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Special Issue "New Paradigms in Cyber-Physical Social Sensing"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (31 October 2016)

Special Issue Editors

Guest Editor
Prof. Dr. Mianxiong Dong

Department of Information and Electronic Engineering, Muroran Institute of Technology, Hokkaido, Japan
Website | E-Mail
Interests: wireless networks; sensor networks; mobile crowd sensing; mobile computing
Guest Editor
Prof. Dr. Zhi Liu

Global Information and Telecommunication Institute (GITI), Waseda University, Tokyo, Japan
E-Mail
Interests: wireless networks; video/image processing and transmission
Guest Editor
Prof. Dr. Anfeng Liu

School of Information Science and Engineering, Central South University, ChangSha, China
Website | E-Mail
Interests: sensor networks; mobile crowd sensing; mobile computing
Guest Editor
Prof. Dr. Didier El Baz

Distributed Computing and Asynchronism Team (CDA), LAAS-CNRS, Toulouse, France
E-Mail
Interests: applied mathematics and parallel and distributed computing; heterogeneous computing and peer-to-peer computing

Special Issue Information

Dear Colleagues,

The goal of Cyber Physical Social Sensing (CPSS) is to form a ubiquitous mobile wireless sensor network using intelligent terminals equipped with various sensors and perceive human social information including the environment, transportation, social activities, etc. It wirelessly uploads the information to the server, and then composites the information and provides the user with a higher level of combined information or services. CPSS enriches human-to-human, human-to-object, and object-to-object interactions in the physical world, human society, as well as in the virtual world. Furthermore, it allows people to participate in the perception process through the mobile terminals and provides pervasive service for people. CPSS expands the dimensions of human perception of the world, and changes the way that people perceive the world. Additionally, it will exhibit a variety of complicated characteristics, which provides more open issues and challenges for research communities.

The goal of this Special Issue is to seek original articles examining the state-of-the-art, open challenging research issues, new research results, and solutions in Cyber-Physical Social Sensing. All submissions should contain substantial tutorial content and be accessible to a general audience of researchers and practitioners.

Prof. Dr. Mianxiong Dong
Prof. Dr. Zhi Liu
Prof. Dr. Anfeng Liu
Prof. Dr. Didier El Baz
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Architecture design of perception system
  • Protocol design of in CPSS
  • Localization, node mobility model for CPSS
  • Construction technology of dynamics group in CPSS
  • Methods for data collection, convergence and storage in CPSS
  • Schemes of data mining, processing and analysis in CPSS
  • Audit mechanism and verification mechanism for data credibility verification in CPSS
  • Data visualization in CPSS
  • Security, as well as privacy performance modeling, analysis, and optimization for CPSS
  • Quality of Experience and Quality of Service in CPSS
  • Economics and pricing mechanism for CPSS
  • Application of social perception calculation and other related applications in CPSS
  • Experimental platform design for CPSS

Published Papers (20 papers)

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Research

Open AccessArticle A Delay-Aware and Reliable Data Aggregation for Cyber-Physical Sensing
Sensors 2017, 17(2), 395; doi:10.3390/s17020395
Received: 10 January 2017 / Revised: 14 February 2017 / Accepted: 15 February 2017 / Published: 17 February 2017
Cited by 1 | PDF Full-text (6065 KB) | HTML Full-text | XML Full-text
Abstract
Physical information sensed by various sensors in a cyber-physical system should be collected for further operation. In many applications, data aggregation should take reliability and delay into consideration. To address these problems, a novel Tiered Structure Routing-based Delay-Aware and Reliable Data Aggregation scheme
[...] Read more.
