D4M, a Self-Adapting Decentralized Derived Data Collection and Monitoring Framework

Abstract

Peer-to-peer systems are evolving as a viable distributed resource sharing paradigm on the Internet. The trend is growing towards the usage of such decentralized systems because they are more scalable and resource efficient than centralized systems. Current decentralized systems, like peer-to-peer networks, lack functionality to adapt the transmission of certain information artifacts, according to their access patterns. Additionally, there is still no approach for an efficient dependency management between distributed and dependent information in decentralized networks. This paper presents our ideas of D4M, a framework for the management of distributed derived data in decentralized systems, and how such data can be handled in an efficient manner.