Optimal scheduling and fair servicepolicy for STDMA in underwater networks with acoustic communications

In this work, a multi-hop string network with a single sink node is analyzed. A periodic optimal scheduling for TDMA operation that considers the characteristic long propagation delay of the underwater acoustic channel is presented. This planning of transmissions is obtained with the help of a new geometrical method based on a 2D lattice in the space-time domain. In order to evaluate the performance of this optimal scheduling, two service policies have been compared: FIFO and Round-Robin. Simulation results, including achievable throughput, packet delay, and queue length, are shown. The network fairness has also been quantified with the Gini index

Symbolic Time Series Analysis in Economics

In this paper I describe and apply the methods of Symbolic Time Series Analysis (STSA) to an experimental framework. The idea behind Symbolic Time Series Analysis is simple: the values of a given time series data are transformed into a finite set of symbols obtaining a finite string. Then, we can process the symbolic sequence using tools from information theory and symbolic dynamics. I discuss data symbolization as a tool for identifying temporal patterns in experimental data and use symbol sequence statistics in a model strategy. To explain these applications, I describe methods to select the symbolization of the data (Section 2), I introduce the symbolic sequence histograms and some tools to characterize and compare these histograms (Section 3). I show that the methods of symbolic time series analysis can be a good tool to describe and recognize time patterns in complex dynamical processes and to extract dynamical information about this kind of system. In particular, the method gives us a language in which to express and analyze these time patterns. In section 4 I report some applications of STSA to study the evolution of ifferent economies. In these applications data symbolization is based on economic criteria using the notion of economic regime introduced earlier in this thesis. I use STSA methods to describe the dynamical behavior of these economies and to do comparative analysis of their regime dynamics. In section 5 I use STSA to reconstruct a model of a dynamical system from measured time series data. In particular, I will show how the observed symbolic sequence statistics can be used as a target for measuring the goodness of fit of proposed models.

A Simple Discrete System with Chaotic Behavior

We discuss the behavior of a particular discrete system, viz. Post's system of tag with alphabet $\{0,1\}$, deletion number $d=3$, and rules: $0\rightarrow 00$, $1\rightarrow 1101$. As initial strings we consider all strings of length less than or equal to 15 as well as all 'worst case' inputs of the form $(100)^m$ with $1\leq m \leq 128$

The streaming kk-mismatch problem

We consider the streaming complexity of a fundamental task in approximate pattern matching: the $k$-mismatch problem. It asks to compute Hamming distances between a pattern of length $n$ and all length-$n$ substrings of a text for which the Hamming distance does not exceed a given threshold $k$. In our problem formulation, we report not only the Hamming distance but also, on demand, the full \emph{mismatch information}, that is the list of mismatched pairs of symbols and their indices. The twin challenges of streaming pattern matching derive from the need both to achieve small working space and also to guarantee that every arriving input symbol is processed quickly. We present a streaming algorithm for the $k$-mismatch problem which uses $O(k\log{n}\log\frac{n}{k})$ bits of space and spends \ourcomplexity time on each symbol of the input stream, which consists of the pattern followed by the text. The running time almost matches the classic offline solution and the space usage is within a logarithmic factor of optimal. Our new algorithm therefore effectively resolves and also extends an open problem first posed in FOCS'09. En route to this solution, we also give a deterministic $O( k (\log \frac{n}{k} + \log |\Sigma|) )$-bit encoding of all the alignments with Hamming distance at most $k$ of a length-$n$ pattern within a text of length $O(n)$. This secondary result provides an optimal solution to a natural communication complexity problem which may be of independent interest.Comment: 27 page

Exact limiting solutions for certain deterministic traffic rules

We analyze the steady-state flow as a function of the initial density for a class of deterministic cellular automata rules (``traffic rules'') with periodic boundary conditions [H. Fuks and N. Boccara, Int. J. Mod. Phys. C 9, 1 (1998)]. We are able to predict from simple considerations the observed, unexpected cutoff of the average flow at unity. We also present an efficient algorithm for determining the exact final flow from a given finite initial state. We analyze the behavior of this algorithm in the infinite limit to obtain for R_m,k an exact polynomial equation maximally of 2(m+k)th degree in the flow and density.Comment: 25 pages, 8 figure

Design strategies for the creation of aperiodic nonchaotic attractors

Parametric modulation in nonlinear dynamical systems can give rise to attractors on which the dynamics is aperiodic and nonchaotic, namely with largest Lyapunov exponent being nonpositive. We describe a procedure for creating such attractors by using random modulation or pseudo-random binary sequences with arbitrarily long recurrence times. As a consequence the attractors are geometrically fractal and the motion is aperiodic on experimentally accessible timescales. A practical realization of such attractors is demonstrated in an experiment using electronic circuits.Comment: 9 pages. CHAOS, In Press, (2009