Physical information sensed by various sensors in a cyber-physical system should be collected for further operation. In many applications, data aggregation should take reliability and delay into consideration. To address these problems, a novel Tiered Structure Routing-based Delay-Aware and Reliable Data Aggregation scheme named TSR-DARDA for spherical physical objects is proposed. By dividing the spherical network constructed by dispersed sensor nodes into circular tiers with specifically designed widths and cells, TSTR-DARDA tries to enable as many nodes as possible to transmit data simultaneously. In order to ensure transmission reliability, lost packets are retransmitted. Moreover, to minimize the latency while maintaining reliability for data collection, in-network aggregation and broadcast techniques are adopted to deal with the transmission between data collecting nodes in the outer layer and their parent data collecting nodes in the inner layer. Thus, the optimization problem is transformed to minimize the delay under reliability constraints by controlling the system parameters. To demonstrate the effectiveness of the proposed scheme, we have conducted extensive theoretical analysis and comparisons to evaluate the performance of TSR-DARDA. The analysis and simulations show that TSR-DARDA leads to lower delay with reliability satisfaction. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle Smooth Sensor Motion Planning for Robotic Cyber Physical Social Sensing (CPSS)
Sensors 2017, 17(2), 393; doi:10.3390/s17020393
Received: 12 December 2016 / Revised: 7 February 2017 / Accepted: 9 February 2017 / Published: 17 February 2017
Cited by 1 | PDF Full-text (727 KB) | HTML Full-text | XML Full-text
Abstract
Although many researchers have begun to study the area of Cyber Physical Social Sensing (CPSS), few are focused on robotic sensors. We successfully utilize robots in CPSS, and propose a sensor trajectory planning method in this paper. Trajectory planning is a fundamental problem
[...] Read more.
Although many researchers have begun to study the area of Cyber Physical Social Sensing (CPSS), few are focused on robotic sensors. We successfully utilize robots in CPSS, and propose a sensor trajectory planning method in this paper. Trajectory planning is a fundamental problem in mobile robotics. However, traditional methods are not suited for robotic sensors, because of their low efficiency, instability, and non-smooth-generated paths. This paper adopts an optimizing function to generate several intermediate points and regress these discrete points to a quintic polynomial which can output a smooth trajectory for the robotic sensor. Simulations demonstrate that our approach is robust and efficient, and can be well applied in the CPSS field. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle Capacity-Delay Trade-Off in Collaborative Hybrid Ad-Hoc Networks with Coverage Sensing
Sensors 2017, 17(2), 232; doi:10.3390/s17020232
Received: 19 November 2016 / Revised: 12 January 2017 / Accepted: 18 January 2017 / Published: 26 January 2017
PDF Full-text (735 KB) | HTML Full-text | XML Full-text
Abstract
The integration of ad hoc device-to-device (D2D) communications and open-access small cells can result in a networking paradigm called hybrid the ad hoc network, which is particularly promising in delivering delay-tolerant data. The capacity-delay performance of hybrid ad hoc networks has been studied
[...] Read more.
The integration of ad hoc device-to-device (D2D) communications and open-access small cells can result in a networking paradigm called hybrid the ad hoc network, which is particularly promising in delivering delay-tolerant data. The capacity-delay performance of hybrid ad hoc networks has been studied extensively under a popular framework called scaling law analysis. These studies, however, do not take into account aspects of interference accumulation and queueing delay and, therefore, may lead to over-optimistic results. Moreover, focusing on the average measures, existing works fail to give finer-grained insights into the distribution of delays. This paper proposes an alternative analytical framework based on queueing theoretic models and physical interference models. We apply this framework to study the capacity-delay performance of a collaborative cellular D2D network with coverage sensing and two-hop relay. The new framework allows us to fully characterize the delay distribution in the transform domain and pinpoint the impacts of coverage sensing, user and base station densities, transmit power, user mobility and packet size on the capacity-delay trade-off. We show that under the condition of queueing equilibrium, the maximum throughput capacity per device saturates to an upper bound of 0.7239 λ b / λ u bits/s/Hz, where λ b and λ u are the densities of base stations and mobile users, respectively. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle Competitive Swarm Optimizer Based Gateway Deployment Algorithm in Cyber-Physical Systems
Sensors 2017, 17(1), 209; doi:10.3390/s17010209
Received: 30 October 2016 / Revised: 4 January 2017 / Accepted: 13 January 2017 / Published: 22 January 2017
PDF Full-text (590 KB) | HTML Full-text | XML Full-text
Abstract
Wireless sensor network topology optimization is a highly important issue, and topology control through node selection can improve the efficiency of data forwarding, while saving energy and prolonging lifetime of the network. To address the problem of connecting a wireless sensor network to
[...] Read more.
