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Reputation-Driven Peer-to-Peer Live Streaming Architecture for Preventing Free-Riding

Rashmi Kushwaha, Rahul Bhattacharyya, Yatindra Nath Singh

TL;DR

The architecture incentivizes active participation and discourages opportunistic behaviors, fostering a more collaborative and sustainable streaming environment, and enhances the overall performance and reliability of the P2P live streaming system but also promotes its long-term sustainability by aligning individual peer incentives with the collective goals of the network.

Abstract

We present a peer-to-peer (P2P) live-streaming architecture designed to address challenges such as free-riding, malicious peers, churn, and network instability through the integration of a reputation system. The proposed algorithm incentivizes active peer participation while discouraging opportunistic behaviors, with a reputation mechanism that rewards altruistic peers and penalizes free riders and malicious actors. To manage peer dynamics, the algorithm continuously updates the strategies and adjusts to changing neighbors. It also implements a request-to-join mechanism for flash crowd scenarios, allowing the source node to delegate requests to child nodes, forming an interconnected tree structure that efficiently handles high demand and maintains system stability. The decentralized reputation mechanism promotes long-term sustainability in the P2P live streaming system.

Reputation-Driven Peer-to-Peer Live Streaming Architecture for Preventing Free-Riding

TL;DR

The architecture incentivizes active participation and discourages opportunistic behaviors, fostering a more collaborative and sustainable streaming environment, and enhances the overall performance and reliability of the P2P live streaming system but also promotes its long-term sustainability by aligning individual peer incentives with the collective goals of the network.

Abstract

We present a peer-to-peer (P2P) live-streaming architecture designed to address challenges such as free-riding, malicious peers, churn, and network instability through the integration of a reputation system. The proposed algorithm incentivizes active peer participation while discouraging opportunistic behaviors, with a reputation mechanism that rewards altruistic peers and penalizes free riders and malicious actors. To manage peer dynamics, the algorithm continuously updates the strategies and adjusts to changing neighbors. It also implements a request-to-join mechanism for flash crowd scenarios, allowing the source node to delegate requests to child nodes, forming an interconnected tree structure that efficiently handles high demand and maintains system stability. The decentralized reputation mechanism promotes long-term sustainability in the P2P live streaming system.
Paper Structure (11 sections, 3 equations, 5 figures, 2 algorithms)

This paper contains 11 sections, 3 equations, 5 figures, 2 algorithms.

Table of Contents

  1. Introduction
  2. Related work
  3. System Architecture
  4. Five key stages of architecture
  5. Joining and authentication
  6. Initialization and topology formation
  7. Construction of routing tables
  8. Streaming of media
  9. Reputation calculation and aggregation
  10. Stability of the system
  11. Conclusion

Figures (5)

  • Figure 1: Mapping of streamID with source ID and DHT layerIDs
  • Figure 2: Significance of '$\alpha$'
  • Figure 4: Topology
  • Figure 5: Payoff Matrix
  • Figure 6: Nash equilibrium