The Execution Time Overhead of Entering and Exiting Scoped Memory in Real-Time Java Applications

2011 ◽  
pp. 545-556
Keyword(s):  
Real Time ◽  
Execution Time ◽  
Time Overhead

scholarly journals Indoor Path-Planning Algorithm for UAV-Based Contact Inspection

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 642
Author(s):  
Luis Miguel González de Santos ◽  
Ernesto Frías Nores ◽  
Joaquín Martínez Sánchez ◽  
Higinio González Jorge
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Execution Time ◽  
Point Cloud ◽  
Indoor Environments ◽  
Calculation Algorithm ◽  
Time Restrictions ◽  
Planning Algorithm ◽  
Inspection Tasks ◽  
Path Planning Algorithm

Nowadays, unmanned aerial vehicles (UAVs) are extensively used for multiple purposes, such as infrastructure inspections or surveillance. This paper presents a real-time path planning algorithm in indoor environments designed to perform contact inspection tasks using UAVs. The only input used by this algorithm is the point cloud of the building where the UAV is going to navigate. The algorithm is divided into two main parts. The first one is the pre-processing algorithm that processes the point cloud, segmenting it into rooms and discretizing each room. The second part is the path planning algorithm that has to be executed in real time. In this way, all the computational load is in the first step, which is pre-processed, making the path calculation algorithm faster. The method has been tested in different buildings, measuring the execution time for different paths calculations. As can be seen in the results section, the developed algorithm is able to calculate a new path in 8–9 milliseconds. The developed algorithm fulfils the execution time restrictions, and it has proven to be reliable for route calculation.

Calculating the maximum execution time of real-time programs

1989 ◽  
Vol 1 (2) ◽  
pp. 159-176 ◽  
Author(s):  
P. Puschner ◽  
Ch. Koza
Keyword(s):  
Real Time ◽  
Execution Time

PARALLEL HYBRID METAHEURISTIC ON SHARED MEMORY SYSTEM FOR REAL-TIME UAV PATH PLANNING

2014 ◽  
Vol 13 (02) ◽  
pp. 1450008 ◽  
Author(s):  
VINCENT ROBERGE ◽  
MOHAMMED TARBOUCHI ◽  
FRANÇOIS ALLAIRE
Keyword(s):  
Real Time ◽  
Shared Memory ◽  
Execution Time ◽  
Hybrid Algorithm ◽  
Statistical Significance ◽  
Optimization Methods ◽  
Memory System ◽  
Hybrid Metaheuristic ◽  
Parallel Hybrid ◽  
Shared Memory System

In this paper, we present a parallel hybrid metaheuristic that combines the strengths of the particle swarm optimization (PSO) and the genetic algorithm (GA) to produce an improved path-planner algorithm for fixed wing unmanned aerial vehicles (UAVs). The proposed solution uses a multi-objective cost function we developed and generates in real-time feasible and quasi-optimal trajectories in complex 3D environments. Our parallel hybrid algorithm simulates multiple GA populations and PSO swarms in parallel while allowing migration of solutions. This collaboration between the GA and the PSO leads to an algorithm that exhibits the strengths of both optimization methods and produces superior solutions. Moreover, by using the "single-program, multiple-data" parallel programming paradigm, we maximize the use of today's multicore CPU and significantly reduce the execution time of the parallel program compared to a sequential implementation. We observed a quasi-linear speedup of 10.7 times faster on a 12-core shared memory system resulting in an execution time of 5 s which allows in-flight planning. Finally, we show with statistical significance that our parallel hybrid algorithm produces superior trajectories to the parallel GA or the parallel PSO we previously developed.

scholarly journals AN INTELLIGENT SCHEDULER APPROACH TO MULTIPROCESSOR SCHEDULING OF APERIODIC TASKS

2012 ◽  
pp. 42-46
Author(s):  
INDURAJ. P. R
Keyword(s):  
Real Time ◽  
Prior Knowledge ◽  
Resource Availability ◽  
Execution Time ◽  
Arrival Time ◽  
Multiprocessor Scheduling ◽  
Multiprocessor System ◽  
Aperiodic Tasks

This paper presents a new scheduler capable of scheduling aperiodic tasks at real time in multiprocessor system. The algorithm proposes a new way to determine dynamically tasks of high priority and low priority finding the elapsed execution time and remaining execution time, and the amount of resource availability and deadline of task, with no prior knowledge of task arrival time and also ensures that no processor remains ideal thus utilizing processors at all times.

Use of Measurements in Worst-Case Execution Time Estimation for Real-Time Systems

2021 ◽  
Author(s):  
Jessica Junia Santillo Costa ◽  
Romulo Silva de Oliveira ◽  
Luis Fernando Arcaro
Keyword(s):  
Real Time ◽  
Execution Time ◽  
Time Estimation ◽  
Real Time Systems ◽  
Worst Case ◽  
Worst Case Execution Time ◽  
Time Systems

Implementing and using execution time clocks in Ada hard real-time applications

1998 ◽  
pp. 90-101 ◽  
Author(s):  
M. González Harbour ◽  
M. Aldea Rivas ◽  
J. J. Gutiérrez García ◽  
J. C. Palencia Gutiérrez
Keyword(s):  
Real Time ◽  
Execution Time ◽  
Real Time Applications ◽  
Hard Real Time

A Novel Approach in Scheduling Of the Real- Time Tasks In Heterogeneous Multicore Processor with Fuzzy Logic Technique For Micro-grid Power Management

2018 ◽  
Vol 9 (1) ◽  
pp. 80
Author(s):  
Lavanya Dhanesh ◽  
P. Murugesan
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Power Management ◽  
Execution Time ◽  
High Performance ◽  
Scheduling Algorithm ◽  
Multicore Processor ◽  
Heterogeneous Multicore ◽  
Micro Grid ◽  
Low Performance

Scheduling of tasks based on real time requirement is a major issue in the heterogeneous multicore systemsfor micro-grid power management . Heterogeneous multicore processor schedules the serial tasks in the high performance core and parallel tasks are executed on the low performance cores. The aim of this paper is to implement a scheduling algorithm based on fuzzy logic for heterogeneous multicore processor for effective micro-grid application. Real – time tasks generally have different execution time and dead line. The main idea is to use two fuzzy logic based scheduling algorithm, first is to assign priority based on execution time and deadline of the task. Second , the task which has assigned higher priority get allotted for execution in high performance core and remaining tasks which are assigned low priority get allotted in low performance cores. The main objective of this scheduling algorithm is to increase the throughput and to improve CPU utilization there by reducing the overall power consumption of the micro-grid power management systems. Test cases with different task execution time and deadline were generated to evaluate the algorithms using  MATLAB software.

scholarly journals A theory for execution-time derivation in real-time programs

2005 ◽  
Vol 346 (1) ◽  
pp. 3-27 ◽  
Author(s):  
Karl Lermer ◽  
Colin J. Fidge ◽  
Ian J. Hayes
Keyword(s):  
Real Time ◽  
Execution Time
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