Number Of CPU Cycles Research Articles

Coal Mine Personnel Safety Monitoring Technology Based on Uncooled Infrared Focal Plane Technology

In an effort to overcome the difficulty of real-time early warning via traditional infrared imaging technology caused by the complex working environment in coal mines, this paper proposes a mine early warning method based on uncooled infrared focal plane technology. The infrared thermal spectrogram of the detected object was visually displayed in a pseudo-color image with high resolution and high sensitivity, which can realize the real-time detection and early warning of personnel safety in modern mines. The multipoint compression correction algorithm based on human visual characteristics divided the response units of all acquisition units into gray intervals according to a threshold value, then the corresponding parameters were set in different intervals, and finally, each interval was compressed using a two-point correction algorithm. The volume of stored data was the sum of the calibration curve and the data from an encode table corrected by a MATLAB simulation, and the number of CPU cycles was run by a CCS 3.3 clock calculation algorithm. The results showed that when the temperature of the blackbody reached 115 °C, the nonuniformity before correction was 6.32%, and the nonuniformity after the multipoint correction of human eyes was 2.99%, which implied that the algorithm proposed in this paper had good denoising ability. The number of CPU cycles occupied by this algorithm was 18,257,363 cycles/frame with a frequency of 29.97 Hz. The sharpness of the compressed infrared images was obviously improved, and the uniformity was better. The method proposed in this paper can meet the need for modern mine personnel search and rescue, equipment supervision and dangerous area detection and other early warning requirements so as to achieve the goal of developing smart mines and ensuring safety in coal mine production.

A Task Offloading Solution for Internet of Vehicles Using Combination Auction Matching Model Based on Mobile Edge Computing

From a global perspective, an Internet of Vehicles task offloading solution based on mobile edge computing is proposed, which satisfies the application requirements (high reliability) strictly. The average time for completing a task can be minimized with the reasonable task offloading solution. Firstly, we model the wireless network, the transmission time and the movement of vehicles. Besides, heterogeneous wireless network architecture is adopted, data centers are deployed at Small-cell Base Stations, Macro-cell Base Stations and Internet. Then considering the limitedness, heterogeneity and task diversity of resources, we utilize matching model based on combination auction to design the offloading model. Furthermore, the multi-round sequential combination auction mechanism is proposed, which equals the matching problem to the multi-dimensional grouping knapsack problem and uses dynamic programming to get the optimal match. This solution is based on virtual machine technology and voltage scaling technology in the task execution time model. Moreover, the computing resources can be measured by CPU frequency. We propose an optimization problem for the shortest average task completion time with limited resources. Finally, the effects of these parameters (such as the number of tasks per unit time, the amount of data offloaded and the number of CPU cycles) on the task execution efficiency are analyzed and compared with other algorithms by simulation experiments. Compared to existing schemes, simulation results show that the proposed algorithm can reduce system overhead and shorten task execution time effectively.

A lightweight IoT‐based security framework for inventory automation using wireless sensor network

SummaryInternet of things (IoT) has evolved as an innovation of next generation in this world of smart devices. IoT tends to provide services for data collection, data management, and data and device security required for application development. Things or devices in IoT communicate and compute to make our lives comfortable and safe. In inventory automation, real‐time check on items, their information management, and status management, monitoring can be carried out using IoT. The huge amount of data that flows among the devices in the network demands for a security framework that ensures authentication, authorization, integrity, and confidentiality of data. The existing security solutions like SIMON or SPECK offer lightweight security solutions but are vulnerable to differential attack because of their simplicity. Moreover, existing solutions do not offer inbuilt authentication. Therefore, this research work contributes a secure and lightweight IoT‐based framework using wireless sensor network (WSN) as a technology. The existing security solutions SPECK and SIMON are compared with the proposed security approach using COOJA simulator. The results show that proposed approach outstands others by 2% reduction in number of CPU cycles, 10% less execution time, 4% less memory requirements of security approach, and with minimum 10% more security impact.

Energy Consumption in Compact Integer Vectors: A Study Case

In the field of algorithms and data structures analysis and design, most of the researchers focus only on the space/time trade-off, and little attention has been paid to energy consumption. Moreover, most of the efforts in the field of Green Computing have been devoted to hardware-related issues, being green software in its infancy. Optimizing the usage of computing resources, minimizing power consumption or increasing battery life are some of the goals of this field of research. As an attempt to address the most recent sustainability challenges, we must incorporate the energy consumption as a first-class constraint when designing new compact data structures. Thus, as a preliminary work to reach that goal, we first need to understand the factors that impact on the energy consumption and their relation with compression. In this work, we study the energy consumption required by several integer vector representations. We execute typical operations over datasets of different nature. We can see that, as commonly believed, energy consumption is highly related to the time required by the process, but not always. We analyze other parameters, such as number of instructions, number of CPU cycles, memory loads, among others.

A Multi-Dimensional approach towards Intrusion Detection System

this paper, we suggest a multi-dimensional approach towards intrusion detection. Network and system usage parameters like source and destination IP addresses; source and destination ports; incoming and outgoing network traffic data rate and number of CPU cycles per request are divided into multiple dimensions. Rather than analyzing raw bytes of data corresponding to the values of the network parameters, a mature function is inferred during the training phase for each dimension. This mature function takes a dimension value as an input and returns a value that represents the level of abnormality in the system usage with respect to that dimension. This mature function is referred to as Individual Anomaly Indicator. Individual Anomaly Indicators recorded for each of the dimensions are then used to generate a Global Anomaly Indicator, a function with n variables (n is the number of dimensions) that provides the Global Anomaly Factor, an indicator of anomaly in the system usage based on all the dimensions considered together. The Global Anomaly Indicator inferred during the training phase is then used to detect anomaly in the network traffic during the detection phase. Network traffic data encountered during the detection phase is fed back to the system to improve the maturity of the Individual Anomaly Indicators and hence the Global Anomaly Indicator.

Mécanismes de traces efficaces pour programmes multithreadés

Nowadays, observing and understanding the performance of a multithreaded application is untrivial, especially within a complex thread environment (multilevel scheduling). Thanks to our environment, the run of a multithreaded application can be precisely analyzed. In particular, our environment allows the programmer to measure the number of CPU cycles used by a given function or the precise scheduling of the threads of the application.