Editorial Advanced Mathematics and Numerical Modeling of IoT

EditorialAdvanced Mathematics and Numerical Modeling of IoT

Young-Sik Jeong,1 Mohammad S. Obaidat,2 Jianhua Ma,3 and Laurence T. Yang4

1Department of Multimedia Engineering, Dongguk University, Seoul 100-715, Republic of Korea2Department of Computer Science and Software Engineering, Monmouth University, West Long Branch, NJ 07764-1898, USA3Faculty of Computer and Information Sciences, Hosei University, Tokyo 102-8160, Japan4Department of Computer Science, St. Francis Xavier University, P.O. Box 5000, Antigonish, NS, Canada

Correspondence should be addressed to Young-Sik Jeong; [email protected]

Received 13 October 2014; Accepted 13 October 2014

Copyright © 2015 Young-Sik Jeong et al. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.

Recent advances in the Internet of Things (IoT) have posedgreat challenges to computer science and engineering. Inter-net of Things systems manage huge numbers of heteroge-neous sensors and/or mobile devices which continuouslymobile of the states of real-world objects, and most data aregenerated automatically throughmobile networking environ-ments. Internet of Things frameworks might help supportthe interaction between “things” and allow for more complexstructures like Distributed/Grid/Cloud computing and thedevelopment of Distributed/Grid/Cloud applications. Cur-rently, some Internet of Things frameworks seem to focuson real-time data logging solutions, which are offering somebasis to workwithmany “things.” Future developmentsmightlead to specific software development environments to createthe software to work with the hardware used in the Internetof Things [1–3]. IoT is also a novel paradigm that is rapidlygaining in the scenario of wireless sensor networks andwireless telecommunications. The basic idea of this conceptis the pervasive presence around our life style of a variety ofthings or objects [2, 4, 5].

The advanced mathematics and numerical modeling ofIoT is being driven by and used in a wide range of academic,research, and commercial application areas. This use isproducing important new practical experience in a varietyof different problem domains in each of these areas. Thereare also new computational methods in these research fields.As an enabler, this technology is leading to a rapid growthin both scientific and information applications that will,in turn, enable additional requirements for the advanced

mathematics and numerical modeling of Internet of Thingsto be identified. These will impact academia, business, andeducation [1, 3, 5].

This special issue aims to provide advanced theory andapplication for researchers and practitioners to contributeoriginal research and review articles that present the state-of-the-art research outcomes, practical results, latest findings,and future evolutions of mathematics in IoT applications.

We have received many manuscripts and the publishedmanuscripts with high quality were finally selected for thisspecial issue. Each manuscript selected was blindly reviewedby at least three reviewers consisting of guest editors andexternal reviewers. We present a brief overview of eachmanuscript in the following.

Recent advances inmathematics and numericalmodelingof Internet of Things have created new topics of interestincluding the following: (1) mathematical and numericalmodeling of smart city including smartphone real-world andmobile networks, (2) optimization methods, mathematicsmodeling for smart Grid with Cloud computing, (3) numeri-cal analysis for security and emergencies in IoT, (4) methodsfor improving efficiency or accuracy of M2M applicationsand vehicle autodiagnosis, (5) adaptive and dynamic algo-rithms for home automation and e-health applications, (6)computational models of communication mechanisms formobile networks in IoT, and (7) advanced modeling for IoTapplications as mobile/vehicle ad hoc networks and mobilesensor networks in CPS (cyber physical system).

Hindawi Publishing CorporationJournal of Applied MathematicsVolume 2015, Article ID 824891, 5 pageshttp://dx.doi.org/10.1155/2015/824891

2 Journal of Applied Mathematics

In these several topics of the advanced mathematics andnumericalmodeling of IoT (Internet ofThings), some articlesproposed the following.

D. Lim et al. proposed a fall-detection algorithm using3-axis acceleration. The fall-feature parameters, calculatedfrom the 3-axis acceleration, are applied to a simple thresholdmethod. Then, the falls that are determined from the simplethreshold are applied to the HMM to distinguish betweenfalls and ADLs. The results from a simple threshold, HMM,and the combination of the simple method and HMM arecompared and analyzed.

