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A Service Pricing-based Two-Stage Incentive Algorithm for Socially Aware Networks

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Abstract

In socially aware networks, data forwarding is usually performed based on opportunistic peer-to-peer connections and using a store-and-forward method. This method requires active collaboration from all nodes. However, due to resource limitations and other factors, several nodes exhibit selfishness and are unwilling to consume their resources to assist other nodes in forwarding data. To tackle the problems of insufficient participating nodes and low willingness to participate, this paper proposes a Service pricing-based Two-stage Incentive Algorithm (STIA). First, in view of the lack of rewards for high reputation nodes in reputation incentive and the indistinguishability of prices for different service levels in credit mechanism, leading to poor incentive effects, this paper uses the service quality of nodes and their own resources to design message pricing functions as rewards for service providers and prevents nodes from making fraudulent offers by disclosing the resource status of both parties. Secondly, this paper considers the case where relay nodes will discard accepted data, thus proposing a two-stage incentive mechanism that motivates nodes to receive and forward data. Finally, in response to nodes discarding received messages due to short-term currency shortages, nodes are permitted to overdraw their currency according to their forwarding capacity under the condition of setting restrictions to increase network cooperation. Experimental simulation results show that STIA offers significant improvements in delivery ratio and latency of messages over existing incentive schemes.

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Data Availability

Data available on request from the authors.

Code Availability

Code available on request from the authors.

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Acknowledgements

This work was partially supported by the National Natural Science Foundation of China (No.61972136), and Hubei Natural Science Foundation (No.2020CFB497, No.2020CFB571), MOE(Ministry of Education in China) Project of Humanities and Social Sciences (No.20YJAZH112), the Hubei Provincial Department of Education Outstanding Youth Scientific Innovation Team Support Foundation (No.T201410, T2020017), the Science and Technology Research Projects of Hubei Provincial Department of Education (No.Q20162706).

Funding

This article was partially supported by the National Natural Science Foundation of China (No.61972136) and Hubei Natural Science Foundation (No.2020CFB497, No.2020CFB571), MOE(Ministry of Education in China) Project of Humanities and Social Sciences (No.20YJAZH112), the Hubei Provincial Department of Education Outstanding Youth Scientific Innovation Team Support Foundation (No.T201410, T2020017), the Science and Technology Research Projects of Hubei Provincial Department of Education (No.Q20162706).

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Authors and Affiliations

  1. School of Computer and Information Science, Hubei Engineering University, Xiaogan, 432000, China

    Xiong Zenggang, Li Xiang, Zhang Xueming, Zhu Sanyuan, Xu Fang, Zhao Xiaochao, Wu Yunyun & Zeng Mingyang

  2. School of Computer Science and Information Engineering, Hubei University, Wuhan, Hubei, 430062, China

    Xiong Zenggang, Li Xiang, Zhang Xueming, Zhu Sanyuan, Xu Fang, Zhao Xiaochao, Wu Yunyun & Zeng Mingyang

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  1. Xiong Zenggang
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  2. Li Xiang
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  4. Zhu Sanyuan
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  5. Xu Fang
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Contributions

Zenggang Xiong: Supervision, Conceptualization, Methodology, Writing - Review & Editing. Xiang Li: Software, Validation, Formal analysis, Writing - Original Draft, Visualization. Xuemin Zhang: Project administration, Conceptualization. Sanyuan Zhu: Methodology, Formal analysis. Fang Xu: Visualization, Writing - Review & Editing. Xiaochao Zhao: algorithm implementation, Writing - Review & Editing. Yunyun Wu: Simulation ,Writing - Review & Editing. Minyang Zeng: Simulation, algorithm implementation.

Corresponding author

Correspondence to Zhu Sanyuan.

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For this type of study formal consent was not required. This manuscript does not contain any studies with human participants or animals performed by any of the authors.

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The authors declare that they have no competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Zenggang, X., Xiang, L., Xueming, Z. et al. A Service Pricing-based Two-Stage Incentive Algorithm for Socially Aware Networks. J Sign Process Syst 94, 1227–1242 (2022). https://doi.org/10.1007/s11265-022-01768-1

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