A review of data sets of short-range wireless networks

Abstract With the rapid development of intelligent devices, it is possible to communicate among devices without base-stations. There is a growing body of research on short-range wireless networks. However, to our knowledge, currently there is little guidance on how to choose the appropriate real data sets to study a specific area of short-range wireless networks, or to verify the proposed algorithms for a specific application. Therefore, this study reviews several real data sets collected by short-range wireless communication devices, analyzes characteristics of each data set, and classifies articles using each data set into several categories. By tracking the latest progress in short-range wireless networks and investigating how to use the real data, this study not only provides guidance for researchers who need to select data sets for analysis or application, but also provides a reference for those who want to perform experiments to collect new traces.

[1]  Qi Han,et al.  Context-Aware Community Construction in Proximity-Based Mobile Networks , 2015, Mob. Inf. Syst..

[2]  Suvadip Batabyal,et al.  Mobility Models, Traces and Impact of Mobility on Opportunistic Routing Algorithms: A Survey , 2015, IEEE Communications Surveys & Tutorials.

[3]  Khaled A. Harras,et al.  Adaptive forwarding of mHealth data in challenged networks , 2017, 2017 IEEE 19th International Conference on e-Health Networking, Applications and Services (Healthcom).

[4]  Ciprian Dobre,et al.  Social Aspects for Opportunistic Communication , 2012, 2012 11th International Symposium on Parallel and Distributed Computing.

[5]  Yonggang Wen,et al.  Toward Scalable Systems for Big Data Analytics: A Technology Tutorial , 2014, IEEE Access.

[6]  Hyun-Woo Lee,et al.  A computational model to evaluate honesty in social internet of things , 2017, SAC.

[7]  Pan Hui,et al.  FlopCoin: A Cryptocurrency for Computation Offloading , 2018, IEEE Transactions on Mobile Computing.

[8]  Peng Li,et al.  User social activity-based routing for cognitive radio networks , 2018, Personal and Ubiquitous Computing.

[9]  Yuebin Bai,et al.  SAME: A students' daily activity mobility model for campus delay-tolerant networks , 2012, 2012 18th Asia-Pacific Conference on Communications (APCC).

[10]  Djamal Zeghlache,et al.  Trust management system design for the Internet of Things: A context-aware and multi-service approach , 2013, Comput. Secur..

[11]  Mei Song,et al.  A Locality-Based Mobile Caching Policy for D2D-Based Content Sharing Network , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).

[12]  Jie Wu,et al.  Geocommunity-Based Broadcasting for Data Dissemination in Mobile Social Networks , 2012 .

[13]  Wenye Wang,et al.  Modeling and estimating the structure of D2D-based mobile social networks , 2016, 2016 IEEE International Conference on Communications (ICC).

[14]  Ciprian Dobre,et al.  Predicting Encounters in Opportunistic Networks Using Gaussian Process , 2013, 2013 19th International Conference on Control Systems and Computer Science.

[15]  Jun Huang,et al.  DTN-Knca: A High Throughput Routing Based on Contact Pattern Detection in DTNs , 2018, 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC).

[16]  Xin Wang,et al.  Secure Routing Based on Social Similarity in Opportunistic Networks , 2016, IEEE Transactions on Wireless Communications.

[17]  Rajesh Krishnan,et al.  An Overview of Opportunistic Routing in Mobile Ad Hoc Networks , 2013, MILCOM 2013 - 2013 IEEE Military Communications Conference.

[18]  Ajay Vikram Singh,et al.  Trust based Intelligent Routing Algorithm for Delay Tolerant Network using Artificial Neural Network , 2016, Wireless Networks.

[19]  Pietro Manzoni,et al.  Adaptive Real-Time Predictive Collaborative Content Discovery and Retrieval in Mobile Disconnection Prone Networks , 2018, IEEE Access.

[20]  Jörg Ott,et al.  Working day movement model , 2008, MobilityModels '08.

[21]  Qiang Zhu,et al.  Analyzing and modeling heterogeneous behavior , 2016 .

[22]  Kun Yang,et al.  An enhanced community-based mobility model for distributed mobile social networks , 2012, Journal of Ambient Intelligence and Humanized Computing.

[23]  Emmanuel Lochin,et al.  Following the right path: Using traces for the study of DTNs , 2016, Comput. Commun..

[24]  Ahmed Helmy,et al.  Structural Analysis of User Association Patterns in University Campus Wireless LANs , 2012, IEEE Transactions on Mobile Computing.

[25]  Serge Fdida,et al.  SIMPS: Using Sociology for Personal Mobility , 2006, IEEE/ACM Transactions on Networking.

