 361005 China Dept. of Computer and Information Hefei University of Technology Hefei 230009 China National mobile Communications Research Lab. Southeast University Nanjing 211189 China

To improve the quality of multimedia services and stimulate secure sensing in Internet of Things applications, such as healthcare and traffic monitoring, mobile crowdsensing(MCS) systems must address security threats such as jamming, spoofing and faked sensing attacks during both sensing and information exchange processes in large-scale dynamic and heterogeneous networks. In this article, we investigate secure mobile crowdsensing and present ways to use deep learning(DL) methods, such as stacked autoencoder, deep neural networks, convolutional neural networks, and deep reinforcement learning, to improve approaches to MCS security, including authentication, privacy protection, faked sensing countermeasures, intrusion detection and anti-jamming transmissions in MCS. We discuss the performance gain of these DLbased approaches compared to traditional security schemes and identify the challenges that must be addressed to implement these approaches in practical MCS systems.

关键词： mobile crowdsensing security deep learning reinforcement learning faked sensing

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A Differentially Private Data Aggregation Method Based on Worker Partition and Location Obfuscation for mobile crowdsensing

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Computers, Materials & Continua 2020年第4期63卷 223-241页

作者： Shuyu Li Guozheng Zhang School of Computer Science Shaanxi Normal UniversityXi’an710119China

With the popularity of sensor-rich mobile devices,mobile crowdsensing(MCS)has emerged as an effective method for data collection and ***,MCS platform usually need workers’precise locations for optimal task execution and collect sensing data from workers,which raises severe concerns of privacy *** to preserve workers’location and sensing data from the untrusted MCS platform,a differentially private data aggregation method based on worker partition and location obfuscation(DP-DAWL method)is proposed in the ***-DAWL method firstly use an improved K-means algorithm to divide workers into groups and assign different privacy budget to the group according to group size(the number of workers).Then each worker’s location is obfuscated and his/her sensing data is perturbed by adding Laplace noise before uploading to the *** the stage of data aggregation,DP-DAWL method adopts an improved Kalman filter algorithm to filter out the added noise(including both added noise of sensing data and the system noise in the sensing process).Through using optimal estimation of noisy aggregated sensing data,the platform can finally gain better utility of aggregated data while preserving workers’*** experiments on the synthetic datasets demonstrate the effectiveness of the proposed method.

关键词： mobile crowdsensing data aggregation differential privacy K-means kalman filter

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BPPF:Bilateral Privacy-Preserving Framework for mobile crowdsensing

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ZTE Communications 2021年第2期19卷 20-28页

作者： LIU Junyu YANG Yongjian WANG En Jilin University Changchun 130012China

With the emergence of mobile crowdsensing (MCS), merchants can use their mobiledevices to collect data that customers are interested in. Now there are many mobilecrowdsensing platforms in the market, such as Gigwalk, Uber and Checkpoint, which publishand select the right workers to complete the task of some specific locations (for example,taking photos to collect the price of goods in a shopping mall). In mobile crowdsensing, in orderto select the right workers, the platform needs the actual location information of workersand tasks, which poses a risk to the location privacy of workers and tasks. In this paper, westudy privacy protection in MCS. The main challenge is to assign the most suitable worker toa task without knowing the task and the actual location of the worker. We propose a bilateralprivacy protection framework based on matrix multiplication, which can protect the locationprivacy between the task and the worker, and keep their relative distance unchanged.

关键词： mobile crowdsensing task allocation privacy preserving

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Enhancing Task Assignment in crowdsensing Systems Based on Sensing Intervals and Location

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Computers, Materials & Continua 2022年第6期71卷 5619-5638页

作者： Rasha Sleem Nagham Mekky Shaker El-Sappagh Louai Alarabi Noha AHikal Mohammed Elmogy Faculty of Computers and Information Mansoura UniversityMansoura35516Egypt Faculty of Computers and Artificial Intelligence Benha UniversityBanha13518Egypt Faculty of Computer Science and Engineering Galala UniversitySuez435611Egypt College of Computer and Information Systems Umm Al-Qura UniversityMecca715Saudi Arabia

The popularity of mobile devices with sensors is captivating the attention of researchers to modern techniques,such as the internet of things(IoT)and mobile crowdsensing(MCS).The core concept behind MCS is to use the power of mobile sensors to accomplish a difficult task collaboratively,with each mobile user completing much simpler *** paper discusses the task assignment problem in mobile crowdsensing,which is dependent on sensing time and path planning with the constraints of participant travel distance budgets and sensing time *** goal is to minimize aggregate sensing time for mobile users,which reduces energy consumption to encourage more participants to engage in sensing activities and maximize total task *** paper introduces a two-phase task assignment framework called location time-based algorithm(LTBA).LTBA is a framework that enhances task assignment in MCS,whereas assigning tasks requires overlapping time intervals between tasks and mobile users’tasks and the location of tasks and mobile users’*** process of assigning the nearest task to the mobile user’s current path depends on the ant colony optimization algorithm(ACO)and Euclidean *** combines two algorithms:(1)greedy online allocation algorithm and(2)bio-inspired traveldistance-balance-based algorithm(B-DBA).The greedy algorithm was sensing time interval-based and worked on reducing the overall sensing time of the mobile user.B-DBA was location-based and worked on maximizing total task *** results demonstrate that the average task quality is 0.8158,0.7093,and 0.7733 for LTBA,B-DBA,and greedy,*** sensing time was reduced to 644,1782,and 685 time units for LTBA,B-DBA,and greedy,*** the algorithms improves task assignment in MCS for both total task quality and sensing *** results demonstrate that combining the two algorithms in LTBA is the best performance for total task quality and total sensing time,and the greed

