Analysis by reduction is a method used in linguistics for checking the correctness of sentences of natural languages. This method is modelled by restarting automata. Here we introduce and study a new type of restarting automaton, the socalled t-sRL-automaton, which is an RL-automaton that is rather restricted in that it has a window of size 1 only, and that it works under a minimal acceptance c...

This paper demonstrates the performance gain of MIGSOCK over Zap, an user-level approach to network process checkpointing and restarting. We consider two scenarios where process checkpointing and restarting could take place. In the first scenario, where processes are aggregated in one PrOcess Domain (pod), it takes Netfilter three times as much time as MIGSOCK to handle translation and forwardi...

The performance of Krylov subspace eigenvalue algorithms for large matrices can be measured by the angle between a desired invariant subspace and the Krylov subspace. We develop general bounds for this convergence that include the effects of polynomial restarting and impose no restrictions concerning the diagonalizability of the matrix or its degree of nonnormality. Associated with a desired se...

The escape of the randomly accelerated undamped particle from finite interval under action stochastic resetting is studied. motion such a described by full Langevin equation and characterized position velocity. We compare three protocols, which restarts velocity or (partial resetting) whole (position -- resetting). Using mean first passage time we assess efficiency restarting protocols in facil...

In this article, I review past, current, and future advances on the study of radio-loud AGN (RLAGN; quasars radio galaxies) lifecycles exclusively in remnant restarting phases. focus their dynamics energetics as inferred from observations while discussing radiative lifetimes, population statistics, trends physical characteristics. briefly summarize multi-wavelength observations, particularly X-...

Backtrack-style exhaustive search algorithms for NP-hard problems tend to have large variance in their runtime. This is because “fortunate” branching decisions can lead to finding a solution quickly, whereas “unfortunate” decisions in another run can lead the algorithm to a region of the search space with no solutions. In the literature, frequent restarting has been suggested as a means to over...

The leapfrog method is popular because of its good stability when solving partial differential equations with oscillatory solutions. “It has the disadvantage that the solution at odd time steps tends to drift farther and farther from the solution for even time steps, so it is common to stop the integration every twenty time steps or so and reinitialize with the first order forward Euler method ...