Wireless sensor network topology optimization is a highly important issue, and topology control through node selection can improve the efficiency of data forwarding, while saving energy and prolonging lifetime of the network. To address the problem of connecting a wireless sensor network to the Internet in cyber-physical systems, here we propose a geometric gateway deployment based on a competitive swarm optimizer algorithm. The particle swarm optimization (PSO) algorithm has a continuous search feature in the solution space, which makes it suitable for finding the geometric center of gateway deployment; however, its search mechanism is limited to the individual optimum (pbest) and the population optimum (gbest); thus, it easily falls into local optima. In order to improve the particle search mechanism and enhance the search efficiency of the algorithm, we introduce a new competitive swarm optimizer (CSO) algorithm. The CSO search algorithm is based on an inter-particle competition mechanism and can effectively avoid trapping of the population falling into a local optimum. With the improvement of an adaptive opposition-based search and its ability to dynamically parameter adjustments, this algorithm can maintain the diversity of the entire swarm to solve geometric K-center gateway deployment problems. The simulation results show that this CSO algorithm has a good global explorative ability as well as convergence speed and can improve the network quality of service (QoS) level of cyber-physical systems by obtaining a minimum network coverage radius. We also find that the CSO algorithm is more stable, robust and effective in solving the problem of geometric gateway deployment as compared to the PSO or Kmedoids algorithms. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle A Non-Intrusive Cyber Physical Social Sensing Solution to People Behavior Tracking: Mechanism, Prototype, and Field Experiments
Sensors 2017, 17(1), 143; doi:10.3390/s17010143
Received: 31 October 2016 / Revised: 21 December 2016 / Accepted: 21 December 2016 / Published: 13 January 2017
PDF Full-text (3330 KB) | HTML Full-text | XML Full-text
Abstract
Tracking people’s behaviors is a main category of cyber physical social sensing (CPSS)-related people-centric applications. Most tracking methods utilize camera networks or sensors built into mobile devices such as global positioning system (GPS) and Bluetooth. In this article, we propose a non-intrusive wireless
[...] Read more.
Tracking people’s behaviors is a main category of cyber physical social sensing (CPSS)-related people-centric applications. Most tracking methods utilize camera networks or sensors built into mobile devices such as global positioning system (GPS) and Bluetooth. In this article, we propose a non-intrusive wireless fidelity (Wi-Fi)-based tracking method. To show the feasibility, we target tracking people’s access behaviors in Wi-Fi networks, which has drawn a lot of interest from the academy and industry recently. Existing methods used for acquiring access traces either provide very limited visibility into media access control (MAC)-level transmission dynamics or sometimes are inflexible and costly. In this article, we present a passive CPSS system operating in a non-intrusive, flexible, and simplified manner to overcome above limitations. We have implemented the prototype on the off-the-shelf personal computer, and performed real-world deployment experiments. The experimental results show that the method is feasible, and people’s access behaviors can be correctly tracked within a one-second delay. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle Efficient DV-HOP Localization for Wireless Cyber-Physical Social Sensing System: A Correntropy-Based Neural Network Learning Scheme
Sensors 2017, 17(1), 135; doi:10.3390/s17010135
Received: 30 October 2016 / Revised: 3 January 2017 / Accepted: 5 January 2017 / Published: 12 January 2017
Cited by 2 | PDF Full-text (569 KB) | HTML Full-text | XML Full-text
Abstract
Integrating wireless sensor network (WSN) into the emerging computing paradigm, e.g., cyber-physical social sensing (CPSS), has witnessed a growing interest, and WSN can serve as a social network while receiving more attention from the social computing research field. Then, the localization of sensor
[...] Read more.