H.-S. Ham et al. applied a linear support vector machine(SVM) to detect Android malware and compare the malwaredetection performance of SVM with that of other machinelearning classifiers. Through experimental validation, theyshow that the SVM outperforms other machine learningclassifiers.

J. Park and M.-J. Lee presented a context distributionframework named SCondi utilizing the messaging servicewhich supports MQTT—an OASIS standard IoT messagingprotocol. SCondi provides the notion of context channel asa core feature to support efficient and reliable mechanismfor distributing huge context information in the IoT environ-ment.The context channel provides a pluggable filter mecha-nism that supports effective extraction, tailoring, authentica-tion, and security of information.

S.-H. Lu and Y.-W. Chan proposed a method of com-bining a peer-to-peer (P2P) overlay network and WSN todevelop a bus arrival time prediction system. A P2P overlaynetwork is added to traditional prediction systems to allowfor real-time data. Each bus is installed with a sensor, andeach bus stop can receive data sent from sensors. Due tothe distance limitation of sensors, the sensors on buses andthe data-receiving device of a bus station form a singleWSN environment. All bus stations and station termini areconnected to form a P2P overlay network, which is used totransmit real-time bus information and predict bus arrivaltimes. Through the WSN technology, bus stations retrievedata from buses and transmit these data to subsequent busstations to estimate the bus arrival times. This approachcan be a powerful tool for monitoring and predicting trafficconditions.

S. Kang et al. proposed a group key sharing schemeand efficient rekeying methods for frequent membershipchanges from network dynamics. The proposed methodenables the group members to simply establish a group keyand provide high flexibility for dynamic group changes suchasmember joining or leaving and groupmerging or partition.They conduct mathematical evaluation with other groupkey management protocols and finally prove its security bydemonstrating group key secrecy, backward and forwardsecrecy, key independence, and implicit key authenticationunder the decisional Diffie-Hellman (DDH) assumption.

M. K. Song and M. K. Sarker proposed automatic detec-tion of car LPs via image processing techniques based onclassifier or machine learning algorithms. In this paper, theypropose a real-time and robust method for LPD systemsusing the two-stage adaptive boosting (AdaBoost) algorithmcombined with different image preprocessing techniques.

Haar-like features are used to compute and select featuresfrom LP images. The AdaBoost algorithm is used to classifyparts of an image within a search window by a trained strongclassifier as either LP or non-LP. Adaptive thresholding isused for the image preprocessing method applied to thoseimages that are of insufficient quality for LPD.This method isof a faster speed and higher accuracy thanmost of the existingmethods used in LPD. Experimental results demonstrate thatthe average LPD rate is 98.38% and the computational time isapproximately 49ms.

B. Lee and N. Park, International Association of Light-house Authorities (IALA), are developing the standard inter-system VTS exchange format (IVEF) protocol for exchangeof navigation and vessel information between VTS systemsand between VTS and vessels. VTS (vessel traffic system)is an important marine traffic monitoring system which isdesigned to improve the safety and efficiency of navigationand the protection of the marine environment. And thedemand of inter-VTS networking has been increased forrealization of e-navigation as shore side collaboration formaritime safety. And IVEF (inter-VTS data exchange format)for inter-VTS network has become a hot research topic ofVTS system. Currently, the IVEF developed by the Inter-national Association of Lighthouse Authorities (IALA) doesnot include any highly trusted certification technology forthe connectors. The output of standardization is distributedas the IALA recommendation V-145, and the protocol isimplemented with an open source. The IVEF open source,however, is the code used to check the functions of standardprotocols. It is too slow to be used in the field and requiresa large memory. And the vessel traffic information requireshigh security since it is highly protected by the countries.Therefore, this paper suggested the authentication protocolto increase the security of the VTS systems using the maincertification server and IVEF.

