Improving Availability of Mobile Code Systems by Decoupling Interaction from Mobility

Resource availability in pervasive environments is restricted by many either mobility- and/or security-related factors. Multi-agent systems deployed in such environments would have to rely on a potentially low number of hosts allowing and supporting the arrival and execution of foreign code. To address this issue, this paper proposes to decouple interaction of executing programs and services from the actual software mobility pattern used to realize this interaction. The proposed system (MoDeS - Mobility Decision System) dynamically decides on the best mobility method to implement a series of software interactions while satisfying the appropriate software constraints. The system takes as input an interaction plan and produces the corresponding mobility plan. A series of simulations were performed on single- and multi-hop scenarios which showed that MoDeS can significantly increase the availability of software interactions even in highly constraint environments.</p

Stability of Simple Periodic Orbits and Chaos in a Fermi -- Pasta -- Ulam Lattice

We investigate the connection between local and global dynamics in the Fermi -- Pasta -- Ulam (FPU) $\beta$ -- model from the point of view of stability of its simplest periodic orbits (SPOs). In particular, we show that there is a relatively high $q$ mode $(q=2(N+1)/{3})$ of the linear lattice, having one particle fixed every two oppositely moving ones (called SPO2 here), which can be exactly continued to the nonlinear case for $N=5+3m, m=0,1,2,...$ and whose first destabilization, $E_{2u}$, as the energy (or $\beta$) increases for {\it any} fixed $N$, practically {\it coincides} with the onset of a ``weak'' form of chaos preceding the break down of FPU recurrences, as predicted recently in a similar study of the continuation of a very low ($q=3$) mode of the corresponding linear chain. This energy threshold per particle behaves like $\frac{E_{2u}}{N}\propto N^{-2}$. We also follow exactly the properties of another SPO (with $q=(N+1)/{2}$) in which fixed and moving particles are interchanged (called SPO1 here) and which destabilizes at higher energies than SPO2, since $\frac{E_{1u}}{N}\propto N^{-1}$. We find that, immediately after their first destabilization, these SPOs have different (positive) Lyapunov spectra in their vicinity. However, as the energy increases further (at fixed $N$), these spectra converge to {\it the same} exponentially decreasing function, thus providing strong evidence that the chaotic regions around SPO1 and SPO2 have ``merged'' and large scale chaos has spread throughout the lattice.Comment: Physical Review E, 18 pages, 6 figure

Scaling similarities of multiple fracturing of solid materials

It has recently reported that electromagnetic flashes of low-energy <IMG WIDTH='12' HEIGHT='29' ALIGN='MIDDLE' BORDER='0' src='http://www.nonlin-processes-geophys.net/11/137/2004/npg-11-137-img1.gif' ALT='$gamma$'>-rays emitted during multi-fracturing on a neutron star, and electromagnetic pulses emitted in the laboratory by a disordered material subjected to an increasing external load, share distinctive statistical properties with earthquakes, such as power-law energy distributions (Cheng et al., 1996; Kossobokov et al., 2000; Rabinovitch et al., 2001; Sornette and Helmstetter, 2002). The neutron starquakes may release strain energies up to <IMG WIDTH='32' HEIGHT='16' ALIGN='BOTTOM' BORDER='0' src='http://www.nonlin-processes-geophys.net/11/137/2004/npg-11-137-img2.gif' ALT='$10^{46}$'>erg, while, the fractures in laboratory samples release strain energies approximately a fraction of an erg. An earthquake fault region can build up strain energy up to approximately <IMG WIDTH='32' HEIGHT='16' ALIGN='BOTTOM' BORDER='0' src='http://www.nonlin-processes-geophys.net/11/137/2004/npg-11-137-img3.gif' ALT='$10^{26}$'>erg for the strongest earthquakes. Clear sequences of kilohertz-megahertz electromagnetic avalanches have been detected from a few days up to a few hours prior to recent destructive earthquakes in Greece. A question that arises effortlessly is if the pre-seismic electromagnetic fluctuations also share the same statistical properties. Our study justifies a positive answer. Our analysis also reveals 'symptoms' of a transition to the main rupture common with earthquake sequences and acoustic emission pulses observed during laboratory experiments (Maes et al., 1998)

