124,400 research outputs found
Network Creation Games: Think Global - Act Local
We investigate a non-cooperative game-theoretic model for the formation of
communication networks by selfish agents. Each agent aims for a central
position at minimum cost for creating edges. In particular, the general model
(Fabrikant et al., PODC'03) became popular for studying the structure of the
Internet or social networks. Despite its significance, locality in this game
was first studied only recently (Bil\`o et al., SPAA'14), where a worst case
locality model was presented, which came with a high efficiency loss in terms
of quality of equilibria. Our main contribution is a new and more optimistic
view on locality: agents are limited in their knowledge and actions to their
local view ranges, but can probe different strategies and finally choose the
best. We study the influence of our locality notion on the hardness of
computing best responses, convergence to equilibria, and quality of equilibria.
Moreover, we compare the strength of local versus non-local strategy-changes.
Our results address the gap between the original model and the worst case
locality variant. On the bright side, our efficiency results are in line with
observations from the original model, yet we have a non-constant lower bound on
the price of anarchy.Comment: An extended abstract of this paper has been accepted for publication
in the proceedings of the 40th International Conference on Mathematical
Foundations on Computer Scienc
Dynamic vs Oblivious Routing in Network Design
Consider the robust network design problem of finding a minimum cost network
with enough capacity to route all traffic demand matrices in a given polytope.
We investigate the impact of different routing models in this robust setting:
in particular, we compare \emph{oblivious} routing, where the routing between
each terminal pair must be fixed in advance, to \emph{dynamic} routing, where
routings may depend arbitrarily on the current demand. Our main result is a
construction that shows that the optimal cost of such a network based on
oblivious routing (fractional or integral) may be a factor of
\BigOmega(\log{n}) more than the cost required when using dynamic routing.
This is true even in the important special case of the asymmetric hose model.
This answers a question in \cite{chekurisurvey07}, and is tight up to constant
factors. Our proof technique builds on a connection between expander graphs and
robust design for single-sink traffic patterns \cite{ChekuriHardness07}
Forecasting the cost of processing multi-join queries via hashing for main-memory databases (Extended version)
Database management systems (DBMSs) carefully optimize complex multi-join
queries to avoid expensive disk I/O. As servers today feature tens or hundreds
of gigabytes of RAM, a significant fraction of many analytic databases becomes
memory-resident. Even after careful tuning for an in-memory environment, a
linear disk I/O model such as the one implemented in PostgreSQL may make query
response time predictions that are up to 2X slower than the optimal multi-join
query plan over memory-resident data. This paper introduces a memory I/O cost
model to identify good evaluation strategies for complex query plans with
multiple hash-based equi-joins over memory-resident data. The proposed cost
model is carefully validated for accuracy using three different systems,
including an Amazon EC2 instance, to control for hardware-specific differences.
Prior work in parallel query evaluation has advocated right-deep and bushy
trees for multi-join queries due to their greater parallelization and
pipelining potential. A surprising finding is that the conventional wisdom from
shared-nothing disk-based systems does not directly apply to the modern
shared-everything memory hierarchy. As corroborated by our model, the
performance gap between the optimal left-deep and right-deep query plan can
grow to about 10X as the number of joins in the query increases.Comment: 15 pages, 8 figures, extended version of the paper to appear in
SoCC'1
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