Effectiveness of Cloud Services for Scientific and VoD Applications

Cloud platforms have emerged as the primary data warehouse for a variety of applications, such as DropBox, iCloud, Google Music, etc. These applications allow users to store data in the cloud and access it from anywhere in the world. Commercial clouds are also well suited for providing high-end servers for rent to execute applications that require computation resources sporadically. Cloud users only pay for the time they actually use the hardware and the amount of data that is transmitted to and from the cloud, which has the potential to be more cost effective than purchasing, hosting, and maintaining dedicated hardware. In this dissertation, we look into the efficiency of the cloud Infrastructure-as-a-Service (IaaS) model for two real time high bandwidth applications: A scientific application of short-term weather forecasting and Video on Demand services. We show that, cloud services are efficient in both network and computation for real time scientific application of weather forecasting. We present a related list reordering approach, which reduces the network traffic of serving videos from VoD services and improve the efficiency of caches deployed to serve them. Also, we present transcoding policies to reduce the transcoding workload and present prediction models to maintain performance of providing ABR streaming of VoD services at the client with online transcoding in the cloud

Future internets escape the simulator

Standardization of basic underlying protocols such as the Internet Protocol (IP) has enabled rapid growth and widespread adoption of the global Internet. However, standardization carries the attendant risks of reducing variability and slowing the pace of progress. Validation and deployment of potential innovations by researchers in networking, distributed computing, and cloud computing are often hampered by Internet ossification, the inertia associated with the accumulated mass of hardware, software, and protocols that constitute the global, public Internet. Researchers simply cannot develop, test, and deploy certain classes of important innovations into the Internet. In the best case, the experimental components and traffic would be ignored; in the worst case, they could disrupt the correct behavior of the Internet. Cloud computing researchers confront a similar dilemma. In order to maintain uniformity and efficiency in their data centers, commercial cloud providers generally do not provide “under the hood” controls that permit modification to the underlying network topology or protocols that comprise the cloud environment