editorial big data and knowledge extraction for cyber...

EditorialBig Data and Knowledge Extraction for Cyber-Physical Systems

Xiuzhen Cheng,1 Yunchuan Sun,2 Antonio Jara,3 Houbing Song,4 and Yingjie Tian5

1The George Washington University, Washington, DC 20052, USA2Beijing Normal University, Beijing 100875, China3The University of Applied Sciences Western Switzerland (HES-SO), 3960 Sierre, Switzerland4West Virginia University, Montgomery, WV 25136, USA5Chinese Academy of Sciences, Beijing 100190, China

Correspondence should be addressed to Xiuzhen Cheng; [email protected]

Received 2 July 2015; Accepted 5 July 2015

Copyright © 2015 Xiuzhen Cheng et al.This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Cyber-Physical Systems (CPS) have come into our view andwill be applied in our daily life and business process man-agement. Emerging CPS are coordinated, distributed, andconnected and must be robust and responsive. Tomorrow’sCPS need to far exceed the systems of today in capability,adaptability, resiliency, safety, security, and usability. Big dataare large, complex, or rapidly generated datasets that cannotbe processed by traditional technologies. Decision makers,resource managers, engineers, first-responders, scientists,and citizens are faced with a multitude of constantly flowingdata streams coming from many sources in many formatsevery day. Understanding the volumes of big data requirescutting-edge tools and techniques that can analyze andextract useful knowledge from vast and diverse streams ofinformation. The wonderful living of human beings and thehigh efficiency of business rely mostly on how to intelligentlyand correctly use the big data and how to retrieve usefulknowledge from the massive data, such that it would bepossible to seamlessly integrate the virtual world and thephysical world.

This special issue aims to explore the above challengesthrough papers that address (1) big data analytics and infor-mation processing in CPS, (2) knowledge extraction fromthe big sensing data in CPS, and (3) other issues (such assecurity and privacy) relevant to big data and knowledgeprocessing in CPS. We received 60 submissions from bothacademia and industry. Each paper was peer-reviewed by atleast two experts in the field. In the following, we provide abrief introduction to each accepted paper.

The paper “Data Mining for the Internet of Things:Literature Review and Challenges” by F. Chen et al. presentsa systematic overview on data mining in view of knowledge,technique, and application, including classification, cluster-ing, association analysis, time series analysis, and outlieranalysis. Some new application cases and new algorithmsare also reviewed. Challenges and open research issues inthis field are discussed and a big data mining system is sug-gested.

The paper “A Phoenix++ Based New Genetic AlgorithmInvolvingMechanism of Simulated Annealing” by L. Hu et al.provides a novel MapReduce enabled simulated annealinggenetic algorithm to increase the efficiency of the high-performance distributed computing platforms, which arecharacterized by the synthesis of the genetic algorithm andthe simulated annealing algorithm and parallelism. Theexperiments on Phoenix++ indicate that the convergencespeed of the proposed algorithm outperforms the traditionalones significantly.

The paper “Privacy Information Security Classificationfor Internet of Things Based on Internet Data” by X. Luet al. focuses on studying the attributes of the privacy andproposes the Privacy Information Security Classification(PISC) model. The privacy issues are classified into foursecurity categories by PISC, and each category has its ownsecurity goal.

The paper “A Novel Dynamic Weight Neural NetworkEnsemble Model” by K. Li et al. proposes a novel dynamicweight neural network ensemble model (DW-NNE). The

Hindawi Publishing CorporationInternational Journal of Distributed Sensor NetworksVolume 2015, Article ID 231527, 4 pageshttp://dx.doi.org/10.1155/2015/231527

2 International Journal of Distributed Sensor Networks

bagging algorithm generates certain neural network individ-uals that are selected by the 𝑘-means clustering algorithm.𝐾-value optimization algorithm is put forward based on adistance cost function to find the optimal 𝐾-values. It alsoproposes a dynamic weight model based on fuzzy neuralnetwork in accordance with the ideas of dynamic weight.

The paper “AReliable Broadcast Protocol inVehicular AdHoc Networks” by C. Wang et al. proposes a MAC protocolbased on the s-disjunct code to achieve reliable and real-time broadcasts via assigning a channel to each vehicle as thevehicle enters the network, which is adaptive as vehicles arerequired to adjust their communication ranges according tothe network density in order to avert the interference amongthem. Even at a high vehicle density, the proposed schemeguarantees high success rates.

The paper titled “Online Optimization of CollaborativeWeb ServiceQoS Prediction Based onApproximateDynamicProgramming” by X. Luo et al. presents an algorithm that canincorporate approximate dynamic programming- (ADP-)based online parameter tuning strategy into the QoS predic-tion approach. The prior knowledge or identification of theprediction model is not required as the proposed approachcan reach the QoS prediction with the automatic parametertuning capability.

The paper “Device-to-Device Users Clustering Basedon Physical and Social Characteristics” by L. Wang et al.proposes a novel method for device-to-device (D2D)user clustering that allows wireless users in proximity toshare common resources to save both system bandwidthand energy resources, based on two proposed clusteringapproaches: the Chinese Restaurant Process (CRP) and thedistance-dependent Chinese Restaurant Process (DCRP).Numerical simulation results show the superiority of theproposed clustering schemes in terms of energy consumptionand energy efficiency.

