IoV Content Delivery Clustering and CDN-P2P Architecture
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Solution Overview
Problem
The inefficiency of network content delivery in the Internet of Vehicles due to rapid mobility of vehicles and instability of wireless networks, leading to incomplete content reception by onboard units.
Innovation Solution
A content delivery method that clusters onboard units based on interest content information, with cluster-heads managing content access requests and updates, utilizing a CDN-P2P architecture to enhance content delivery efficiency and reduce network load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If content delivery is performed using a traditional CDN server at the roadside unit, then network content can be delivered to vehicles, but the delivery efficiency is low due to rapid vehicle mobility and wireless network instability
Solution Approach 1:
The patent segments the CDN system into multiple levels: edge servers at roadside units, cluster head vehicles, and ordinary vehicles. This segmentation allows content to be cached and delivered from multiple distributed locations, improving both delivery efficiency and reliability by reducing dependence on a single roadside unit.
Solution Approach 2:
The system performs preliminary action by pre-caching content on multiple nodes including edge servers, cluster head vehicles, and ordinary vehicles before actual content requests occur. This ensures that content is already available in the network when vehicles need it, overcoming the limitations of rapid mobility and unstable wireless connections.
2Device complexity
If content is cached only at roadside unit CDN servers, then content delivery is simplified, but the system cannot handle rapid vehicle mobility and network instability effectively
Solution Approach 1:
The caching structure is segmented across multiple levels: edge servers at roadside units, cluster head vehicles, and ordinary vehicles. This multi-level segmentation distributes the caching burden and improves content delivery efficiency by allowing vehicles to retrieve content from the nearest available cache, reducing latency despite increased structural complexity.
Solution Approach 2:
The system implements local quality by allowing different nodes to cache different content based on their location and the interests of nearby vehicles. Cluster head vehicles and ordinary vehicles cache content relevant to their local vehicle groups, improving delivery efficiency for local requests while the overall system maintains a distributed caching structure.
3Productivity
If the system uses a multi-level caching structure with edge servers, cluster heads, and ordinary vehicles, then content delivery efficiency improves, but the system complexity increases
Solution Approach 1:
The system merges the functions of content caching and content delivery into a unified multi-level architecture where edge servers, cluster head vehicles, and ordinary vehicles all participate in both caching and delivery. This integration improves efficiency by allowing any node to serve content while reducing the need for separate specialized components, thereby managing system complexity.
Solution Approach 2:
Vehicles in the system serve multiple functions: they act as mobile users, potential cluster heads, and content caches simultaneously. This multi-functionality reduces system complexity by eliminating the need for dedicated cache devices, as ordinary vehicles can function as caches when needed, thereby improving content delivery efficiency without proportionally increasing system complexity.
4Reliability
If content updates are performed frequently on all onboard units, then content freshness is maintained, but the network load increases
Solution Approach 1:
The system performs preliminary action by pre-updating content on edge servers and cluster head vehicles before ordinary vehicles need the updated content. When content needs updating, it is first pushed to edge servers and cluster heads, which then make it available to ordinary vehicles on demand, reducing the immediate network load while maintaining content freshness.
Solution Approach 2:
Content updates are performed with local quality by updating content at edge servers and cluster head vehicles based on the specific interests and needs of their local vehicle groups. Not all nodes receive all updates, and updates are propagated selectively based on local demand, thereby maintaining content freshness for relevant content while reducing overall network load compared to universal frequent updates.
Data Source
AI summary
A content delivery method and a content update method for a vehicle network associated with an Internet of Vehicles are disclosed. The content delivery method for an Internet of Vehicles includes dividing the plurality of onboard units into clusters based on interest content information of the plurality of onboard units. Each of the clusters includes at least one cluster-head onboard unit. The method includes receiving, by the cluster-head onboard unit, an interest content access request of an requestor onboard unit in the cluster, searching for the interest content corresponding to the interest content access request in the Internet of Vehicles and sending the searched interest content to the requestor onboard unit.