B. Wang et al. developed a novel model and protocolused in some specific scenarios, in which the participantsof multiple groups with different permissions can finish thesignature together. They applied the secret sharing schemebased on difference equation to the private key distributionphase and secret reconstruction phrase of their thresholdsignature scheme. In addition, their scheme can achieve thesignature success because of the punishment strategy of therepeated rational secret sharing. Besides, the bit commitmentand verification method used to detect players’ cheatingbehavior acts as a contributing factor to prevent the internalfraud.

D. Seo et al. presented the Korean spine database andautomatic surface mesh intersection algorithm to constructe-spine. To date, the Korean spine database has collectedspine data from 77 cadavers and 298 patients. The spine dataconsists of 2D images from CT, MRI, or X-ray, 3D shapes,geometry data, and property data. The volume and quality oftheKorean spine database are now theworld’s highest ones. Inaddition, their triangular surfacemesh intersection algorithmautomatically remeshes the spine-implant intersectionmodelto make it valid for finite element analysis (FEA).This makesit possible to run the FEA using the spine-implant meshmodel without any manual effort.

Journal of Applied Mathematics 3

L.-P. Hung et al. proposed a new framework using radiofrequency identification (RFID) technology for a mobilizedsurgical process monitoring system. Through the active tag,an application management system used before, during, andafter the surgical processes has been proposed.The concept ofsignal level matrix, SLM, was proposed to accurately identifypatients and dynamically track patients’ location. By updat-ing patient’s information real time, the preprocessing timeneeded for various tasks and incomplete transfers amongdepartments can be reduced, the medical resources canbe effectively used, unnecessary medical disputes can bereduced, and more comprehensive health care environmentcan be provided. The feasibility and effectiveness of theirproposed system are demonstrated with a number of experi-mental results.

K. Hwang and S.-H. Yoon provided a well-defined tax-onomy of low-power listening protocols by examining indetail the existing low-power sensor network protocols andevaluation results. It will also be very useful for helpingM2Mdesigners understand specific features of low-power mediaaccess control protocols as they design new M2M networks.

D. Jung et al. proposed the workflow scheduling schemethat reduces the out-of-bid situation. Consequently, the totaltask completion time is decreased. The simulation resultsreveal that, compared to various instance types, their schemeachieves performance improvements in terms of an averagecombined metric of 12.76% over workflow scheme withoutconsidering the processing rate. However, the cost in theirscheme is higher than an instance with low performance andis lower than an instance with high performance.

H.-J. Jeong et al. propose a multilayered quad rotor con-trol method that can move the quad rotor to the desired goalwhile resisting disturbance. The proposed control system ismodular, convenient to design and verify, and easy to extend.It comprises three layers: a physical layer, a displacementcontrol layer, and an attitude control layer. The displacementcontrol layer considers the movement of the vehicle, whilethe attitude control layer controls its attitude. The physicallayer deals with the physical operation of the vehicle.The twocontrol layers use a mathematical method to provide minutestep-by-step control. The proposed control system effectivelycombines the three layers to achieve drift stabilization.

K.-S. Wong and M. H. Kim studied a self-awareness datacollection protocol to raise the confidence of the respondentswhen submitting their personal data to the data collector.Their self-awareness protocol requires each respondent tohelp others in preserving individual privacy. The commu-nication (respondents and data collector) and collaboration(among respondents) in their solution will be performedautomatically.

H. K. Lee et al. provided the following contributions; theypresented a service design for an adaptive STB that decreasesthe dependence among scalable layers. Their adaptive STBconverts the receiving scalable streamswith high dependencyinto scalable streams with low dependency. As a result,it decreases the indirect loss of media data and increasesstreaming service performance even over mobile networks.They then analyzed a media scheme to convert scalablestreams.

S. Sivamani et al. proposed a smart logistics servicemodelfor providing user-centric intelligent logistics service byutilizing smartphones in a smart environment. They alsodevelop anOWLbased ontologymodel for the smart logisticsfor the better understanding among the context information.