Integrating wireless sensor network (WSN) into the emerging computing paradigm, e.g., cyber-physical social sensing (CPSS), has witnessed a growing interest, and WSN can serve as a social network while receiving more attention from the social computing research field. Then, the localization of sensor nodes has become an essential requirement for many applications over WSN. Meanwhile, the localization information of unknown nodes has strongly affected the performance of WSN. The received signal strength indication (RSSI) as a typical range-based algorithm for positioning sensor nodes in WSN could achieve accurate location with hardware saving, but is sensitive to environmental noises. Moreover, the original distance vector hop (DV-HOP) as an important range-free localization algorithm is simple, inexpensive and not related to the environment factors, but performs poorly when lacking anchor nodes. Motivated by these, various improved DV-HOP schemes with RSSI have been introduced, and we present a new neural network (NN)-based node localization scheme, named RHOP-ELM-RCC, through the use of DV-HOP, RSSI and a regularized correntropy criterion (RCC)-based extreme learning machine (ELM) algorithm (ELM-RCC). Firstly, the proposed scheme employs both RSSI and DV-HOP to evaluate the distances between nodes to enhance the accuracy of distance estimation at a reasonable cost. Then, with the help of ELM featured with a fast learning speed with a good generalization performance and minimal human intervention, a single hidden layer feedforward network (SLFN) on the basis of ELM-RCC is used to implement the optimization task for obtaining the location of unknown nodes. Since the RSSI may be influenced by the environmental noises and may bring estimation error, the RCC instead of the mean square error (MSE) estimation, which is sensitive to noises, is exploited in ELM. Hence, it may make the estimation more robust against outliers. Additionally, the least square estimation (LSE) in ELM is replaced by the half-quadratic optimization technique. Simulation results show that our proposed scheme outperforms other traditional localization schemes. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle Spectrum Sharing Based on a Bertrand Game in Cognitive Radio Sensor Networks
Sensors 2017, 17(1), 101; doi:10.3390/s17010101
Received: 28 October 2016 / Revised: 18 December 2016 / Accepted: 28 December 2016 / Published: 7 January 2017
PDF Full-text (12468 KB) | HTML Full-text | XML Full-text
Abstract
In the study of power control and allocation based on pricing, the utility of secondary users is usually studied from the perspective of the signal to noise ratio. The study of secondary user utility from the perspective of communication demand can not only
[...] Read more.
In the study of power control and allocation based on pricing, the utility of secondary users is usually studied from the perspective of the signal to noise ratio. The study of secondary user utility from the perspective of communication demand can not only promote the secondary users to meet the maximum communication needs, but also to maximize the utilization of spectrum resources, however, research in this area is lacking, so from the viewpoint of meeting the demand of network communication, this paper designs a two stage model to solve spectrum leasing and allocation problem in cognitive radio sensor networks (CRSNs). In the first stage, the secondary base station collects the secondary network communication requirements, and rents spectrum resources from several primary base stations using the Bertrand game to model the transaction behavior of the primary base station and secondary base station. The second stage, the subcarriers and power allocation problem of secondary base stations is defined as a nonlinear programming problem to be solved based on Nash bargaining. The simulation results show that the proposed model can satisfy the communication requirements of each user in a fair and efficient way compared to other spectrum sharing schemes. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle Enhance the Quality of Crowdsensing for Fine-Grained Urban Environment Monitoring via Data Correlation
Sensors 2017, 17(1), 88; doi:10.3390/s17010088
Received: 1 November 2016 / Revised: 19 December 2016 / Accepted: 20 December 2016 / Published: 4 January 2017
PDF Full-text (4479 KB) | HTML Full-text | XML Full-text
Abstract
Monitoring the status of urban environments, which provides fundamental information for a city, yields crucial insights into various fields of urban research. Recently, with the popularity of smartphones and vehicles equipped with onboard sensors, a people-centric scheme, namely “crowdsensing”, for city-scale environment monitoring
[...] Read more.
Monitoring the status of urban environments, which provides fundamental information for a city, yields crucial insights into various fields of urban research. Recently, with the popularity of smartphones and vehicles equipped with onboard sensors, a people-centric scheme, namely “crowdsensing”, for city-scale environment monitoring is emerging. This paper proposes a data correlation based crowdsensing approach for fine-grained urban environment monitoring. To demonstrate urban status, we generate sensing images via crowdsensing network, and then enhance the quality of sensing images via data correlation. Specifically, to achieve a higher quality of sensing images, we not only utilize temporal correlation of mobile sensing nodes but also fuse the sensory data with correlated environment data by introducing a collective tensor decomposition approach. Finally, we conduct a series of numerical simulations and a real dataset based case study. The results validate that our approach outperforms the traditional spatial interpolation-based method. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle Node Immunization with Time-Sensitive Restrictions
Sensors 2016, 16(12), 2141; doi:10.3390/s16122141
Received: 9 October 2016 / Revised: 22 November 2016 / Accepted: 5 December 2016 / Published: 15 December 2016
PDF Full-text (2497 KB) | HTML Full-text | XML Full-text
Abstract
When we encounter a malicious rumor or an infectious disease outbreak, immunizing k nodes of the relevant network with limited resources is always treated as an extremely effective method. The key challenge is how we can insulate limited nodes to minimize the propagation
[...] Read more.