The paper “An Approach for Prediction of AcuteHypotensive Episodes via the Hilbert-Huang Transform andMultiple Genetic Programming Classifier” by D. Jiang et al.presents a methodology to predict AHE for ICU patientsbased on big data time series. The experimental data isMeanArterial Pressure (MAP) transformed from theArterialBlood Pressure (ABP) data. The methodology is applied inthe datasets of the 10th PhysioNet andComputers CardiologyChallenge in 2009 and Multiparameter Intelligent Monitor-ing for Intensive Care (MIMIC-II). The accuracy of 83.33%in the training set and 91.89% in the testing set of the 2009Challenge’s dataset and 84.13% in the training set and 82.41%in the testing set of the MIMIC-II dataset are achieved.

A scheme using Extended Service Set (ESS) based archi-tecture is presented to implement the proxy mobile IPv6protocol, that is, PMIPv6, for IEEE 802.11 infrastructureWireless Local Area Networks (WLANs) in the paper titled“Implementing PMIPv6 Protocol Based on Extended ServiceSet for IEEE 802.11 Infrastructure WLAN” by D. Zhu et al.The key signaling packets together with their time sequencesfor the mobility management in the proposed scheme areproposed. Numerical analysis indicates the proposed schemeoutperforms the existing one that uses the Basic Service Set(BSS) based architecture in terms of handoff delay in the case

when the delay between Mobile Access Gateway (MAG) andLocal Mobile Anchor (LMA) is relatively large.

The paper “New Benchmarking Methodology and Pro-gramming Model for Big Data Processing” by A. Kos etal. presents a possible solution for the coming exascale bigdata processing: a data flow computing concept. A newbenchmarking methodology is proposed, which integratesthe performance issues of speed, area, and power neededto execute the task. According to the authors, the next stepof data flow computing development should be a movefrom specialized to more general algorithms and appli-cations.

The paper “Context-Aware Recommendation via Graph-Based ContextualModeling and Postfiltering” by H.Wu et al.proposes a graph-based framework tomodel and incorporatecontextual information into the recommendation processin an advantageous way to help the development and useof context-aware recommendation capabilities. A contex-tual graph-based relevance measure (CGR) is specificallydesigned to assess the potential relevance between the targetuser and the items further used to make an item recommen-dation. A probabilistic-based postfiltering strategy is pro-posed to refine the recommendation results. Experimentalresults show the superiority and the effectiveness in context-aware recommendation scenario.

The paper “Waypoint Graph Based Fast Pathfinding inDynamic Environment” by W. Zhu et al. proposes a fastapproach for waypoint graph-based pathfinding. Unneces-sary waypoints and edges are eliminated to make the graphsparse. A prediction-based local method is also designed tohandle the dynamic change in the environment. Extensivesimulation results show the proposed approach outperformsexisting ones.

The paper “Model-Based Sensitivity Analysis on AerosolOptical Thickness Prediction,” by B. Han et al., proposesa support vector regression (SVR) model-based sensitivityanalysis approach to order 35MODIS input attributes accord-ing to their sensitivity to prediction outputs. The attributesensitivity orders are used for feature selection in the contextof regression by removing insensitive attributes one at a timeor by removing attributes whose sensitive orders are largerthan a number 𝑘. Experimental results show that the top 10insensitive attributes can be screened to speed up predictionmodel computation with very little loss of accuracy. Theproposed approach would be useful for remote sensingscientists or atmospheric scientists to optimize the designprecision of top sensitive attributes in scanning equipmentlike MODIS to improve the AOT retrieval accuracy.

The paper “Enterprise-Oriented IoT Name Service forAgricultural Product Supply Chain Management” by Y. Liuet al. presents a simple and efficient enterprise-oriented nameservice, namely, iotNS, which is designed for agriculturalproducts with faster response than the standard GS1 ONSsystem. The iotNS has been deployed across five cities toenable the efficient storage and retrieval of information aboutagricultural products as they are tracked from the farm to themarket. The deployment shows that iotNS is a mechanismthat fosters cooperation and supply chain improvementsamong the enterprises using the iotNS.

International Journal of Distributed Sensor Networks 3

The paper “A Dynamic Processing System for SensorData in IoT” by M. Li et al. proposes a dynamic sensordata processing (SDP) system to capture and process sensordata continuously on the basis of data streaming technologyaccording the characteristics of the sensor data in IoT,which uses Particle Swarm Optimization (PSO) algorithm totrain threshold dynamically for data compression avoidingredundancy. The experimental results show that SDP cancompress sensor data through dynamically balancing theaccuracy and compression rate.

The paper “Enhanced Asymmetric Bilinear Model forFace Recognition” by W. Gong et al. proposes an enhancedasymmetric model for illumination robust face recognitionwhich initializes the factor probabilities with nearest neigh-bormethod and optimizes it for the test data.The experimentresults show that the enhanced asymmetric model can reacha high recognition accuracy.

