scholarly journals Analysis of Energy Consumption and Optimization Techniques for Writing Energy-Efficient Code

Electronics ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 1192 ◽  
Author(s):  
Javier Corral-García ◽  
Felipe Lemus-Prieto ◽  
José-Luis González-Sánchez and Miguel-Ángel Pérez-Toledano
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Optimization Techniques ◽  
Raspberry Pi ◽  
Software Systems ◽  
Major Subject ◽  
Efficient Code ◽  
Reduction Of Energy Consumption ◽  
The Internet Of Things

The unprecedented growth of connected devices, together with the remarkable convergence of a wide variety of technologies, have led to an exponential increase in the services that the internet of things (IoT) can offer, all aimed at improving quality of life. Consequently, in order to meet the numerous challenges this produces, the IoT has become a major subject of research. One of these challenges is the reduction of energy consumption given the significant limitations of some devices. In addition, although the search for energy efficiency was initially focused on hardware, it has become a concern for software developers too. In fact, it has become an intense area of research with the principal objective of analyzing and optimizing the energy consumption of software systems. This research analyzes the energy saving that can be achieved when using a broad set of techniques for writing energy-efficient code for Raspberry Pi devices. It also demonstrates that programmers can save more energy if they apply the proposed techniques manually than when relying on other automatic optimization options offered by the GNU compiler collection (GCC). Thus, it is important that programmers are aware of the significant impact these techniques can have on an application’s energy consumption.

scholarly journals Evaluation of Strategies for the Development of Efficient Code for Raspberry Pi Devices

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 4066 ◽  
Author(s):  
Javier Corral-García ◽  
José-Luis González-Sánchez ◽  
Miguel-Ángel Pérez-Toledano
Keyword(s):  
Energy Efficient ◽  
Focal Point ◽  
Raspberry Pi ◽  
Code Optimization ◽  
Execution Speed ◽  
Efficient Code ◽  
Complete Set ◽  
Iot Devices ◽  
Processor Efficiency ◽  
The Internet Of Things

The Internet of Things (IoT) is faced with challenges that require green solutions and energy-efficient paradigms. Architectures (such as ARM) have evolved significantly in recent years, with improvements to processor efficiency, essential for always-on devices, as a focal point. However, as far as software is concerned, few approaches analyse the advantages of writing efficient code when programming IoT devices. Therefore, this proposal aims to improve source code optimization to achieve better execution times. In addition, the importance of various techniques for writing efficient code for Raspberry Pi devices is analysed, with the objective of increasing execution speed. A complete set of tests have been developed exclusively for analysing and measuring the improvements achieved when applying each of these techniques. This will raise awareness of the significant impact the recommended techniques can have.

scholarly journals Review: Reduction of energy consumption in TMP refining through mechanical pre-treatment of wood chips

2010 ◽  
Vol 25 (2) ◽  
pp. 156-161 ◽  
Author(s):  
Dmitri Gorski ◽  
Jan Hill ◽  
Per Engstrand ◽  
Lars Johansson
Keyword(s):  
Energy Consumption ◽  
Pilot Scale ◽  
High Ratio ◽  
Wood Chips ◽  
Chip Size ◽  
Weak Points ◽  
Pulp Properties ◽  
Pre Treatment ◽  
Reduction Of Energy Consumption

Abstract This review covers the effect of mechanical pre-treatment of wood chips on the energy consumption in refining and the quality of pulp. To understand the mechanisms of mechanical pre-treatment, a short description of relevant refining theory and reported effects of pre-treatment on wood morphology is given. Mechanical pre-treatment offers a chance to utilize the energy needed to defibrate chips in a more efficient way, minimizing the cyclic elastic deformations which are the main defibration mechanism in refining. Studies of fibre morphology indicate that compressive pretreatment mechanically introduces favorable weak points in the S1 and S2 fibre walls where defibration proceeds easier upon subsequent refining. Published results which cover the effect of the pretreatment on energy consumption and pulp properties are reviewed. Energy reduction of between 10% and 30% is reported in the literature. High ratio of volumetric compression is necessary. Pressurized conditions are required to ensure that the fibres are not damaged during the pre-treatment. Other effects of compressive pretreatment include a more uniform chip size and moisture content, better penetration of chemicals and removal of extractives from the chips. A list of equipment used for chip pre-compression is provided together with published results of pilot-scale and mill-scale operation.

scholarly journals A Novel Energy Efficient Resource Management System in Cloud Computing Environment.

2018 ◽  
Vol 7 (4.19) ◽  
pp. 1030
Author(s):  
S. K. Sonkar ◽  
M. U.Kharat
Keyword(s):  
Resource Allocation ◽  
Energy Consumption ◽  
Resource Management ◽  
Virtual Machine ◽  
Energy Efficient ◽  
Service Providers ◽  
Optimization Techniques ◽  
Cloud Provider ◽  
Efficient Resource ◽  
Machine Allocation

Primary target of cloud provider is to provide the maximum resource utilization and increase the revenue by reducing energy consumption and operative cost. In the service providers point of view, resource allocation, resource sharing, migration of resources on demand, memory management, storage management, load balancing, energy efficient resource usage, computational complexity handling in virtualization are some of the major tasks that has to be dealt with. The major issue focused in this paper is to reduce the energy consumption problem and management of computation capacity utilization.  For the same, an energy efficient resource management method is proposed to grip the resource scheduling and to minimize the energy utilized by the cloud datacenters for the computational work. Here a novel resource allocation mechanism is proposed, based on the optimization techniques. Also a novel dynamic virtual machine (VM) allocation method is suggested to help dynamic virtual machine allocation and job rescheduling to improve the consolidation of resources to execute the jobs. Experimental results indicated that proposed strategy outperforms as compared to the existing systems.  

