research-article

Effective Data Transmission and Control Based on Social Communication in Social Opportunistic Complex Networks

Authors:

Jingwen LuoAuthors Info & Claims

Complexity, Volume 2020

https://doi.org/10.1155/2020/3721579

Published: 01 January 2020 Publication History

Abstract

In opportunistic complex networks, information transmission between nodes is inevitable through broadcast. The purpose of broadcasting is to distribute data from source nodes to all nodes in the network. In opportunistic complex networks, it is mainly used for routing discovery and releasing important notifications. However, when a large number of nodes in the opportunistic complex networks are transmitting information at the same time, signal interference will inevitably occur. Therefore, we propose a low-latency broadcast algorithm for opportunistic complex networks based on successive interference cancellation techniques to improve propagation delay. With this kind of algorithm, when the social network is broadcasting, this algorithm analyzes whether the conditions for successive interference cancellation are satisfied between the broadcast links on the assigned transmission time slice. If the conditions are met, they are scheduled at the same time slice, and interference avoidance scheduling is performed when conditions are not met. Through comparison experiments with other classic algorithms of opportunistic complex networks, this method has outstanding performance in reducing energy consumption and improving information transmission efficiency.

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Index Terms

Effective Data Transmission and Control Based on Social Communication in Social Opportunistic Complex Networks
1. Networks
  1. Network protocols
  2. Network types
    1. Mobile networks
    2. Wireless access networks

Index terms have been assigned to the content through auto-classification.

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cover image Complexity

Complexity Volume 2020, Issue

2020

17147 pages

ISSN:1076-2787

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Copyright © 2020 Weiyu Yang 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.

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John Wiley & Sons, Inc.

United States

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Published: 01 January 2020

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Cited By

Ouyang TYang SGou FDai ZWu J(2022)Rethinking U-Net from an Attention Perspective with Transformers for Osteosarcoma MRI Image SegmentationComputational Intelligence and Neuroscience10.1155/2022/79734042022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/7973404
Li LGou FWu J(2022)Modified Data Delivery Strategy Based on Stochastic Block Model and Community Detection in Opportunistic Social NetworksWireless Communications & Mobile Computing10.1155/2022/50678492022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/5067849
Zhuang QDai ZWu J(2022)Deep Active Learning Framework for Lymph Node Metastasis Prediction in Medical Support SystemComputational Intelligence and Neuroscience10.1155/2022/46016962022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/4601696
Zhang XChang LLuo JWu J(2021)Effective communication data transmission based on community clustering in opportunistic social networks in IoT systemJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-21080741:1(2129-2144)Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.3233/JIFS-210807
Wu JGou FXiong WZhou X(2021)A Reputation Value-Based Task-Sharing Strategy in Opportunistic Complex Social NetworksComplexity10.1155/2021/85543512021Online publication date: 26-Nov-2021
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Lou PChen YGao S(2020)Adaptive Variable Neighborhood Search-Based Supply Network Reconfiguration for Robustness EnhancementComplexity10.1155/2020/12929382020Online publication date: 8-Dec-2020
https://dl.acm.org/doi/10.1155/2020/1292938

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