Addressing MAC protocol for wireless network based onultrawide band (UWB) to solve the problems of real-timeservices and reliability in wireless transmitting, the papertitled “The Study on Media Access Control Protocol forWireless Network in Library” by W. Zeng et al. proposes amultichannel MAC protocol (UWBIMAC) based on status-adaptiveness to choose the channel mechanism. Simulationresults show that the protocol has the ability of stronger anti-jamming, improves the network throughput, and providesbetter average delay performance than IEEE 802.15.4MAC,IEEE 802.11MAC, and other UWBMAC protocols.

The paper “Minimized Cost Gateway Deployment inCyber-Physical Systems” by H. Wang et al. addresses theproblem of gateway placement for satisfying the bandwidth-requirement of each node by usingminimumgateways whichcan be formulated as a variant of Minimum Geometric DiskCover problem.Aheuristic gateway placement algorithm andone grid-based heuristic algorithm are proposed for this NP-complete problem.The result of simulation demonstrates thatthe heuristic algorithm can offer a good solution with bigprobability.

The paper “A Genetic-Algorithm-Based Approach forTask Migration in Pervasive Clouds” by W. Zhang et al.proposes a genetic-algorithm- (GA-) based approach that iseffective in addressingmultiobjective optimization problems.The preliminary evaluations show quite promising results byusing one of the classical genetic algorithms and the GAs canbe used for decision making in task migrations in pervasiveclouds.

The paper “Development and Validation of a PortableHuman Body Joint Power Test System” by L. Li et al.presents a portable human body joint power test system usinginertial sensor technology and wireless Bluetooth acquisitiontechnology. The test system can be applied into many areassuch as athlete selection and daily strength training.

A two-dimension code spatiotemporal modeling methodis proposed in the paper “Two-Dimensional Code BasedSpatiotemporal Modeling and its Application in ObjectTracing” by Y. Gao et al. Two-dimension code is used tostore object’s characteristics in the smartphone to obtainthe object’s real-time spatiotemporal data. A use case to

trace object’s spatiotemporal information is also developed tovalidate the proposed modeling method.

Due to the imbalanced energy consumption amongnodes in wireless sensor networks, some nodes die pre-maturely, which decreases the network lifetime. Address-ing this problem, the paper “IDUC: An Improved Dis-tributed Unequal Clustering Protocol for Wireless SensorNetworks” byC. Chen et al. proposes an improved distributedunequal clustering protocol (IDUC) for wireless sensor net-works, where nodes are energy heterogeneous and scatteredunevenly. The cores of IDUC are the formation of unequalcluster topology and the construction of intercluster com-munication routing tree. Compared with previous protocols,IDUC is suitable for various network scenarios, and it canbalance the energy consumption more efficiently and extendthe lifetime of networks significantly.

The paper “Vehicular Ad Hoc Networks: Architectures,Research Issues, Methodologies, Challenges, and Trends” byW. Liang et al. provides an overview of the main aspectsof VANETs from a research perspective including the archi-tecture, research issues and general research methods, andchallenges and future trends of VANETs.

In the paper “Identifying Missing and Spurious Interac-tions in Directed Networks” by X. Zhang et al., the authorsmake use of classical link prediction indices for undirectednetworks, adapt them to directed versionwhich could predictboth the existence and direction of an arc between twonodes, and investigate their prediction ability on six real-world directed networks. Experimental results demonstratethat those modified indices perform quite well in directednetworks. Compared with bifan predictor, some of them canprovide more accurate predictions.

The paper “AMultimodel Based Range Query ProcessingAlgorithm for Information Collection in CPS” by G. Li et al.proposes a multimodel based range query processing algo-rithm, which utilizes multiple probability models to depictthe data distribution of a sensor node. Compared with thesingle model-based algorithm, the data distribution depictedby the multimodel based algorithm is much more accuratethan that of the single one. Experiments on real dataset showthe efficiency of the proposed model.

The paper “Deadline Aware Retransmission ThresholdSetting Protocol In Cyber-Physical Systems” by R. Bi et al.investigates the problem in finding the optimal retransmis-sion thresholds for the relay nodes along given delivery path,such that the summation of the probability of the packetbeing transmitted to the next relay node or destination nodewithin the specified deadline is maximized. A distributedgreedy algorithm is proposed for computing the optimalretransmission threshold. Experimental results show that theproposed protocols have better performance in terms ofdeadline success ratio and real-time ratio.

Addressing real-time transmitting in CPS, the paper“Handling Interservice Time Constraints in Wireless Net-works” by X. Zheng et al. designs an interservice timeguaranteed scheduling which defines a new capacity regionof networks with a strict interservice time and a novelscheduling policy. Simulation results show the frameworkperforms well in interservice time and throughput.

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Acknowledgments

We would like to thank all authors for their valuable contri-butions to this special issue. We are indebted to the journaleditors and all anonymous reviewers for their hard workthat helps the authors further enhance the quality of themanuscripts. It is also an honor for us to serve as the GuestEditors of this issue.

Xiuzhen ChengYunchuan SunAntonio Jara

Houbing SongYingjie Tian

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