1 research outputs found
Algorithms for Data Dissemination and Collection
Broadcasting and gossiping are classical problems that have been
widely studied for decades. In broadcasting, one source node wishes to
send a message to every other node, while in gossiping, each node has
a message that they wish to send to everyone else. Both are some of
the most basic problems arising in communication networks. In this
dissertation we study problems that generalize gossiping and
broadcasting. For example, the source node may have several messages
to broadcast or multicast. Many of the works on broadcasting in the
literature are focused on homogeneous networks. The algorithms
developed are more applicable to managing data on local-area
networks. However, large-scale storage systems often consist of
storage devices clustered over a wide-area network. Finding a suitable
model and developing algorithms for broadcast that recognize the
heterogeneous nature of the communication network is a significant part of
this dissertation.
We also address the problem of data collection in a wide-area network,
which has largely been neglected, and is likely to become more
significant as the Internet becomes more embedded in everyday life. We
consider a situation where large amounts of data have to be moved from
several different locations to a destination. In this work, we focus
on two key properties: the available bandwidth can fluctuate, and the
network may not choose the best route to transfer the data between two
hosts.
We focus on improving the task completion time by re-routing the data
through intermediate hosts and show that under certain network
conditions we can reduce the total completion time by a factor of
two. This is done by developing an approach for computing coordinated
data collection schedules using network flows