Selective Content Retrieval in Information-Centric Networking
Abstract
:1. Introduction
2. Background and Related Work
2.1. Named Data Networking
2.2. Caching Transient Content in NDN
2.3. NDN and IoT Services at the Edge
2.4. In-Network Processing via NDN
2.5. Handling IoT Data
2.6. Critical Summary
3. Efficient IoT Content Retrieval
3.1. Motivational Scenario
3.2. On NDN and Content (Dis)Aggregation
3.3. Realisation Approaches
- The producer provides detailed content (dis)aggregation information (e.g., a manifest detailing the structure of the content and how to extract the different pieces listed in such a manifest);
- A network entity has the content (dis)aggregation intelligence (e.g., the network entity implements the extraction functionalities which are run based on the incoming requests).
- Consumer: consumers hold the (dis)aggregation knowledge and generate complex queries that identify the desired piece of content. For such an approach to work, the intermediary routers must implement and support a (dis)aggregation protocol;
- Router: intermediary routers hold the (dis)aggregation knowledge and processes incoming Interests and return the associated data. Consumers should have the required knowledge to request pieces of content (e.g., through discovery procedures);
- Third party: a third party entity holds the (dis)aggregation information. In this approach, the (dis)aggregation duties are offloaded to the third party entity, which must implement a (dis)aggregation protocol known to users and/or routers.
4. Solution Overview
4.1. Design Choices
4.2. Proof-of-Concept Prototype
4.3. Security Considerations
5. Evaluation
- (1)
- How does the proposed mechanism affect the amount of information exchanged between the edge of the network and the information producers?
- Answered by analysing the number of hops followed by data packets before reaching the consumers.
- (2)
- How does it impact the overall cache utilisation?
- Answered by determining the space used for storing content in all the network content stores.
- (3)
- How do applications perceive the effects of the mechanism?
- Answered by determining the processing delay as observed by the applications (i.e., end-to-end application delay).
5.1. Simulation Set-Up
5.2. Results and Discussion
6. Conclusions and Future Directions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Parameter | Value |
---|---|
Channel Data Rate | 1 Mbps |
Latency | 10 ms |
Interest Rate | 10 Interests/s |
CS Size | 100 packets |
CS Replacement Policy | LRU |
Freshness | [0, 10, 50] s |
Topology depth | (3, 12) |
Simulation Duration | 20 s |
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Quevedo, J.; Corujo, D. Selective Content Retrieval in Information-Centric Networking. Sensors 2022, 22, 8742. https://doi.org/10.3390/s22228742
Quevedo J, Corujo D. Selective Content Retrieval in Information-Centric Networking. Sensors. 2022; 22(22):8742. https://doi.org/10.3390/s22228742
Chicago/Turabian StyleQuevedo, José, and Daniel Corujo. 2022. "Selective Content Retrieval in Information-Centric Networking" Sensors 22, no. 22: 8742. https://doi.org/10.3390/s22228742