Content Closure Offloading in Content Centric Networks
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Solution Overview
Problem
Content producers in content-centric networks face inefficiencies due to the need to recompute expensive functions for multiple consumer requests, leading to congestion and network inefficiency when data from multiple sources is involved.
Innovation Solution
A system that generates a content closure message containing the function and necessary data, allowing consumers to perform computations independently, thereby offloading the computation from the producer to the consumer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the content producer computes expensive functions for each consumer request, then the consumer receives accurate computation results, but the producer becomes overwhelmed and network congestion occurs
Solution Approach 1:
The patent extracts the computation function and necessary data from the producer and delivers them to the consumer as a content closure. The consumer then independently executes the function, removing the computational burden from the producer while maintaining accurate results.
Solution Approach 2:
The consumer is empowered to perform the computation themselves using the provided function and data. This self-service approach eliminates the need for the producer to repeatedly compute the same expensive function for multiple consumers.
2Reliability
If the content producer handles all computation centrally, then computation results are accurate, but network efficiency decreases due to repeated computations
Solution Approach 1:
The producer creates a copy of the function and data (as a content closure) and delivers it to the consumer. This copying approach allows the consumer to execute the function locally without requiring repeated centralized computations, reducing network energy consumption while maintaining result reliability.
3Adaptability or versatility
If the producer recomputes functions for each request from multiple consumers, then each consumer gets personalized results, but the producer becomes a bottleneck causing congestion
Solution Approach 1:
The patent segments the computation task by separating the function definition from the execution. The producer only needs to manage function definitions, while each consumer independently executes the function with their own data, eliminating the bottleneck of centralized recomputation while maintaining personalized results.
Data Source
AI summary
One embodiment provides a system that facilitates content closures in a CCN. During operation, the system generates, by a client computing device, an initial interest with a name that is a hierarchically structured variable length identifier which comprises contiguous name components ordered from a most general level to a most specific level, wherein the initial interest indicates a request for a result of a computation. The system receives from a content producing device a content object which indicates a function that outputs the requested result and data to be used as input to the function. The system performs the function based on the indicated data, which outputs the requested result, thereby facilitating a content producing device to offload computation of the function to the client computing device.