When we encounter a malicious rumor or an infectious disease outbreak, immunizing k nodes of the relevant network with limited resources is always treated as an extremely effective method. The key challenge is how we can insulate limited nodes to minimize the propagation of those contagious things. In previous works, the best k immunised nodes are selected by learning the initial status of nodes and their strategies even if there is no feedback in the propagation process, which eventually leads to ineffective performance of their solutions. In this paper, we design a novel vaccines placement strategy for protecting much more healthy nodes from being infected by infectious nodes. The main idea of our solution is that we are not only utilizing the status of changing nodes as auxiliary knowledge to adjust our scheme, but also comparing the performance of vaccines in various transmission slots. Thus, our solution has a better chance to get more benefit from these limited vaccines. Extensive experiments have been conducted on several real-world data sets and the results have shown that our algorithm has a better performance than previous works. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle A Robust and Device-Free System for the Recognition and Classification of Elderly Activities
Sensors 2016, 16(12), 2043; doi:10.3390/s16122043
Received: 25 October 2016 / Revised: 25 November 2016 / Accepted: 29 November 2016 / Published: 1 December 2016
PDF Full-text (1714 KB) | HTML Full-text | XML Full-text
Abstract
Human activity recognition, tracking and classification is an essential trend in assisted living systems that can help support elderly people with their daily activities. Traditional activity recognition approaches depend on vision-based or sensor-based techniques. Nowadays, a novel promising technique has obtained more attention,
[...] Read more.
Human activity recognition, tracking and classification is an essential trend in assisted living systems that can help support elderly people with their daily activities. Traditional activity recognition approaches depend on vision-based or sensor-based techniques. Nowadays, a novel promising technique has obtained more attention, namely device-free human activity recognition that neither requires the target object to wear or carry a device nor install cameras in a perceived area. The device-free technique for activity recognition uses only the signals of common wireless local area network (WLAN) devices available everywhere. In this paper, we present a novel elderly activities recognition system by leveraging the fluctuation of the wireless signals caused by human motion. We present an efficient method to select the correct data from the Channel State Information (CSI) streams that were neglected in previous approaches. We apply a Principle Component Analysis method that exposes the useful information from raw CSI. Thereafter, Forest Decision (FD) is adopted to classify the proposed activities and has gained a high accuracy rate. Extensive experiments have been conducted in an indoor environment to test the feasibility of the proposed system with a total of five volunteer users. The evaluation shows that the proposed system is applicable and robust to electromagnetic noise. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle Optimal Resource Allocation Policies for Multi-User Backscatter Communication Systems
Sensors 2016, 16(12), 2016; doi:10.3390/s16122016
Received: 26 October 2016 / Revised: 23 November 2016 / Accepted: 24 November 2016 / Published: 29 November 2016
Cited by 3 | PDF Full-text (386 KB) | HTML Full-text | XML Full-text
Abstract
This paper considers a backscatter communication (BackCom) system including a reader and N tags, where each tag receives excitation signals transmitted by the reader and concurrently backscatters information to the reader in time-division-multiple-access (TDMA) mode. In this system, we aim to maximize the
[...] Read more.
This paper considers a backscatter communication (BackCom) system including a reader and N tags, where each tag receives excitation signals transmitted by the reader and concurrently backscatters information to the reader in time-division-multiple-access (TDMA) mode. In this system, we aim to maximize the total system goodput by jointly optimizing reader transmission power, time allocation, and reflection ratio for the cases of passive and semi-passive tags. For each case, an optimization problem is formulated, which is non-convex and can be solved by being decomposed into at most N feasible sub-problems based on the priority of allocated reader transmission power. First, for the passive tags case, by solving the convex sub-problems sequentially and comparing their maximum total goodput, we derive the optimal resource allocation policy. Then, for the semi-passive tags case, we find a close-to-optimal solution, since each sub-problem can be reformulated as a biconvex problem, which is solved by a proposed block coordinate descent (BCD)-based optimization algorithm. Finally, simulation results demonstrate the superiority of the proposed resource allocation policies. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle Task and Participant Scheduling of Trading Platforms in Vehicular Participatory Sensing Networks
Sensors 2016, 16(12), 2013; doi:10.3390/s16122013
Received: 30 October 2016 / Revised: 23 November 2016 / Accepted: 23 November 2016 / Published: 28 November 2016
PDF Full-text (1323 KB) | HTML Full-text | XML Full-text
Abstract
The vehicular participatory sensing network (VPSN) is now becoming more and more prevalent, and additionally has shown its great potential in various applications. A general VPSN consists of many tasks from task, publishers, trading platforms and a crowd of participants. Some literature treats
[...] Read more.
