Using current uptime to improve failure detection in peer-to-peer networks

Q Science > QA Mathematics > QA75 Electronic computers. Computer science

Price, Richard Michael ; Tino, Peter,Theodoropoulos, Georgios

University:University of Birmingham

Department:School of Computer Science

关键词: Q Science;    QA Mathematics;    QA75 Electronic computers. Computer science;   

Others  :  http://etheses.bham.ac.uk//id/eprint/1101/1/Price10PhD.pdf

来源: University of Birmingham eTheses Repository

【 摘 要 】

Peer-to-Peer (P2P) networks share computer resources or services through the exchange of information between participating nodes. These nodes form a virtual network overlay by creating a number of connections with one another. Due to the transient nature of nodes within these systems any connection formed should be monitored and maintained to ensure the routing table is kept up-to-date. Typically P2P networks predefine a fixed keep-alive period, a maximum interval in which connected nodes must exchange messages. If no other message has been sent within this interval then keep-alive messages are exchanged to ensure the corresponding node has not left the system. A fixed periodic interval can be viewed as a centralised, static and deterministic mechanism; maintaining overlays in an predictable, reliable and non-adaptive fashion. Several studies have shown that older peers are more likely to remain in the network longer than their short-lived counterparts. Therefore using the distribution of peer session times and the current age of peers as key attributes, we propose three algorithms which allow connections to extend the interval between successive keep-alive messages based upon the likelihood that a corresponding node will remain in the system. By prioritising keep-alive messages to nodes that are more likely to fail, our algorithms reduce the expected delay between failures occurring and their subsequent detection. Using extensively empirical analysis, we analyse the properties of these algorithms and compare them to the standard periodic approach in unstructured and structured network topologies, using tracedriven simulations based upon measured network data. Furthermore we also investigate the effect of nodes that misreport their age upon our adaptive algorithms and detail an efficient keep-alive algorithm that can adapt to the limitations network address translation devices.