[talks] Y Wang preFPO

Melissa M Lawson mml at CS.Princeton.EDU
Mon Nov 27 10:11:48 EST 2006

Young 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.

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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