The vehicular participatory sensing network (VPSN) is now becoming more and more prevalent, and additionally has shown its great potential in various applications. A general VPSN consists of many tasks from task, publishers, trading platforms and a crowd of participants. Some literature treats publishers and the trading platform as a whole, which is impractical since they are two independent economic entities with respective purposes. For a trading platform in markets, its purpose is to maximize the profit by selecting tasks and recruiting participants who satisfy the requirements of accepted tasks, rather than to improve the quality of each task. This scheduling problem for a trading platform consists of two parts: which tasks should be selected and which participants to be recruited? In this paper, we investigate the scheduling problem in vehicular participatory sensing with the predictable mobility of each vehicle. A genetic-based trading scheduling algorithm (GTSA) is proposed to solve the scheduling problem. Experiments with a realistic dataset of taxi trajectories demonstrate that GTSA algorithm is efficient for trading platforms to gain considerable profit in VPSN. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle On Performance Analysis of Protective Jamming Schemes in Wireless Sensor Networks
Sensors 2016, 16(12), 1987; doi:10.3390/s16121987
Received: 31 October 2016 / Revised: 16 November 2016 / Accepted: 20 November 2016 / Published: 24 November 2016
PDF Full-text (571 KB) | HTML Full-text | XML Full-text
Abstract
Wireless sensor networks (WSNs) play an important role in Cyber Physical Social Sensing (CPSS) systems. An eavesdropping attack is one of the most serious threats to WSNs since it is a prerequisite for other malicious attacks. In this paper, we propose a novel
[...] Read more.
Wireless sensor networks (WSNs) play an important role in Cyber Physical Social Sensing (CPSS) systems. An eavesdropping attack is one of the most serious threats to WSNs since it is a prerequisite for other malicious attacks. In this paper, we propose a novel anti-eavesdropping mechanism by introducing friendly jammers to wireless sensor networks (WSNs). In particular, we establish a theoretical framework to evaluate the eavesdropping risk of WSNs with friendly jammers and that of WSNs without jammers. Our theoretical model takes into account various channel conditions such as the path loss and Rayleigh fading, the placement schemes of jammers and the power controlling schemes of jammers. Extensive results show that using jammers in WSNs can effectively reduce the eavesdropping risk. Besides, our results also show that the appropriate placement of jammers and the proper assignment of emitting power of jammers can not only mitigate the eavesdropping risk but also may have no significant impairment to the legitimate communications. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle 3D Tracking via Shoe Sensing
Sensors 2016, 16(11), 1809; doi:10.3390/s16111809
Received: 6 September 2016 / Revised: 15 October 2016 / Accepted: 20 October 2016 / Published: 28 October 2016
PDF Full-text (14866 KB) | HTML Full-text | XML Full-text
Abstract
Most location-based services are based on a global positioning system (GPS), which only works well in outdoor environments. Compared to outdoor environments, indoor localization has created more buzz in recent years as people spent most of their time indoors working at offices and
[...] Read more.
Most location-based services are based on a global positioning system (GPS), which only works well in outdoor environments. Compared to outdoor environments, indoor localization has created more buzz in recent years as people spent most of their time indoors working at offices and shopping at malls, etc. Existing solutions mainly rely on inertial sensors (i.e., accelerometer and gyroscope) embedded in mobile devices, which are usually not accurate enough to be useful due to the mobile devices’ random movements while people are walking. In this paper, we propose the use of shoe sensing (i.e., sensors attached to shoes) to achieve 3D indoor positioning. Specifically, a short-time energy-based approach is used to extract the gait pattern. Moreover, in order to improve the accuracy of vertical distance estimation while the person is climbing upstairs, a state classification is designed to distinguish the walking status including plane motion (i.e., normal walking and jogging horizontally), walking upstairs, and walking downstairs. Furthermore, we also provide a mechanism to reduce the vertical distance accumulation error. Experimental results show that we can achieve nearly 100% accuracy when extracting gait patterns from walking/jogging with a low-cost shoe sensor, and can also achieve 3D indoor real-time positioning with high accuracy. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle Combating QR-Code-Based Compromised Accounts in Mobile Social Networks
Sensors 2016, 16(9), 1522; doi:10.3390/s16091522
Received: 3 July 2016 / Revised: 10 September 2016 / Accepted: 12 September 2016 / Published: 20 September 2016
Cited by 1 | PDF Full-text (420 KB) | HTML Full-text | XML Full-text
Abstract
Cyber Physical Social Sensing makes mobile social networks (MSNs) popular with users. However, such attacks are rampant as malicious URLs are spread covertly through quick response (QR) codes to control compromised accounts in MSNs to propagate malicious messages. Currently, there are generally two
[...] Read more.
