Abstract
Distributed Hash Tables (DHTs) were originated from the design of structured peer-to-peer (P2P) systems. A DHT provides a key-based lookup service similar to a hash table. In this paper, we present the detailed design of a new DHT protocol, Tambour. The novelty of the protocol is that it uses parallel lookup to reduce retrive latency and bounds communication overhead to a dynamically adjusted routing table. Tambour estimates the probabilities of routing entries' liveness based on statistics of node lifetime history and evicts dead entries after lookup failures. When the network is unstable, more routing entries will be evicted in a given period of time, and the routing tables will be getting smaller which minimize the number of timeouts for later lookup requests. An experimental prototype of Tambour has been simulated and compared against two popular DHT protocols. Results show that Tambour outperforms the compared systems in terms of bandwith cost, lookup latency and the overall efficiency.
Highlights
Unlike the majority of current file sharing P2P systems, Distributed Hash Tables (DHTs) organize the P2P network in a structured manner and provide a simple lookup interface which similar to hash table
We present the detailed design of a new DHT protocol, Tambour
When the network is unstable, more routing entries will be evicted in a given period of time, and the routing tables will be getting smaller which minimize the number of timeouts for later lookup requests
Summary
Unlike the majority of current file sharing P2P systems, DHTs organize the P2P network in a structured manner and provide a simple lookup interface which similar to hash table. Each host in DHTs stores and serves resources named by keys like a bucket in classic hash tables, and it employs a distributed lookup function collaboratively with other hosts to locate the hosts being responsible for assigned keys. This simple and elegant lookup interface makes DHTs a potential universal building block for many distributed system applications. There are various methods to reduce lookup latency and increase the accuracy of routing tables under churn These methods generate extra communication to get more information about the liveness of existing neighbours and new nodes in the network.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Communications, Network and System Sciences
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