[26]  Jianwu Wang,et al.  A Scalable Data Science Workflow Approach for Big Data Bayesian Network Learning , 2014, 2014 IEEE/ACM International Symposium on Big Data Computing.

[27]  Hongyi Wu,et al.  Bargain-based Stimulation Mechanism for Selfish Mobile Nodes in Participatory Sensing Network , 2009, 2009 6th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[28]  Julinda Stefa,et al.  SWIM: A Simple Model to Generate Small Mobile Worlds , 2008, IEEE INFOCOM 2009.

[29]  Cecilia Mascolo,et al.  Designing mobility models based on social network theory , 2007, MOCO.

[30]  Ignas G. Niemegeers,et al.  Predicting mobility events on personal devices , 2010, Pervasive Mob. Comput..

[31]  Jia Guo,et al.  Trust Management for SOA-Based IoT and Its Application to Service Composition , 2016, IEEE Transactions on Services Computing.

[32]  Ciprian Dobre,et al.  SENSE: A collaborative selfish node detection and incentive mechanism for opportunistic networks , 2014, J. Netw. Comput. Appl..

[33]  Nitin Pandey,et al.  Opportunistic message forwarding in self organized cluster based DTN , 2017, INFOCOM 2017.

[34]  Karim Djemame,et al.  Analysis of human mobility patterns for opportunistic forwarding in shopping mall environments , 2015, Social Network Analysis and Mining.

[35]  Feng Zeng,et al.  Effective Social Relationship Measurement and Cluster Based Routing in Mobile Opportunistic Networks † , 2017, Sensors.

[36]  Khaled A. Harras,et al.  On the shortcoming of DTN solutions in rural mHealth applications , 2017, 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC).

[37]  Guiran Chang,et al.  TRM-IoT: A trust management model based on fuzzy reputation for internet of things , 2011, Comput. Sci. Inf. Syst..

[38]  Jalel Ben-Othman,et al.  CGAM: A community and geography aware mobility model , 2018, Int. J. Commun. Syst..

[39]  Duncan J. Watts,et al.  Characterizing individual communication patterns , 2009, KDD.

[40]  Le Chang,et al.  Reducing the Overhead of Multicast Using Social Features in Mobile Opportunistic Networks , 2019, IEEE Access.

[41]  Qi Shi,et al.  Machine Learning Based Trust Computational Model for IoT Services , 2019, IEEE Transactions on Sustainable Computing.

[42]  Amjad Rehman,et al.  Data offloading in IoT environments: modeling, analysis, and verification , 2019, EURASIP J. Wirel. Commun. Netw..

[43]  Matteo Zignani Geo-CoMM: A geo-community based mobility model , 2012, 2012 9th Annual Conference on Wireless On-Demand Network Systems and Services (WONS).

[44]  Takahiro Hara,et al.  Multi-model Z-compression for high speed data streaming and low-power wireless sensor networks , 2019, Distributed and Parallel Databases.

[45]  Qingzhong Liang,et al.  Encounter Probability Aware Task Assignment in Mobile Crowdsensing , 2017, Mob. Networks Appl..

[46]  Thrasyvoulos Spyropoulos,et al.  Modelling and Analysis of Communication Traffic Heterogeneity in Opportunistic Networks , 2015, IEEE Transactions on Mobile Computing.

[47]  Andrea G. Ribeiro Modeling the impact of human spontaneity in mobile trajectories , 2013, 2013 IEEE 9th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob).

[48]  Shashikala Tapaswi,et al.  Mobility prediction in mobile ad hoc networks using a lightweight genetic algorithm , 2016, Wirel. Networks.

[49]  M. L. Valarmathi,et al.  Trust Management in the Social Internet of Things , 2017, Wireless Personal Communications.

[50]  Amin Vahdat,et al.  Epidemic Routing for Partially-Connected Ad Hoc Networks , 2009 .

[51]  Milena Radenkovic,et al.  Practical MANETs for Pervasive Cattle Monitoring , 2008, Seventh International Conference on Networking (icn 2008).

[52]  Yan Shi,et al.  Exploiting Social Relationship for Opportunistic Routing in Mobile Social Networks , 2015, IEICE Trans. Commun..

[53]  Annalisa Socievole,et al.  Opportunistic mobile social networks: From mobility and Facebook friendships to structural analysis of user social behavior , 2016, Comput. Commun..

[54]  Tracy Camp,et al.  SMOOTH: a simple way to model human mobility , 2011, MSWiM '11.

[55]  Xu Chen,et al.  Socially Motivated Data Caching in Ultra-Dense Small Cell Networks , 2017, IEEE Network.

