Effective Data Transmission Strategy Based on Node Socialization in Opportunistic Social Networks

With the development of big data and high-speed communication networks, traditional end-to-end transmission mechanisms in social networks are difficult to achieve large amounts of data communication between mobile devices. Therefore, the implementation of effective data transmission in social networks requires “opportunity”. Opportunistic social networks suggest choosing the most appropriate next hop nodes for effective data transmission. Most existing routing algorithms attempt to use the interest points of nodes and the social relationships between them to choose optimal relay nodes among neighbors. However, most community-based algorithms take node attributes and social relations into account but fail to consider the energy consumption of inefficient nodes which accounts for a large part of routing cost. To improve the transmission strategy, this paper proposes an effective transmission strategy based on node socialization (ETNS), which divides nodes in the network into several different communities. The proposed scheme also involves a community reduction method that removes some inefficient nodes according to the attributes of optimal relay nodes. The simulation results show that the packet delivery ratio of ETNS is 13% higher than the epidemic algorithm, and ETNS also has lower transmission delay and routing overhead.

[1]  Jie Wu,et al.  Optimal data partitioning and forwarding in opportunistic mobile networks , 2018, 2018 IEEE Wireless Communications and Networking Conference (WCNC).

[2]  C. Montag,et al.  Facebook usage on smartphones and gray matter volume of the nucleus accumbens , 2017, Behavioural Brain Research.

[3]  Jie Wu,et al.  Incentive-Driven and Freshness-Aware Content Dissemination in Selfish Opportunistic Mobile Networks , 2015, IEEE Transactions on Parallel and Distributed Systems.

[4]  Xiang Li,et al.  Structural Vulnerability Assessment of Community-Based Routing in Opportunistic Networks , 2016, IEEE Transactions on Mobile Computing.

[5]  Zhigang Chen,et al.  FCNS: A Fuzzy Routing-Forwarding Algorithm Exploiting Comprehensive Node Similarity in Opportunistic Social Networks , 2018, Symmetry.

[6]  Benoît Otjacques,et al.  Community extraction and visualization in social networks applied to Twitter , 2018, Inf. Sci..

[7]  Victor C. M. Leung,et al.  Deep-Reinforcement-Learning-Based Optimization for Cache-Enabled Opportunistic Interference Alignment Wireless Networks , 2017, IEEE Transactions on Vehicular Technology.

[8]  Ciprian Dobre,et al.  Leader Election in Opportunistic Networks , 2017, 2017 16th International Symposium on Parallel and Distributed Computing (ISPDC).

[9]  Shiguang Wang,et al.  On localizing urban events with Instagram , 2017, IEEE INFOCOM 2017 - IEEE Conference on Computer Communications.

[10]  Chenyang Yang,et al.  High-Throughput Opportunistic Cooperative Device-to-Device Communications With Caching , 2016, IEEE Transactions on Vehicular Technology.

[11]  Arno Schlueter,et al.  A review of unsupervised statistical learning and visual analytics techniques applied to performance analysis of non-residential buildings , 2018 .

[12]  Fei Hao,et al.  Social identity–aware opportunistic routing in mobile social networks , 2018, Trans. Emerg. Telecommun. Technol..

[13]  Jia Wu,et al.  Vehicle trajectory prediction algorithm in vehicular network , 2019, Wirel. Networks.

[14]  Damla Arifoglu,et al.  Deep Online Hierarchical Unsupervised Learning for Pattern Mining from Utility Usage Data , 2018, UKCI.

[15]  Joel J. P. C. Rodrigues,et al.  A Machine Learning-Based Protocol for Efficient Routing in Opportunistic Networks , 2018, IEEE Systems Journal.

[16]  M. Chitra,et al.  Selective epidemic broadcast algorithm to suppress broadcast storm in vehicular ad hoc networks , 2017 .

[17]  Giancarlo Fortino,et al.  A utility-oriented routing algorithm for community based opportunistic networks , 2013, Proceedings of the 2013 IEEE 17th International Conference on Computer Supported Cooperative Work in Design (CSCWD).

[18]  Juan-Carlos Cano,et al.  Evaluating and Enhancing Information Dissemination in Urban Areas of Interest Using Opportunistic Networks , 2018, IEEE Access.

[19]  Kuan-Yu Chen,et al.  An Online Activity Recommendation Approach Based on the Dynamic Adjustment of Recommendation Lists , 2017, 2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI).

[20]  Ezequiel López-Rubio,et al.  Unsupervised learning by cluster quality optimization , 2018, Inf. Sci..

[21]  Mohammad S. Obaidat,et al.  Energy-Efficient Prophet-PRoWait-EDR Protocols for Opportunistic Networks , 2017, GLOBECOM 2017 - 2017 IEEE Global Communications Conference.

