Seiberg duality, quiver gauge theories, and Ihara's zeta function

We study Ihara’s zeta function for graphs in the context of quivers arising from gauge theories, especially under Seiberg duality transformations. The distribution of poles is studied as we proceed along the duality tree, in light of the weak and strong graph versions of the Riemann Hypothesis. As a by-product, we find a refined version of Ihara’s zeta function to be the generating function for the generic superpotential of the gauge theory

A Combinatorial Framework for Designing (Pseudoknotted) RNA Algorithms

We extend an hypergraph representation, introduced by Finkelstein and Roytberg, to unify dynamic programming algorithms in the context of RNA folding with pseudoknots. Classic applications of RNA dynamic programming energy minimization, partition function, base-pair probabilities...) are reformulated within this framework, giving rise to very simple algorithms. This reformulation allows one to conceptually detach the conformation space/energy model -- captured by the hypergraph model -- from the specific application, assuming unambiguity of the decomposition. To ensure the latter property, we propose a new combinatorial methodology based on generating functions. We extend the set of generic applications by proposing an exact algorithm for extracting generalized moments in weighted distribution, generalizing a prior contribution by Miklos and al. Finally, we illustrate our full-fledged programme on three exemplary conformation spaces (secondary structures, Akutsu's simple type pseudoknots and kissing hairpins). This readily gives sets of algorithms that are either novel or have complexity comparable to classic implementations for minimization and Boltzmann ensemble applications of dynamic programming

Analysis and design of algorithms : double hashing and parallel graph searching

The following is in two parts, corresponding to the two separate topics in the dissertation.Probabilistic Analysis of Double HashingIn [GS78], a deep and elegant analysis shows that double hashing is asymptotically equivalent to the ideal uniform hashing up to a load factor of about 0.319. In this paper we show how a resampling technique can be used to develop a surprisingly simple proof of the result that this equivalence holds for load factors arbitrarily close to 1.Parallel Depth First Search of Planar Directed Acyclic GraphsIn 1988, Kao [Kao88] presented the first NC algorithm for the depth first search of a directed planar graph. Recently, Kao and Klein [KK90] reduced the number of processors required from O(n^4) to linear, but the time bound is O(log^8 n).We present an algorithm for the depth first search of a planar directed acyclic graph with k sources using O(n) processors and O(log k log n) time on a CRCW PRAM model. For planar dags with a single source and a single sink, we present a simple optimal algorithm which gives the depth first search in O(log n) time with O(n/log n) processors on an EREW PRAM. For a single-source multiple-sink planar dag, we have an O(log n) time O(n) processor EREW algorithm. The EREW algorithms assume that the embedding is given. A simplified variant of the depth first search of a multisource planar dag can be used to solve the single source reachability problem for a planar directed acyclic graph in O(log^2 n) time and O(n) processors on an CRCW PRAM. Since an O(log^4 n) algorithm for this problem is used as a subroutine by Kao and Klein in their depth first search for the general planar directed graph, this will lower their time bound by a factor of log^2 n. Our work uses the concept of a planar Euler tour depth first search, a depth first search in which the Euler tour around the tree is planar and crosses no tree edge. This concept may prove to be of use in other parallel algorithms for planar graphs

Graph-based software specification and verification

The (in)correct functioning of many software systems heavily influences how\ud we qualify our daily lives. Software companies as well as academic computer\ud science research groups spend much effort on applying and developing techniques for improving the correctness of software systems. In this dissertation\ud we focus on using and developing graph-based techniques to specify and verify\ud the behaviour of software systems in general, and object-oriented systems more\ud specifically. We elaborate on two ways to improve the correctness (and thereby\ud the quality) of such systems.\ud Firstly, we investigate the potential of using the graph transformation tech-\ud nique to formally specify the dynamic semantics of (object-oriented) program-\ud ming languages. Those semantics are typically specified in natural language.\ud Such specifications are often hard to understand or even ambiguous. We show\ud how the graph transformation framework provides formal and intuitive means\ud for their specification.\ud Secondly, we develop techniques to verify systems of which the behaviour is\ud specified as graph production systems. For the verification of such systems, we\ud introduce an algorithm that combines a well-known on-the-\ud y model checking\ud algorithm with ideas from bounded model checking. One of the main prob-\ud lems of model checking is the state-explosion problem. This problem is often\ud tackled using partial order reduction techniques. Unfortunately, many such\ud techniques are based on assumptions that do not hold for graph production sys-\ud tems. Therefore, we develop a new dynamic partial order reduction algorithm\ud based on selecting so-called probe sets and prove its correctness.\ud Most of the techniques developed in this dissertation have been implemented\ud in the graph transformation tool GROOVE

Congestion avoidance in overlay networks through multipath routing

Overlay networks relying on traditional multicast routing approaches use only a single path between a sender and a receiver. This path is selected based on latency, with the goal of achieving fast delivery. Content is routed through links with low latency, ignoring slower links of the network which remain unused. With the increasing size of content on the Internet, this leads to congestion, messages are dropped and have to be retransmitted. A multicast multipath congestion-avoidance routing scheme which uses multiple bottleneck-disjoint paths between senders and receivers was developed, as was a linear programming model of the network to distribute messages intelligently across these paths according to two goals: minimum network usage and load-balancing. The former aims to use as few links as possible to perform routing, while the latter spreads messages across as many links as possible, evenly distributing the traffic. Another technique, called message splitting, was also used. This allows nodes to send a single copy of a message with multiple receivers, which will then be duplicated by a node closer to the receivers and sent along separate paths only when required. The model considers all of the messages in the network and is a global optimisation. Nevertheless, it can be solved quickly for large networks and workloads, with the cost of routing remaining almost entirely the cost of finding multiple paths between senders and receivers. The Gurobi linear programming solver was used to find solutions to the model. This routing approach was implemented in the NS-3 network simulator. The work is presented as a messaging middleware scheme, which can be applied to any overlay messaging network.Open Acces

Geographic Routing for Point to Point Data Delivery in Wireless Sensor Network

Ph.DDOCTOR OF PHILOSOPH