Adaptive forwarding strategies to reduce redundant Interests and Data in named data networks

摘要

In Named Data Networks, a requester sends out an Interest for a desired content and the routers forward the Interest to the content source/s. Multiple copies of the content, i.e. Data, arrive at the requester if multiple sources respond to the Interest. Apart from the first copy, all other copies of Data arrived are considered redundant, so as the Interests communicated to generate these copies. These redundancies introduce overhead and unnecessary waste of resources. In this paper, two forwarding strategies, Search and Discovery, are proposed to reduce these redundant transmission. Also, a novel asymmetric tree model for transmission of Interests and Data is proposed to analyze the transmission overhead in the network. In Search, a content source calculates the Interest Forwarding Factor (IFF) for each Interest it receives and responds with Data if the IFF is greater or equal to some threshold T. While in Discovery, after calculating the IFF, a source responds with Data if IFF = T otherwise responds with Offer only. Finally, extensive simulation study is conducted using ndnSIM to evaluate the performance of the proposed strategies. Model based analysis and simulation results confirm that, along with reducing the delay and increasing the cache hit, proposed strategies reduce the overhead significantly.