A Top-k Concast Service for Multiple Tiny Data Retrieval in NDN

Abstract

Offering a paradigm for retrieving and aggregating multiple data from multiple sources is a crucial requirement in a large content-centric network. However, the major hindrances to this paradigm are network’s dynamic feature, traffic balance, wired forwarding and the absence of cooperation between communications and computations. In this paper, we present a scalable and top-k Concast service on Named Data Networking (NDN). The service enables cooperation between top-k tiny data discovering and aggregating among multiple routers and paths for a user’s Interest that contained a hierarchical name and other constraints. Specifically, multiple types and strategies of tiny data aggregation for merging and processing the positive data and suppressing the negative, futile data, as well as a determination of response completeness are introduced for enhancing relevant results recall and sharing. The experimentation demonstrated the top-k Concast service can effectively improve the service quality, reduce network traffic and shorten response time.