Cyber Physical Social Sensing makes mobile social networks (MSNs) popular with users. However, such attacks are rampant as malicious URLs are spread covertly through quick response (QR) codes to control compromised accounts in MSNs to propagate malicious messages. Currently, there are generally two types of methods to identify compromised accounts in MSNs: one type is to analyze the potential threats on wireless access points and the potential threats on handheld devices’ operation systems so as to stop compromised accounts from spreading malicious messages; the other type is to apply the method of detecting compromised accounts in online social networks to MSNs. The above types of methods above focus neither on the problems of MSNs themselves nor on the interaction of sensors’ messages, which leads to the restrictiveness of platforms and the simplification of methods. In order to stop the spreading of compromised accounts in MSNs effectively, the attacks have to be traced to their sources first. Through sensors, users exchange information in MSNs and acquire information by scanning QR codes. Therefore, analyzing the traces of sensor-related information helps to identify the compromised accounts in MSNs. This paper analyzes the diversity of information sending modes of compromised accounts and normal accounts, analyzes the regularity of GPS (Global Positioning System)-based location information, and introduces the concepts of entropy and conditional entropy so as to construct an entropy-based model based on machine learning strategies. To achieve the goal, about 500,000 accounts of Sina Weibo and about 100 million corresponding messages are collected. Through the validation, the accuracy rate of the model is proved to be as high as 87.6%, and the false positive rate is only 3.7%. Meanwhile, the comparative experiments of the feature sets prove that sensor-based location information can be applied to detect the compromised accounts in MSNs. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle Distributed Particle Filter for Target Tracking: With Reduced Sensor Communications
Sensors 2016, 16(9), 1454; doi:10.3390/s16091454
Received: 28 April 2016 / Revised: 2 September 2016 / Accepted: 2 September 2016 / Published: 9 September 2016
Cited by 2 | PDF Full-text (309 KB) | HTML Full-text | XML Full-text
Abstract
For efficient and accurate estimation of the location of objects, a network of sensors can be used to detect and track targets in a distributed manner. In nonlinear and/or non-Gaussian dynamic models, distributed particle filtering methods are commonly applied to develop target tracking
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For efficient and accurate estimation of the location of objects, a network of sensors can be used to detect and track targets in a distributed manner. In nonlinear and/or non-Gaussian dynamic models, distributed particle filtering methods are commonly applied to develop target tracking algorithms. An important consideration in developing a distributed particle filtering algorithm in wireless sensor networks is reducing the size of data exchanged among the sensors because of power and bandwidth constraints. In this paper, we propose a distributed particle filtering algorithm with the objective of reducing the overhead data that is communicated among the sensors. In our algorithm, the sensors exchange information to collaboratively compute the global likelihood function that encompasses the contribution of the measurements towards building the global posterior density of the unknown location parameters. Each sensor, using its own measurement, computes its local likelihood function and approximates it using a Gaussian function. The sensors then propagate only the mean and the covariance of their approximated likelihood functions to other sensors, reducing the communication overhead. The global likelihood function is computed collaboratively from the parameters of the local likelihood functions using an average consensus filter or a forward-backward propagation information exchange strategy. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle A Greedy Scanning Data Collection Strategy for Large-Scale Wireless Sensor Networks with a Mobile Sink
Sensors 2016, 16(9), 1432; doi:10.3390/s16091432
Received: 15 July 2016 / Revised: 27 August 2016 / Accepted: 30 August 2016 / Published: 6 September 2016
Cited by 2 | PDF Full-text (1966 KB) | HTML Full-text | XML Full-text
Abstract
Mobile sink is widely used for data collection in wireless sensor networks. It can avoid ‘hot spot’ problems but energy consumption caused by multihop transmission is still inefficient in real-time application scenarios. In this paper, a greedy scanning data collection strategy (GSDCS) is