[22]  Yibo Yang,et al.  Social-aware data dissemination in opportunistic mobile social networks , 2017 .

[23]  Sau-Hsuan Wu,et al.  Cross-Layer Performance Analysis of Cooperative ARQ With Opportunistic Multi-Point Relaying in Mobile Networks , 2018, IEEE Transactions on Wireless Communications.

[24]  Zhigang Chen,et al.  Effective information transmission based on socialization nodes in opportunistic networks , 2017, Comput. Networks.

[25]  Jie Wu,et al.  Rethink data dissemination in opportunistic mobile networks with mutually exclusive requirement , 2018, J. Parallel Distributed Comput..

[26]  Yue Cao,et al.  A Social-Based DTN Routing in Cooperative Vehicular Sensor Networks , 2018, Int. J. Cooperative Inf. Syst..

[27]  Joel J. P. C. Rodrigues,et al.  Enhanced fuzzy logic‐based spray and wait routing protocol for delay tolerant networks , 2016, Int. J. Commun. Syst..

[28]  Zhigang Chen,et al.  An Effective Data Transmission Algorithm Based on Social Relationships in Opportunistic Mobile Social Networks , 2018, Algorithms.

[29]  Xiao Chen,et al.  Efficient Multicast Algorithms in Opportunistic Mobile Social Networks using Community and Social Features , 2016, Comput. Networks.

[30]  Kelvin George Chng,et al.  Unsupervised machine learning account of magnetic transitions in the Hubbard model. , 2017, Physical review. E.

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

[32]  Weimin Li,et al.  Effective community division based on improved spectral clustering , 2017, Neurocomputing.

[33]  Jie Wu,et al.  Cooperative Internet Access Using Helper Nodes and Opportunistic Scheduling , 2017, IEEE Transactions on Vehicular Technology.

[34]  Lin Zhang,et al.  VIRO: A virtual routing method for eliminating dead end in Opportunistic Mobile Social Network , 2015, 2015 IEEE International Conference on Communications (ICC).

[35]  Pankaj Sharma,et al.  A new modified spray and wait routing algorithm for heterogeneous delay tolerant network , 2017, 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC).

[36]  Yang Gao,et al.  Contacts-aware opportunistic forwarding in mobile social networks: A community perspective , 2018, 2018 IEEE Wireless Communications and Networking Conference (WCNC).

[37]  Zhigang Chen,et al.  Information cache management and data transmission algorithm in opportunistic social networks , 2018, Wireless Networks.

[38]  Hang Chang,et al.  Unsupervised Transfer Learning via Multi-Scale Convolutional Sparse Coding for Biomedical Applications , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[39]  Vicente Hernández Díaz,et al.  Cross-Layer and Reliable Opportunistic Routing Algorithm for Mobile Ad Hoc Networks , 2018, IEEE Sensors Journal.

[40]  Zhigang Chen,et al.  Workload scheduling toward worst-case delay and optimal utility for single-hop Fog-IoT architecture , 2018, IET Commun..

[41]  Huan Wang,et al.  RNOB: Receiver Negotiation Opportunity Broadcast Protocol for Trustworthy Data Dissemination in Wireless Sensor Networks , 2018, IEEE Access.

[42]  Haibo Zhang,et al.  Adaptive Message Routing and Replication in Mobile Opportunistic Networks for Connected Communities , 2017, ACM Trans. Internet Techn..

[43]  Siu-Ming Yiu,et al.  A Dynamic Trust Framework for Opportunistic Mobile Social Networks , 2018, IEEE Transactions on Network and Service Management.

[44]  Benjamin Munson,et al.  Supervised and unsupervised machine learning approaches to classifying chimpanzee vocalizations , 2018 .

[45]  David Tse,et al.  Mobility increases the capacity of ad-hoc wireless networks , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[46]  Isaac Woungang,et al.  A location Prediction-based routing scheme for opportunistic networks in an IoT scenario , 2018, J. Parallel Distributed Comput..

[47]  Anthony Harkin,et al.  Walk-modularity and community structure in networks , 2014, Network Science.

[48]  Mohamed-Slim Alouini,et al.  Optimal Caching in 5G Networks With Opportunistic Spectrum Access , 2018, IEEE Transactions on Wireless Communications.

[49]  Chittaranjan Hota,et al.  STEEP: speed and time-based energy efficient neighbor discovery in opportunistic networks , 2019, Wirel. Networks.

[50]  Zheng Yan,et al.  Predict Pairwise Trust Based on Machine Learning in Online Social Networks: A Survey , 2018, IEEE Access.

[51]  Jia Wu,et al.  Weight distribution and community reconstitution based on communities communications in social opportunistic networks , 2019, Peer Peer Netw. Appl..

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