CedCom A Cache Only Memory Architecture for Big Data Applications
Keywords
Cache Only Memory Architecture, Big Data, Attraction Memory
Synopsis
Distributed architecture is widely used for storing and processing Big
Data. Operations on Big Data need first,locating the required data
blocks and then, read them. Reading data from secondary storage to
process Big Data jobs is not an ideal approach especially for high
performance applications. Because, the processors cannot access data
faster if they are stored in secondary devices. In addition, fetching
data from main memory is time consuming due to limited I/O
bandwidth. Therefore, to optimize the application performance, it is not
sufficient to have efficient algorithms only, an efficient architecture
is needed to provide faster data access to the processors. The need for
such an architecture has been a research issue for a long-time, however,
the state of the art is still missing one. The CedCom model offers a
flexible architecture which caches data in main memory. It essentially
transforms a main memory into a attraction memory which enables
high-speed data access. Also, it enables automatic migration of data
blocks and computations across the nodes contained in the clusters. It
offers an exchange protocol for fast transfer of data blocks between the
different physical nodes and speeds up job processing. The proposed
architecture combines the power of Cache-Only Memory Architectures
(COMAs) and the structural principle of Hadoop.
Software
Technical References
