Heartbeat Synchronization: in a paper entitled Fireﬂy-inspired Heartbeat Synchronization in Overlay Networks by
the University of Bologna and Trento Italy along with the University of Szeged, Hungary: “Heartbeat synchronization
strives to have nodes in a distributed system generate periodic, local “heartbeat” events approximately at the
same time. Many useful distributed protocols rely on the existence of such heartbeats for driving their cycle- based execution..
The heartbeat synchronization protocol for overlay networks is inspired by mathematical models of ﬂash synchronization
in certain species of ﬁre ﬂies. Nodes send ﬂash messages to their neighbors when a local heartbeat triggers.
Fireflies adjust the phase of their next heartbeat based on incoming ﬂash messages using an algorithm inspired by mathematical
models of ﬁre-ﬂy synchronization.
Heartbeat synchronization strives to have nodes in a distributed system generate
periodic, local “heartbeat” events approximately at the same time. It differs from classical clock synchronization
in that nodes are not interested in counting cycles and agreeing on a ID of a current cycle. There is no requirement regarding
the length of a cycle with respect to real time as long as a length is bounded and all nodes agree on it eventually. The goal
is to guarantee that all nodes start and end their cycles at the same time, with an error that is at least one, but preferably
more, orders of magnitude smaller than a chosen cycle length. "What we are interested in guaranteeing is that all nodes start and end their cycles at the same time, with an error
that is at least one, but preferably more, orders of magnitude smaller than a chosen cycle length".
events matched with cyclical heartbeat cycles would require a read / write, store and forward service. Ceilometer as a Time-Series-as-a-Service Ceilometer API is a time series read/write service, useful in auditing leveraging a time-sample
API as part of an event subsystem. = new project called Gnocchi, Gnocchi is split in two parts: a time series API and its
driver, and a resource indexing API with its own driver. Having two distinct driver sets allows it to use different technologies
to store each data type in the best storage engine possible. The canonical driver for time series handling is based on Pandas
and Swift. The canonical resource indexer driver is based on SQLAlchemy. See https://julien.danjou.info/blog/2014/openstack-summit-juno-ceilometer
Firefly heartbeat synchronization reduces
uncertainty in stochastic networks". In context with the Internet of Everything Value index, cross network and system
stochastic harmonization will help improve the process of searching for unused resources and unmet needs of goods at rest
and in transit in context with geo-spatial temporal snapshots in time enabling the redirection, re-vectoring of assets in
near real time to point of consumption, point of need resulting in a more efficient (re) distribution scheme, savings in fuel
and support for real time news-casting / beacon broadcasting, news-casting, replicating advertisements to subscribers.
FIREFLY INSPIRED HEARTBEAT ALGORITHM University
of Bologna / University of Hungary LINK: http://www.slideshare.net/StevenMcGee2/fireyinspired-heartbeat-synchronization