[talks] Y Wang preFPO

[Melissa M Lawson]

Yong Wang will present his preFPO on Thursday November 30 at 10:30AM in Room 402. The
members of his committee are:  Margaret Martonosi, advisor; Li-Shiuan Peh, Jennifer
Rexford, Larry Peterson, and Kai Li.  
Everyone is invited to attend his talk.. His abstract follows below.

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Wireless sensor networks and disruption-tolerant networks are new types of challenged
networks that have very unpredictable and unusual situations, quite distinct from what a
protocol architecture is usually designed for.  The unique communication characteristics
of these networks have created new, interesting challenges for the research community,
such as opportunistic mobility, sparse connectivity, frequent network
disruption/disconnection, and severely constrained energy budgets.  Such challenges demand
novel solutions to maintain efficient routing and take advantage of existing network
services.  This requires the network to be aware of such challenges and respond
appropriately.

In this thesis, I explore new optimizations via situation-awareness to improve routing
performance in the presence of such challenges and disruptions. In particular, I study
five categories of challenges that cover a wide range of disruptions experienced in
challenged networks:
sparse end-to-end connectivity, highly varying mobility, opportunistic connectivity,
intermittent connectivity, and network congestion. The first three categories are confined
to mobile networks, while the last two categories apply to static networks.

The first category consists of networks with sparse end-to-end connectivity.  Therefore,
route breakage may bring a communication pair into temporary disconnection or lead to
nodes using stale routes.  I propose a timekeeping technique to drive route prefetching
and decay operations based on route lifetime information. Through extensive simulations, I
demonstrate up to 31% improvement in packet delivery rate and 53% improvement in average
end-to-end packet latency.

The second category consists of networks with a varying mobility pattern that is typical
in many emerging networks, an example of which is ZebraNet.  With such a mobility pattern,
nodes move in phases that have very different characteristics  I propose a model-based
approach to capture mobility phase changes in order to maintain efficient routing.
When evaluated using a mobility trace from the real-world ZebraNet deployment, the
situation-aware approach leads to an improvement of up to 120% in packet delivery rate.

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