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Mobile sink is widely used for data collection in wireless sensor networks. It can avoid ‘hot spot’ problems but energy consumption caused by multihop transmission is still inefficient in real-time application scenarios. In this paper, a greedy scanning data collection strategy (GSDCS) is proposed, and we focus on how to reduce routing energy consumption by shortening total length of routing paths. We propose that the mobile sink adjusts its trajectory dynamically according to the changes of network, instead of predetermined trajectory or random walk. Next, the mobile sink determines which area has more source nodes, then it moves toward this area. The benefit of GSDCS is that most source nodes are no longer needed to upload sensory data for long distances. Especially in event-driven application scenarios, when event area changes, the mobile sink could arrive at the new event area where most source nodes are located currently. Hence energy can be saved. Analytical and simulation results show that compared with existing work, our GSDCS has a better performance in specific application scenarios. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle Queuing Theory Based Co-Channel Interference Analysis Approach for High-Density Wireless Local Area Networks
Sensors 2016, 16(9), 1348; doi:10.3390/s16091348
Received: 16 June 2016 / Revised: 10 August 2016 / Accepted: 12 August 2016 / Published: 23 August 2016
Cited by 1 | PDF Full-text (1333 KB) | HTML Full-text | XML Full-text
Abstract
Increased co-channel interference (CCI) in wireless local area networks (WLANs) is bringing serious resource constraints to today’s high-density wireless environments. CCI in IEEE 802.11-based networks is inevitable due to the nature of the carrier sensing mechanism however can be reduced by resource optimization
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Increased co-channel interference (CCI) in wireless local area networks (WLANs) is bringing serious resource constraints to today’s high-density wireless environments. CCI in IEEE 802.11-based networks is inevitable due to the nature of the carrier sensing mechanism however can be reduced by resource optimization approaches. That means the CCI analysis is basic, but also crucial for an efficient resource management. In this article, we present a novel CCI analysis approach based on the queuing theory, which considers the randomness of end users’ behavior and the irregularity and complexity of network traffic in high-density WLANs that adopts the M/M/c queuing model for CCI analysis. Most of the CCIs occur when multiple networks overlap and trigger channel contentions; therefore, we use the ratio of signal-overlapped areas to signal coverage as a probabilistic factor to the queuing model to analyze the CCI impacts in highly overlapped WLANs. With the queuing model, we perform simulations to see how the CCI influences the quality of service (QoS) in high-density WLANs. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks
Sensors 2016, 16(7), 1081; doi:10.3390/s16071081
Received: 4 June 2016 / Revised: 6 July 2016 / Accepted: 8 July 2016 / Published: 14 July 2016
Cited by 2 | PDF Full-text (4636 KB) | HTML Full-text | XML Full-text
Abstract
Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance
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Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle’s position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
Open AccessArticle A Cyber-Physical System for Girder Hoisting Monitoring Based on Smartphones
Sensors 2016, 16(7), 1048; doi:10.3390/s16071048
Received: 18 May 2016 / Revised: 23 June 2016 / Accepted: 4 July 2016 / Published: 7 July 2016
Cited by 3 | PDF Full-text (14953 KB) | HTML Full-text | XML Full-text
Abstract
Offshore design and construction is much more difficult than land-based design and construction, particularly due to hoisting operations. Real-time monitoring of the orientation and movement of a hoisted structure is thus required for operators’ safety. In recent years, rapid development of the smart-phone
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Offshore design and construction is much more difficult than land-based design and construction, particularly due to hoisting operations. Real-time monitoring of the orientation and movement of a hoisted structure is thus required for operators’ safety. In recent years, rapid development of the smart-phone commercial market has offered the possibility that everyone can carry a mini personal computer that is integrated with sensors, an operating system and communication system that can act as an effective aid for cyber-physical systems (CPS) research. In this paper, a CPS for hoisting monitoring using smartphones was proposed, including a phone collector, a controller and a server. This system uses smartphones equipped with internal sensors to obtain girder movement information, which will be uploaded to a server, then returned to controller users. An alarming system will be provided on the controller phone once the returned data exceeds a threshold. The proposed monitoring system is used to monitor the movement and orientation of a girder during hoisting on a cross-sea bridge in real time. The results show the convenience and feasibility of the proposed system. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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