The following technical report is available from
http://aib.informatik.rwth-aachen.de/:
A New Satisfiability Algorithm With Applications To Max-Cut
Joachim Kneis, Peter Rossmanith
AIB 2005-08
We prove an upper bound of m/5.217+3 on the treewidth of a graph with
m edges. Moreover, we can always find efficiently a set of no more
than m/5.217 nodes whose removal yields a very simple graph. As an
application, we immediately get simple algorithms for several problems,
including Max-Cut, Max-2-SAT and Max-2-XSAT. The resulting algorithms
have running times of O*(2^t/5.217), where t is the number of distinct
clause types. In particular, this implies a record-breaking time
complexity of O*(2^m/5.217).
The following technical report is available from
http://aib.informatik.rwth-aachen.de/:
Felix C. Freiling, Thorsten Holz, Georg Wicherski
Botnet Tracking: Exploring a Root-Cause Methodology to Prevent
Distributed Denial-of-Service Attacks
AIB 2005-07
Abstract:
Denial-of-Service (DoS) attacks pose a significant threat to the
Internet today especially if they are distributed, i.e., launched
simultaneously at a large number of systems. Reactive techniques that
try to detect such an attack and throttle down malicious traffic prevail
today but usually require an additional infrastructure to be really
effective. In this paper we show that preventive mechanisms can be as
effective with much less effort: We present an approach to (distributed)
DoS attack prevention that is based on the observation that coordinated
automated activity by many hosts needs a mechanism to remotely control
them. To prevent such attacks, it is therefore possible to identify,
infiltrate and analyze this remote control mechanism and to stop it in
an automated fashion. We show that this method can be realized in the
Internet by describing how we infiltrated and tracked IRC-based botnets
which are the main DoS technology used by attackers today.
The following technical report is available from
http://aib.informatik.rwth-aachen.de/:
Adaptive Routing with Stale Information
Simon Fischer, Berthold Vöcking
AIB 2005-06
We investigate adaptive routing policies for large networks in which
agents reroute traffic based on old information. It is a well known and
practically relevant problem that old information can lead to undesirable
oscillation effects resulting in poor performance. We investigate how
adaptive routing policies should be designed such that these effects can
be avoided.
In our theoretical model, the network is represented by a general graph
with latency functions on the edges. Traffic is managed by a large number
of agents each of which is responsible for a negligible amount of traffic.
Initially the agents' routing paths are chosen in an arbitrary fashion.
>From time to time each agent revises her routing strategy by sampling
another path and switching with positive probability to this path if it
promises smaller latencies. As the information on which the agent bases
her decision might be stale, however, this does not necessarily lead to
an improvement. The points of time at which agents revise their strategy
are generated by a Poisson distribution. Stale information is modelled
in form of a bulletin board that is updated periodically and lists the
latencies on all edges.
We analyze such a distributed routing process in the so-called fluid
limit, that is, we use differential equations describing the fractions
of traffic on different paths over time. In our model, we can show the
following effects. Simple routing policies that always switch to the
better alternative lead to oscillation, regardless at which frequency
the bulletin board is updated. Oscillation effects can be avoided,
however, when using smooth adaption policies that do not always switch
to better alternatives but only with a probability depending on the
advantage in the latency. In fact, such policies have dynamics that
converge to a fixed point corresponding to a Nash equilibrium for the
underlying routing game, provided the update periods are not too large.
In addition, we also analyze the speed of convergence towards approximate
equilibria of two specific variants of smooth adaptive routing policies,
e.g., for a replication policy adopted from evolutionary game theory.