Parallelization of Finding the Current Coordinates of the Lidar Based on the Genetic Algorithm and OpenMP Technology

The problem of determining the position of the lidar with optimal accuracy is relevant in various fields of application. This is an important task of robotics that is widely used as a model when planning the route of vehicles, flight control systems, navigation systems, machine learning, and managing economic efficiency, a study of land degradation processes, planning and control of agricultural production stages, land inventory to evaluations of the consequences of various environmental impacts. The paper provides a detailed analysis of the proposed parallelization algorithm for solving the problem of determining the current position of the lidar. To optimize the computing process in order to accelerate and have the possibility of obtaining a real-time result, the OpenMP parallel computing technology is used. It is also possible to significantly reduce the computational complexity of the successive variant. A number of numerical experiments on the multi-core architecture of modern computers have been carried out. As a result, it was possible to accelerate the computing process about eight times and achieve an efficiency of 0.97. It is shown that a special difference in time of execution of a sequential and parallel algorithm manages to increase the number of measurements of lidar and iterations, which is relevant in simulating various problems of robotics. The obtained results can be substantially improved by selecting a computing system where the number of cores is more than eight. The main areas of application of the developed method are described, its shortcomings and prospects for further research are provided.

Novel Dynamic Scaling (NDS) Algorithm to Balance Energy Level in Eiot For Efficient Cloud Computing Process

The cloud computing is very efficient platform for storing and processing huge data applications. IoT, Edge computing models helps the cloud infrastructure for processing data with less network latencies, efficient data processing with minimum energy consumption for better infrastructure. More researches on cloud computing process makes them matured in providing best services to the users. Also IT services on cloud have developed rapidly. The different cloud services have different energy level with is memory, processing speed, bandwidth and system capability. The users have different data and requirements to process their job. Process of finding the best resources with less energy consumption is main goal of our proposed article. The edge devices, IoT devices first focused to help cloud architecture. Edge and IoT are promising supportive technology to address the NP hard problems like less latency and consume less energy during data transfer. However, when the information and data are increasing in cloud, it’s very difficult to solve the energy consumption problem in heterogeneous cloud infrastructure. In our proposed work edge server clouds and central server clouds works collaboratively for reducing the energy consumption. in this article we implemented the novel dynamic speed (NDS) scaling algorithm . This NDS algorithm computes the workload of CPU for particular data application. The speed processor scaling is a methodology used for consuming less energy and gaining less rates. if processing speed is high then energy consumption will be higher vise versa if processing speed is low then energy consumption will be less. This ideology is developed using NDS algorithm in edge cloud devices to compute data using less energy. The proposed algorithm is compared with existing energy saving algorithms and its efficiency is better than other algorithms is evaluated.

Enhancing Mobile Agent Security Level (Proposed Model)

Mobile agents are application design schemes for distributed systems that consist of mobile code ideology including Mobile agent software. In the last period mobile computing process had a vision that’s a set of execution code that’s move from platform to another in the heterogeneous network with an ability of carrying there result and updating them self-sate. This paper presents several enhancements on mobile agent security and provides generalized code protection. Several novel techniques are proposed to protect mobile agents in any environments and to describe and solve practical problems in the mobile agent system.

Evaluation of a Cyber-Physical Computing System with Migration of Virtual Machines during Continuous Computing

The Markov model of reliability of a failover cluster performing calculations in a cyber-physical system is considered. The continuity of the cluster computing process in the event of a failure of the physical resources of the servers is provided on the basis of virtualization technology and is associated with the migration of virtual machines. The difference in the proposed model is that it considers the restrictions on the allowable time of interruption of the computational process during cluster recovery. This limitation is due to the fact that, if two physical servers fail, then object management is lost, which is unacceptable. Failure occurs if their recovery time is longer than the maximum allowable time of interruption of the computing process. The modes of operation of the cluster with and without system recovery in the event of a failure of part of the system resources that do not lead to loss of continuity of the computing process are considered. The results of the article are aimed at the possibility of assessing the probability of cluster operability while supporting the continuity of computations and its running to failure, leading to the interruption of the computational (control) process beyond the maximum permissible time. As a result of the calculation example for the presented models, it was shown that the mean time to failure during recovery under conditions of supporting the continuity of the computing process increases by more than two orders of magnitude.

Development of a technique for modeling entangled quantum computations that are applicable in Simon’s quantum algorithm

This paper describes the basics of developing quantum algorithms and modeling entangled quantum computations applicable in quantum algorithms. Quantum algorithms involve the use of vector and matrix algebra. The basic tasks of the simulation proposed in the work are determined within the framework of the algorithm for executing quantum algorithms, taking into account entanglement. A technique has been developed for modeling entangled quantum calculations applicable in the Simon quantum algorithm, which helps to predict the behavior of the quantum algorithm (or any other computing process that proceeds as part of the work of a quantum computer system) with partial entanglement.