THESIS
2013
xi, 73 pages : illustrations ; 30 cm
Abstract
This work aims to provide predictable and guaranteed performance support for real-time
applications in cloud data center network (DCN) by optimizing network topology and
transport layer design.
Sensing enAbled Localization and Tracking (SALT) system is an integrated real-time
application for positioning, tracking and resource allocation for cognitive radio network
in TV white space, which illustrates the latency and throughput requirements of real-time
applications in modern DCN. SALT localizes Secondary Users (SU) based on their
measurement of Primary User signals in the TV spectrum, and also uses the SU movement
information to dynamically manage the available spectrum with an optimal spectrum
allocation algorithm to maximize the up-link throughput of the entire network.
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This work aims to provide predictable and guaranteed performance support for real-time
applications in cloud data center network (DCN) by optimizing network topology and
transport layer design.
Sensing enAbled Localization and Tracking (SALT) system is an integrated real-time
application for positioning, tracking and resource allocation for cognitive radio network
in TV white space, which illustrates the latency and throughput requirements of real-time
applications in modern DCN. SALT localizes Secondary Users (SU) based on their
measurement of Primary User signals in the TV spectrum, and also uses the SU movement
information to dynamically manage the available spectrum with an optimal spectrum
allocation algorithm to maximize the up-link throughput of the entire network.
We also present MCP, a distributed and reactive mechanism for DCN to achieve minimal
per-packet delay while providing the guaranteed transmission rates to meet flow
deadlines. To design MCP, we first formulate a stochastic packet delay minimization
problem with constraints on deadline completion and network stability. By solving this
problem via Lyapunov Optimization techniques, we derive an optimal congestion window update function which establishes the theoretical foundation for MCP. To be incrementally
deployable with existing switch hardware, MCP leverages existing mechanism on
commodity switch to approximate the optimal window update function.
For topology layer, FatTorus is proposed, which is a joint topology design of storage
units and servers in cloud data center. FatTorus, by means of traffic routing rules, achieves
performance isolation of flows generated by storage unit and servers, and is a first step in
designing a heterogeneous server-centric network in DCN. FatTorus provides low latency
interconnection for servers, as well as high-throughput networking for the storage units.
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