Mobile P2P Subgroup Routing for In-Vehicle Media and Goods Delivery
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Solution Overview
Problem
Existing peer-to-peer (P2P) networks fail to leverage advanced technologies for delivering media content and physical goods to mobile users in vehicles, particularly those in transit, missing opportunities for enhanced entertainment and social experiences.
Innovation Solution
A computer-implemented method for P2P networks that dynamically forms local subgroups of mobile devices based on user affinities and proximity, optimizing media content delivery and physical article transfer between vehicles using high-bandwidth connections and predictive algorithms, with support from blockchain technology for authentication and self-sovereign identity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If P2P networks use traditional delivery methods, then infrastructure requirements are reduced, but delivery speed and bandwidth to mobile users are insufficient
Solution Approach 1:
The network is segmented into local subgroups of mobile devices based on geographic proximity and user affinities. Each subgroup operates semi-independently, forming a distributed mesh network that can deliver content faster locally while reducing overall network complexity through modular organization.
Solution Approach 2:
The patent introduces a new dimension of delivery by utilizing mobile devices in vehicles as intermediate nodes. This creates a three-dimensional delivery architecture: traditional infrastructure nodes, intermediate mobile nodes, and end-user devices, enabling faster content propagation through multiple simultaneous transmission paths.
2Productivity
If P2P networks dynamically form local subgroups based on user affinities, then content delivery optimization is improved, but computational requirements and processing time increase
Solution Approach 1:
User affinities and preferences are pre-calculated and stored before delivery operations. When a local subgroup forms, the system retrieves pre-computed affinity data rather than calculating it in real-time, significantly reducing computational energy requirements while maintaining optimized content delivery efficiency.
Solution Approach 2:
The patent replaces complex real-time computational matching with pre-computed affinity scores stored in distributed ledgers. This substitution of mechanical calculation with stored lookup operations reduces energy consumption while preserving delivery optimization.
3Reliability
If the system uses blockchain technology for authentication and self-sovereign identity, then security is improved, but device complexity and processing overhead increase
Solution Approach 1:
Mobile devices maintain their own self-sovereign identities and authentication credentials locally. Each device independently manages its own security credentials without requiring constant centralized verification, reducing system-wide complexity while maintaining high security through distributed trust management.
Solution Approach 2:
The system changes the parameter of identity management from centralized database storage to distributed local storage on mobile devices. This parameter change reduces central system complexity while enhancing security through decentralized credential management.
4Power
If high-bandwidth connections are established between moving vehicles, then media content delivery quality is improved, but connection stability and reliability decrease
Solution Approach 1:
The network dynamically adjusts connection parameters and routes based on real-time vehicle positions, speeds, and signal conditions. As vehicles move, the system continuously reconfigures the mesh network topology to maintain optimal high-bandwidth connections, adapting to changing conditions rather than relying on static connections.
Solution Approach 2:
The system pre-establishes multiple potential transmission paths between vehicles before content delivery begins. When a high-bandwidth connection is available, content is delivered through that path, and alternative paths are already prepared as backups, ensuring reliability without sacrificing bandwidth optimization.
Data Source
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AI summary
A computer-implemented method for peer-to-peer (P2P) networks for the delivery of media content held in the peer-to-peer network to a vehicle in a local subgroup of the P2P network, and for providing an automated process for P2P networks for transferring of physical articles or electronic data package between vehicles traveling different routes.