研究目的
To address the challenges posed by the convergence of networking and computing in the edge for a number of scenarios, including reliability in Fog-to-Cloud computing, architecture for a residential SDN gateway featuring NFV, switching based on SDN for data centres, resiliency in SDN controller location, and delay analysis in a single node C-RAN scenario.
研究成果
The paper presents a comprehensive overview of the Elastic Networks research network's approach to addressing the convergence of networking and computing in the edge. It highlights innovative solutions for reliability in F2C, SDN/NFV architectures, flexible packet matching, resilient controller location, and eCPRI traffic latency modeling, suggesting significant advancements in the field.
研究不足
The paper does not explicitly mention limitations, but potential areas for optimization could include scalability of the proposed solutions, real-world deployment challenges, and the need for further testing under varied conditions.
1：Experimental Design and Method Selection:
The paper covers multiple topics with different methodologies, including Zero-Knowledge strategy for reliability in F2C, SDN and NFV application in residential networks, flexible packet matching in hardware for SDN, resilient controller location under target attacks in SDN network, and eCPRI fronthaul traffic latency modeling.
2：Sample Selection and Data Sources:
Trials were run in the CRAAX testbed for F2C reliability, and simulations were conducted for other topics.
3：List of Experimental Equipment and Materials:
Raspberry PIs and virtualized entities for F2C trials, SRAMs for flexible packet matching, and various network configurations for other studies.
4：Experimental Procedures and Operational Workflow:
Detailed procedures vary by topic, including the ZK strategy for F2C, SDN/NFV architecture deployment, cuckoo hashing implementation, and latency modeling.
5：Data Analysis Methods:
Statistical techniques and simulations were used to analyze results, including memory occupancy for cuckoo hashing and queueing delay percentiles for eCPRI traffic.
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