关键词： mobile crowdsensing online task assignment participatory sensing path planning sensing time intervals ant colony optimization

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Multi-sensing paradigm based urban air quality monitoring and hazardous gas source analyzing:a review

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Journal of Safety Science and Resilience 2021年第3期2卷 131-145页

作者： Zhengqiu Zhu Bin Chen Yong Zhao Yatai Ji College of Systems Engineering National University of Defense Technology(NUDT)410073109 Deya RoadKaifu DistrictChangsha CityHunan provinceChina Research Group of Multi-scale Networked Systems Informatics InstituteUniversity of Amsterdam(UvA)Science Park 904P.O.Box 943231096 XH AmsterdamNetherlands

Effectively monitoring urban air quality,and analyzing the source terms of the main atmospheric pollutants is important for public authorities to take air quality management *** works,such as long-term obser-vations by monitoring stations,cannot provide customized data services and in-time emergency response under urgent situations(gas leakage incidents).Therefore,we first review the up-to-date approaches(often machine learning and optimization methods)with respect to urban air quality monitoring and hazardous gas source *** bridge the gap between present solutions and practical requirements,we design a conceptual framework,namely MAsmed(Multi-Agents for sensing,monitoring,estimating and determining),to provide fine-grained concentration maps,customized data services,and on-demand emergency *** this framework,we leverage the hybrid design of wireless sensor networks(WSNs)and mobile crowdsensing(MCS)to sense urban air quality and relevant data(*** data,meteorological data,etc.);Using the sensed data,we can create a fine-grained air quality map for the authorities and relevant stakeholders,and provide on-demand source term estimation and source searching methods to estimate,seek,and determine the sources,thereby aiding decision-makers in emergency response(*** evacuation).In this paper,we also identify several potential opportunities for future research.

关键词： Urban air quality monitoring and source analyzing system MAsmed framework Wireless sensor networks mobile crowdsensing Air quality management

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Blockchain-Based MCS Detection Framework of Abnormal Spectrum Usage for Satellite Spectrum Sharing Scenario

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China Communications 2024年第2期21卷 32-48页

作者： Ning Yang Heng Wang Jingming Hu Bangning Zhang Daoxing Guo Yuan Liu College of Communications Engineering Army Engineering UniversityNanjing 210007China

In this paper, the problem of abnormal spectrum usage between satellite spectrum sharing systems is investigated to support multi-satellite spectrum coexistence. Given the cost of monitoring, the mobility of low-orbit satellites, and the directional nature of their signals, traditional monitoring methods are no longer suitable, especially in the case of multiple power level. mobile crowdsensing(MCS), as a new technology, can make full use of idle resources to complete a variety of perceptual tasks. However, traditional MCS heavily relies on a centralized server and is vulnerable to single point of failure attacks. Therefore, we replace the original centralized server with a blockchain-based distributed service provider to enable its security. Therefore, in this work, we propose a blockchain-based MCS framework, in which we explain in detail how this framework can achieve abnormal frequency behavior monitoring in an inter-satellite spectrum sharing system. Then, under certain false alarm probability, we propose an abnormal spectrum detection algorithm based on mixed hypothesis test to maximize detection probability in single power level and multiple power level scenarios, respectively. Finally, a Bad out of Good(BooG) detector is proposed to ease the computational pressure on the blockchain nodes. Simulation results show the effectiveness of the proposed framework.

关键词： blockchain hypothesis test mobile crowdsensing satellite communication spectrum sharing

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Maximum-Profit Advertising Strategy Using crowdsensing Trajectory Data

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ZTE Communications 2021年第2期19卷 29-43页

作者： LOU Kaihao YANG Yongjian YANG Funing ZHANG Xingliang Jilin University Changchun 130012China China mobile Group Jilin Co. Ltd.Changchun 130021China

Out-door billboard advertising plays an important role in attracting potential ***,whether a customer can be attracted is influenced by many factors,such as the probability that he/she sees the billboard,the degree of his/her interest,and the detour distance for buying the *** the above factors into account,we propose advertising strategies for selecting an effective set of billboards under the advertising budget to maximize commercial *** using the data collected by mobile crowdsensing(MCS),we extract potential customers’implicit information,such as their trajectories and *** then study the billboard selection problem under two situations,where the advertiser may have only one or multiple *** only one kind of product needs advertising,the billboard selection problem is formulated as the probabilistic set coverage *** propose two heuristic advertising strategies to greedily select advertising billboards,which achieves the expected maximum commercial profit with the lowest *** the advertiser has multiple products,we formulate the problem as searching for an optimal solution and adopt the simulated annealing algorithm to search for global optimum instead of local *** experiments based on three real-world data sets verify that our proposed advertising strategies can achieve the superior commercial profit compared with the state-of-the-art strategies.

关键词： billboard advertising mobile crowdsensing probabilistic set coverage problem simulated annealing optimization problem

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