Description:
 
Background
Research on information-centric networking (ICN) architectures over the past few years show a focus on a number of central network design issues. One prominent issue is how to jointly design traffic engineering and caching strategies to maximally exploit the bandwidth and storage resources of the network for optimal performance. While traffic engineering and caching have been investigated separately for many years, their joint optimization within an ICN setting was under‑explored.
 
Technology Overview
In this invention, a new unified framework is used to minimize congestion-dependent network cost in information-centric networks by jointly optimizing forwarding and caching strategies. Since caching variables are integer-constrained, the resulting optimization problem is considered to be NP-hard (non-deterministic polynomial-time hardness). Northeastern researchers have developed a necessary optimality condition for the relaxed problem and leveraged this result to design MinDelay: an adaptive and distributed joint forwarding and caching algorithm based on the conditional gradient algorithm. 
The MinDelay algorithm efficiently yields feasible routing variables and integer caching variables at each iteration and can be implemented with low complexity and overhead. Over a wide range of network topologies, simulation results show that MinDelay typically has significantly better delay performance in the low to moderate request rate regions. Furthermore, the MinDelay and VIP algorithms complement each other in delivering superior delay performance across the entire range of request arrival rates.
 
Benefits
- Can minimize congestion-dependent network costs through jointly optimal request forwarding and caching
- It is both distributed and adaptive
- Operates based on packets passing through and communication with immediate neighboring nodes
- Better delay performance in the low to moderate request rate regions 
 
Applications
- Content delivery networks
- Information-centric networks
- Peer-to-peer networks
- Cloud computing 
 
Opportunity
- Licensing
- Research collaboration
- Partnering
Patent Information:
Category(s):
Software
For Information, Contact:
Mark Saulich
Associate Director of Commercialization
Northeastern University
m.saulich@northeastern.edu
Inventors:
Edmund Yeh
Milad Mahdian
Keywords: