This paper is a simulation based study of cloud assisted multi-user video streaming. It is based upon two use cases (one related to video poker the other related to MOOCs). The paper looks at strategies for placing cloud locations to facilitate streaming using Amazon EC2 cloud locations. The paper compares a strategy that dynamically picks new locations for cloud hosts as time goes on. Interestingly this seems to provide little benefit compared with simply having a good initial choice of sites even when users may drop into and out of a cloud chat session over the course of many hours.
Ingmar Poese, Benjamin Frank, Bernhard Ager, Georgios Smaragdakis and Anja Feldmann
This paper looks at CDN networks and, in particular, suggests
Provider-aided Distance Information System (PaDIS), which is a mechanism
to rank client-host pairs based upon information such as RTT,
bandwidth or number of hops. Headline figure, 70% of http traffic
from a major european ISP can be accessed via multiple different
locations. “Hyper giants” are defined as the large content providers
such as google, yahoo and CDN providers which effectively build
their own network and have content in multiple places.
Eric Nordstrom, David Shue, Prem Gopalan, Robert Kiefer, Matvey Arye, Steven Y. Ko, Jennifer Rexford and Michael J. Freedman
USENIX Symposium on Networked Systems Design and Implementation
This paper looks at the problem of accessing services on a network
which are potentially geographically distributed (for example, the
closest server for a particular service). Serval allows the
discovery of end-points for services and allows them to seamlessly
migrate so ‘‘end-points can seamlessly change network addresses,
migrate flows across interfaces… [with] uninterrupted service access."
Serval runs on an unmodified network layer. Application communicate
with service names (identifying the changing group of hosts
providing a service) not addresses and ports.
Networking 2011, Lecture Notes in Computer Science (6640)
This paper creates a simple mathematical model based on Markov chains which can model (with some simple assumptions) the type of cacheing trees seen in content centric networking. The model is tested with some simulation results.