scholarly journals The influence of random delays on parallel execution times

1993 ◽  
Author(s):  
Vikram S. Adve ◽  
Mary K. Vernon
Keyword(s):  
Parallel Execution ◽  
Random Delays ◽  
Execution Times

FUNCTIONAL COORDINATION OF METHODS OF ORGANIZATION OF ADAPTIVE DATA COLLECTION PROCESSES AND METHODS OF SPATIAL SELF-ORGANIZATION OF MOBILE AGENTS

2017 ◽  
Vol 2 (1) ◽  
pp. 27-32
Author(s):  
Botchkaryov. A. ◽  
Keyword(s):  
Data Collection ◽  
Key Words ◽  
Motion Control ◽  
Mobile Agent ◽  
Mobile Agents ◽  
Parallel Execution ◽  
Self Organization ◽  
Data Collection Process ◽  
Speed Up ◽  
Adaptive Data Collection

The way of functional coordination of methods of organization adaptive data collection processes and methods of spatial self-organization of mobile agents by parallel execution of the corresponding data collection processes and the process of motion control of a mobile agent using the proposed protocol of their interaction and the algorithm of parallel execution planning is proposed. The method allows to speed up the calculations in the decision block of the mobile agent by an average of 40.6%. Key words: functional coordination, adaptive data collection process, spatial self-organization, mobile agents

Exponential stability of impulsive systems with random delays under sampled-data control

2017 ◽  
Vol 11 (16) ◽  
pp. 2834-2847 ◽  
Author(s):  
Kuppusamy Subramanian ◽  
Palanisamy Muthukumar ◽  
Quanxin Zhu
Keyword(s):  
Exponential Stability ◽  
Sampled Data ◽  
Impulsive Systems ◽  
Random Delays ◽  
Data Control ◽  
Sampled Data Control

FORESEE: An Effective and Efficient Framework for Estimating the Execution Times of IO Traces on the SSD

2020 ◽  
pp. 1-1
Author(s):  
Yoonsuk Kang ◽  
Yong-Yeon Jo ◽  
Jaehyuk Cha ◽  
Wan D. Bae ◽  
Wonjun Lee ◽  
...  
Keyword(s):  
Execution Times

scholarly journals New general mixed-integer linear programming model for mobile workforce management

2021 ◽  
Author(s):  
András Éles ◽  
István Heckl ◽  
Heriberto Cabezas
Keyword(s):  
Programming Model ◽  
Time Windows ◽  
Mutual Exclusion ◽  
Parallel Execution ◽  
Mixed Integer ◽  
Management Problem ◽  
Routing Problem ◽  
Workforce Management ◽  
Computational Performance ◽  
Wide Range

AbstractA mathematical model is introduced to solve a mobile workforce management problem. In such a problem there are a number of tasks to be executed at different locations by various teams. For example, when an electricity utility company has to deal with planned system upgrades and damages caused by storms. The aim is to determine the schedule of the teams in such a way that the overall cost is minimal. The mobile workforce management problem involves scheduling. The following questions should be answered: when to perform a task, how to route vehicles—the vehicle routing problem—and the order the sites should be visited and by which teams. These problems are already complex in themselves. This paper proposes an integrated mathematical programming model formulation, which, by the assignment of its binary variables, can be easily included in heuristic algorithmic frameworks. In the problem specification, a wide range of parameters can be set. This includes absolute and expected time windows for tasks, packing and unpacking in case of team movement, resource utilization, relations between tasks such as precedence, mutual exclusion or parallel execution, and team-dependent travelling and execution times and costs. To make the model able to solve larger problems, an algorithmic framework is also implemented which can be used to find heuristic solutions in acceptable time. This latter solution method can be used as an alternative. Computational performance is examined through a series of test cases in which the most important factors are scaled.

scholarly journals Timing attacks and local timing attacks against Barrett’s modular multiplication algorithm

2021 ◽  
Author(s):  
Johannes Mittmann ◽  
Werner Schindler
Keyword(s):  
Side Channel ◽  
Modular Exponentiation ◽  
Modular Multiplication ◽  
Multiplication Algorithm ◽  
Diffie Hellman ◽  
Mathematical Difficulties ◽  
Execution Times ◽  
Stochastic Properties ◽  
Timing Attacks ◽  
Theoretical Results

AbstractMontgomery’s and Barrett’s modular multiplication algorithms are widely used in modular exponentiation algorithms, e.g. to compute RSA or ECC operations. While Montgomery’s multiplication algorithm has been studied extensively in the literature and many side-channel attacks have been detected, to our best knowledge no thorough analysis exists for Barrett’s multiplication algorithm. This article closes this gap. For both Montgomery’s and Barrett’s multiplication algorithm, differences of the execution times are caused by conditional integer subtractions, so-called extra reductions. Barrett’s multiplication algorithm allows even two extra reductions, and this feature increases the mathematical difficulties significantly. We formulate and analyse a two-dimensional Markov process, from which we deduce relevant stochastic properties of Barrett’s multiplication algorithm within modular exponentiation algorithms. This allows to transfer the timing attacks and local timing attacks (where a second side-channel attack exhibits the execution times of the particular modular squarings and multiplications) on Montgomery’s multiplication algorithm to attacks on Barrett’s algorithm. However, there are also differences. Barrett’s multiplication algorithm requires additional attack substeps, and the attack efficiency is much more sensitive to variations of the parameters. We treat timing attacks on RSA with CRT, on RSA without CRT, and on Diffie–Hellman, as well as local timing attacks against these algorithms in the presence of basis blinding. Experiments confirm our theoretical results.

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