[56]  Weihua Zhuang,et al.  Software Defined Networking Enabled Wireless Network Virtualization: Challenges and Solutions , 2017, IEEE Network.

[57]  Anders Lindgren,et al.  Probabilistic Routing in Intermittently Connected Networks , 2004, SAPIR.

[58]  Yujin Lim,et al.  A Markov-Based Prediction Algorithm for User Mobility at Heterogeneous Cloud Radio Access Network , 2019, 2019 IEEE International Conference on Big Data and Smart Computing (BigComp).

[59]  Klara Nahrstedt,et al.  Jyotish: A novel framework for constructing predictive model of people movement from joint Wifi/Bluetooth trace , 2011, 2011 IEEE International Conference on Pervasive Computing and Communications (PerCom).

[60]  Xiulong Wu,et al.  Analyzing and modeling mobility for infrastructure-less communication , 2015, J. Netw. Comput. Appl..

[61]  Yuchen Zhao,et al.  A robust reputation-based location-privacy recommender system using opportunistic networks , 2016, MobiCASE.

[62]  Sanjay Kumar Madria,et al.  Secure Information Forwarding through Fragmentation in Delay-Tolerant Networks , 2018, 2018 IEEE 37th Symposium on Reliable Distributed Systems (SRDS).

[63]  Jörg Ott,et al.  The ONE simulator for DTN protocol evaluation , 2009, SIMUTools 2009.

[64]  Gürkan Solmaz,et al.  Modeling pedestrian mobility in disaster areas , 2017, Pervasive Mob. Comput..

[65]  Xiaoshuang Xing,et al.  Relay selection based on social relationship prediction and information leakage reduction for mobile social networks , 2018, Math. Found. Comput..

[66]  Aline Carneiro Viana,et al.  A Message Removal Mechanism for Delay Tolerant Networks , 2016, UNet.

[67]  Annalisa Socievole,et al.  Routing in Mobile Opportunistic Social Networks with Selfish Nodes , 2019, Wirel. Commun. Mob. Comput..

[68]  Lei Xu,et al.  A link prediction approach based on deep learning for opportunistic sensor network , 2017, Int. J. Distributed Sens. Networks.

[69]  Shahram Babaie,et al.  Selfish node detection in ad hoc networks based on fuzzy logic , 2019, Neural Computing and Applications.

[70]  Michel Diaz,et al.  STEPS - An Approach for Human Mobility Modeling , 2011, Networking.

[71]  Subrat Kar,et al.  Utilizing Social Networks Data for Trust Management in a Social Internet of Things Network , 2018, MobiCom.

[72]  Paolo Santi,et al.  The Node Distribution of the Random Waypoint Mobility Model for Wireless Ad Hoc Networks , 2003, IEEE Trans. Mob. Comput..

[73]  Liang Dong,et al.  Clarifying Trust in Social Internet of Things , 2017, IEEE Trans. Knowl. Data Eng..

[74]  Haitao Yu,et al.  A Secure Credit-Based Incentive Scheme for Opportunistic Networks , 2015, 2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics.

[75]  Honggang Wang,et al.  Socially aware D2D cooperative communications for enhancing Internet of Things application , 2018, EURASIP J. Wirel. Commun. Netw..

[76]  Damla Turgut,et al.  Opportunistic Message Broadcasting in Campus Environments , 2014, GLOBECOM 2014.

[77]  Farrukh Salim Shaikh,et al.  Routing in Multi-Hop Cellular Device-to-Device (D2D) Networks: A Survey , 2018, IEEE Communications Surveys & Tutorials.

[78]  Sajal K. Das,et al.  Multi-periodic contact patterns in predicting future contacts over mobile networks , 2017, 2017 IEEE 18th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM).

[79]  Lin Wang,et al.  Characterizing pairwise contact patterns in human contact networks , 2012, Ad Hoc Networks.

[80]  Ioannis Anagnostopoulos,et al.  A Covering Classification Rule Induction Approach for Big Datasets , 2014, 2014 IEEE/ACM International Symposium on Big Data Computing.

[81]  Stephan Winter,et al.  Random encounters in probabilistic time geography , 2018, Int. J. Geogr. Inf. Sci..

[82]  Greg Bigwood,et al.  IRONMAN: Using Social Networks to Add Incentives and Reputation to Opportunistic Networks , 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.

[83]  Feng Xia,et al.  Human mobility in opportunistic networks: Characteristics, models and prediction methods , 2014, J. Netw. Comput. Appl..

[84]  Ciprian Dobre,et al.  Exploring Predictability in Mobile Interaction , 2012, 2012 Third International Conference on Emerging Intelligent Data and Web Technologies.