S.-H. Chae et al. researched how to reconstruct seg-mentation region in a small region in order to improve thesegmentation results.They generated predicted segmentationof slices using volume data with linear equation and proposedimprovement method for small regions using the predictedsegmentation. In order to verify the performance of theproposed method, lung region by chest CT images wassegmented. As a result of experiments, volume data segmen-tation accuracy rose from 0.978 to 0.981 and from 0.281 to0.187 with a standard deviation improvement confirmed.

J.-H. Park et al. provided a higher level of abstraction byintegration of the two types of access interface, REST APIand MapReduce. The motivation of this research stems fromthe slower response time for accessing simple RDBMS onHadoop than direct access to RDMBS.This is because there isoverhead to job scheduling, initiating, starting, tracking, andmanagement during MapReduce-based parallel execution.Therefore, they provided a good performance for RESTOpenAPI service and for MapReduce, respectively.

D. Jung et al. proposed an estimated interval-based check-pointing (EIC) using weightedmoving average.Their schemesets the thresholds of price and execution time based onhistory. Whenever the actual price and the execution timecross over the thresholds, the system saves the state of spotinstances. The Bollinger Bands is adopted to inform theranges of estimated cost and execution time for user’s discre-tion.The simulation results reveal that, compared to theHBCand REC, the EIC reduces the number of checkpoints and therollback time. Consequently, the task execution time has beendecreased with EIC by HBC and REC.The EIC also providedthe benefit of the cost reduction byHBCandREC, on average.

D. Kang et al. discussed their approach and confirm thevalidity of their proposed system for preventing network andapplication protocol attacks in SCADA senor networks.

J. Song et al. presented a novel approach called TSMC(three-stage memory copy) for live virtual machine migra-tion. In TSMC, memory pages only need to be transmittedtwice at most and page fault just occurred in small part ofdirty pages. They implement it in Xen and compare it withXen’s original precopy approach. The experimental resultsunder variousmemory workloads show that TSMC approachcan significantly reduce the cumulative migration time andtotal pages transferred and achieve better network IO perfor-mance at the same time.

S.-Y. Ihm et al. propose a new skyline method (calledGrid-PPPS) for efficiently handling top-𝑘 queries in IoTapplications.Theproposedmethod first performsGrid-basedpartitioning on data space and then partitions it once againusing hyperplane projection. Experimental results show thattheir method improves the index building time compared tothe existing state-of-the-art methods.

K. Hwang and S. Nam introduced a DSME beaconscheduling model and present a concrete design model.

4 Journal of Applied Mathematics

Furthermore, validity and performance of DSME are evalu-ated through experiments. Based on experiment results, theyanalyzed the problems and limitations of DSME, presentedsolutions step by step, and finally proposed an enhancedDSME beacon schedulingmodel.Through additional experi-ments, they proved the performance superiority of enhancedDSME.

R. Su et al. compared the PMPGA (parallel multipopu-lation genetic algorithm) with the multiobjective fuzzy opti-mization algorithm and differential evolution based algo-rithm and showed that PMPGA has achieved better result.Themethod can bewidely applied to related high-speed train.

K.-C. Lin et al. proposed a classified model in which anartificial fish swarm algorithm and a support vector machineare combined. ALAN environment with several computerswhich has been infected by the botnet virus was simulatedfor testing this model; the packet data of network flow wasalso collected. The proposed method was used to identifythe critical features that determine the pattern of botnet.The experimental results indicated that the method can beused for identifying the essential botnet features and that theperformance of the proposed method was superior to that ofgenetic algorithms.

K.-C. Chu and L.-P. Hung proposed the TRPNmodel andprovided a practical, effective, and adaptive method for riskevaluation. In particular, the defined GRPN function offersa new method to prioritize failure modes in failure modeand effect analysis (FMEA). The different risk preferencesconsidered in the healthcare example show that the modifiedFMEA model can take into account the various risk factorsand prioritize failure modes more accurately.