A Hierarchical Profiler of Intermediate Representation Code based on LLVM

Profiling based techniques have gained much attention on computer architecture and software analysis communities. The target is to rely on one or more profiling tools in order to identify specific code pieces of interest e.g., code pieces that slowdown a given application. The extracted code pieces can be further modified and optimized. In general, the profiling tools can be classified as deterministic, statistical-based, or rely on hardware performance counters. A common characteristic of the available profiling tools is typically based on analyzing or even manipulating (in case of binary instrumentation tools) machine-level code. This approach come with two main drawbacks. First, a lot of information (even GBytes of data) needs to be gathered, stored, post-processed, and visualized. Second, the performed analysis of the gathered data is platform-specific and it is not straightforward to categorize the given applications/program phases/kernels into distinct categories that have the same or almost the same behavior (e.g., the same percentage of computational vs. control instructions). The latter stems from the fact even small changes in the source code of the applications might lead to significantly different machine code implementations. Therefore, even two specific program kernels exhibit the same behavior (e.g., they have the same number of instructions, but with a different ordering), it is very difficult for a machine-code level profiling tool to assess their similarity, simply because the generated machine level code might have significant differences resulting in many missing opportunities for the available profiling tools. To address this issue, in this paper, we present a new profiling tool that is able to operate on the machine independent intermediate representation (IR) level. The profiler (still in development phase) relies on the LLVM API and it is able to hierarchically (at various levels of the call stack) and recursively parse the IR code and extract various useful statistics. We showcase the practicality of our profiler by analyzing a subset of the PolyBench benchmarks assuming (as pointed out by a recent study) that there is a strong correlation of LLVM IR code

Successful network inference from time-series data using Mutual Information Rate

This work uses an information-based methodology to infer the connectivity of complex systems from observed time-series data. We first derive analytically an expression for the Mutual Information Rate (MIR), namely, the amount of information exchanged per unit of time, that can be used to estimate the MIR between two finite-length low-resolution noisy time-series, and then apply it after a proper normalization for the identification of the connectivity structure of small networks of interacting dynamical systems. In particular, we show that our methodology successfully infers the connectivity for heterogeneous networks, different time-series lengths or coupling strengths, and even in the presence of additive noise. Finally, we show that our methodology based on MIR successfully infers the connectivity of networks composed of nodes with different time-scale dynamics, where inference based on Mutual Information fails

Interplay Between Chaotic and Regular Motion in a Time-Dependent Barred Galaxy Model

We study the distinction and quantification of chaotic and regular motion in a time-dependent Hamiltonian barred galaxy model. Recently, a strong correlation was found between the strength of the bar and the presence of chaotic motion in this system, as models with relatively strong bars were shown to exhibit stronger chaotic behavior compared to those having a weaker bar component. Here, we attempt to further explore this connection by studying the interplay between chaotic and regular behavior of star orbits when the parameters of the model evolve in time. This happens for example when one introduces linear time dependence in the mass parameters of the model to mimic, in some general sense, the effect of self-consistent interactions of the actual N-body problem. We thus observe, in this simple time-dependent model also, that the increase of the bar's mass leads to an increase of the system's chaoticity. We propose a new way of using the Generalized Alignment Index (GALI) method as a reliable criterion to estimate the relative fraction of chaotic vs. regular orbits in such time-dependent potentials, which proves to be much more efficient than the computation of Lyapunov exponents. In particular, GALI is able to capture subtle changes in the nature of an orbit (or ensemble of orbits) even for relatively small time intervals, which makes it ideal for detecting dynamical transitions in time-dependent systems.Comment: 21 pages, 9 figures (minor typos fixed) to appear in J. Phys. A: Math. Theo

Dynamical complexity in the C.elegans neural network

We model the neuronal circuit of the C.elegans soil worm in terms of a Hindmarsh-Rose system of ordinary differential equa- tions, dividing its circuit into six communities which are determined via the Walktrap and Louvain methods. Using the numerical solution of these equations, we analyze important measures of dynamical com- plexity, namely synchronicity, the largest Lyapunov exponent, and the ?AR auto-regressive integrated information theory measure. We show that ?AR provides a useful measure of the information contained in the C.elegans brain dynamic network. Our analysis reveals that the C.elegans brain dynamic network generates more information than the sum of its constituent parts, and that attains higher levels of integrated information for couplings for which either all its communities are highly synchronized, or there is a mixed state of highly synchronized and de- synchronized communities