S.-H. Park et al. proposed energy-efficient probabilisticrouting (EEPR) algorithm,which controls the transmission ofthe routing request packets stochastically in order to increasethe network lifetime and decrease the packet loss under theflooding algorithm. The proposed EEPR algorithm adoptsenergy-efficient probabilistic control by simultaneously usingthe residual energy of each node and ETX metric in thecontext of the typical AODV protocol. In the simulations,they verified that the proposed algorithm has longer networklifetime and consumes the residual energy of each nodemoreevenly when compared with the typical AODV protocol.

To overcome this limitation, H. Cho et al. tested theusability of a new conceptual autonomous emergency brak-ing (AEB) system that employs vehicle-to-vehicle (V2V)communication technology in the existing AEB system. Tothis end, a radar sensor and a driving and communicationenvironment constituting the AEB system were simulated;the simulation was then linked by applying vehicle dynamicsand control logic. The simulation results show that the colli-sion avoidance relaxation rate of V2V communication-basedAEB system was reduced compared with that of existingvehicle-mounted-sensor-based system. Thus, a method thatcan lower the collision risk of the existing AEB system, whichuses only a sensor cluster installed on the vehicle, is realized.

Y.-S. Jeong et al. proposed an efficient and secure mobile-IPS (m-IPS) for businesses utilizing mobile devices in mobileenvironments for human-centric computing. The m-IPS

system incorporates temporal spatial awareness in human-centric computing with various mobile devices and checksusers’ temporal spatial information, profiles, and role infor-mation to provide precise access control. And it also canextend application of m-IPS to the Internet of Things (IoT),which is one of the important advanced technologies for sup-porting human-centric computing environment completely,for real ubiquitous field with mobile devices.

L. Chen et al. studied the exponential stability of thecomplex dynamical network described by differentially non-linear equations which couple with time delay and stochasticimpulses. Some sufficient conditions are established to ensure𝑝th moment exponential stable for the stochastic impulsivesystems (SIS) with time delay. An example with its numericalsimulation is presented to illustrate the validation of mainresults.

Finally, D. Shin et al. developed watch-type device (smartwatch) that patients wear and a server system. The smartwatch developed includes a GPS, accelerometer, and illumi-nation sensor and can obtain real-time health information bymeasuring the position of patients, quantity of exercise, andamount of sunlight. The server system includes the sensordata analysis algorithmandweb server used by the doctor andprotector to monitor the sensor data acquired from the smartwatch. The proposed data analysis algorithm acquires theexercise information and detects the step count in patients’motion acquired from the acceleration sensor and verifies thethree cases of fast pace, slow pace, and walking pace, showing96% of the experimental results.

Acknowledgments

Our special thanks go to everybody of Journal of AppliedMathematics. We would like to thank all authors for theircontributions to this special issue. We also extend our thanksto the external reviewers for their excellent help in reviewingthe manuscripts.

Young-Sik JeongMohammad S. Obaidat

JianhuaMaLaurence T. Yang

References

[1] Y.-S. Jeong, N. Chilamkurti, and L. J. G. Villalba, “Advancedtechnologies and communication solutions for internet ofthings,” International Journal of Distributed Sensor Networks,vol. 2014, Article ID 896760, 3 pages, 2014.

[2] L. Atzori, A. Iera, and G. Morabito, “The internet of things: asurvey,”Computer Networks, vol. 54, no. 15, pp. 2787–2805, 2010.

[3] Y.-S. Jeong and J. H. Park, “High availability and efficient energyconsumption for cloud computing service with grid infrastruc-ture,” Computers and Electrical Engineering, vol. 39, no. 1, pp.15–23, 2013.

[4] Gartner, Gartner’s Hype Cycle Special Report for 2011, Gart-ner, 2012, http://www.gartner.com/technology/research/hype-cycles/.

Journal of Applied Mathematics 5

[5] H. Ning and Z. Wang, “Future internet of things architecture:likemankind neural system or social organization framework?”IEEE Communications Letters, vol. 15, no. 4, pp. 461–463, 2011.

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Editorial Advanced Mathematics and Numerical Modeling of IoT