A Location Based Energy Proficient Path Routing for Internet of Things and Its Applications

2020 ◽  
pp. 6-10
Author(s):  
Arulanantham D ◽  
Pradeepkumar G ◽  
Palanisamy C ◽  
Dineshkumar Ponnusamy
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Network Architecture ◽  
Base Station ◽  
Consumer Electronics ◽  
The Internet ◽  
Energy Efficient Routing ◽  
The Internet Of Things

The Internet of Things (IoT) is an establishment with sensors, base station, gateway, and network servers. IoT is an efficient and intellectual system that minimizes human exertion as well as right to use to real devices. This method also has an autonomous control property by which any device can control without any human collaboration. IoT-based automation has become very reasonable and it has been applied in several sectors such as manufacturing, transport, health care, consumer electronics, etc. In WSN’s smaller energy consumption sensors are expected to run independently for long phases. So much ongoing researches on implementing routing protocols for IoTbased WSNs.Energy consciousness is an essential part of IoT based WSN design issue. Minimalizing Energy consumption is well-thought-out as one of the key principles in the Expansion of routing protocols for the Internet of things. In this paper, we propose a Location based Energy efficient path routing for Internet of things and its applications its sensor position and clustering based finding the shortest path and real time implementation of Arduino based wireless sensor network architecture with the ESP8266 module. Finally, analyze the principles of Location-based energy-efficient routing and performance of QoS parameters, and then implemented automatic gas leakage detection and managing system.

scholarly journals Fireflies Ant Optimized Reliable Quality Awareness Energy Efficient Routing Protocol for Managing Quality of Medical Data in Wireless Body Networks

2019 ◽  
Vol 9 (1) ◽  
pp. 5007-5012
Keyword(s):  
Energy Consumption ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Medical Data ◽  
Energy Efficient Routing ◽  
Packet Delivery ◽  
End To End Delay ◽  
End To End ◽  
Quality Awareness

The wireless body area network is one of effective wearable devices that have been used in medical applications for collecting patient information to providing the treatment incorrect time for avoiding seriousness. The collected data’s such as blood pressure, air flow, temperature, electromagnetic information is transmitted to the health care center via the wireless technology, which reduces the difficulties also helps to provide the immediate treatment. During the information transmission, the main issues are Quality of Service (QoS), low packet delivery, high energy consumption and end to end delay. So, in this paper introduces the Fireflies Ant Optimized, Reliable Quality Awareness, Energy Efficient Routing Protocol ((FAORQEER) for maintaining the quality of the recorded medical data. The network examines the optimal path by using the characteristics of fireflies and the network life time and energy of the network is managed by introducing an energy efficient method. The process then evaluates efficiency with test results about energy consumption, packet delivery ratio, end to end delay and QoS metric associated constraints.

scholarly journals Energy Efficiency Optimization of Cognitive UAV-Assisted Edge Communication for Semantic Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yilong Gu ◽  
Yangchao Huang ◽  
Hang Hu ◽  
Weiting Gao ◽  
Yu Pan
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Energy Efficient ◽  
Optimization Problem ◽  
Optimization Scheme ◽  
Battery Capacity ◽  
Aerial Vehicle ◽  
Efficient Alternative ◽  
The Internet Of Things

With the consolidation of the Internet of Things (IoT), the unmanned aerial vehicle- (UAV-) based IoT has attracted much attention in recent years. In the IoT, cognitive UAV can not only overcome the problem of spectrum scarcity but also improve the communication quality of the edge nodes. However, due to the generation of massive and redundant IoT data, it is difficult to realize the mutual understanding between UAV and ground nodes. At the same time, the performance of the UAV is severely limited by its battery capacity. In order to form an autonomous and energy-efficient IoT system, we investigate semantically driven cognitive UAV networks to maximize the energy efficiency (EE). The semantic device model for cognitive UAV-assisted IoT communication is constructed. And the sensing time, the flight speed of UAV, and the coverage range of UAV communication are jointly optimized to maximize the EE. Then, an efficient alternative algorithm is proposed to solve the optimization problem. Finally, we provide computer simulations to validate the proposed algorithm. The performance of the joint optimization scheme based on the proposed algorithm is compared to some benchmark schemes. And the simulation results show that the proposed scheme can obtain the optimal system parameters and can significantly improve the EE.

scholarly journals E2-MACH: Energy efficient multi-attribute based clustering scheme for energy harvesting wireless sensor networks

2020 ◽  
Vol 16 (10) ◽  
pp. 155014772096804
Author(s):  
Inam Ul Haq ◽  
Qaisar Javaid ◽  
Zahid Ullah ◽  
Zafar Zaheer ◽  
Mohsin Raza ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Internet Of Things ◽  
Packet Loss ◽  
Energy Efficient ◽  
Cluster Head ◽  
Wireless Sensor

Internet of things have emerged enough due to its applications in a wide range of fields such as governance, industry, healthcare, and smart environments (home, smart, cities, and so on). Internet of things–based networks connect smart devices ubiquitously. In such scenario, the role of wireless sensor networks becomes vital in order to enhance the ubiquity of the Internet of things devices with lower cost and easy deployment. The sensor nodes are limited in terms of energy storage, processing, and data storage capabilities, while their radio frequencies are very sensitive to noise and interference. These factors consequently threaten the energy consumption, lifetime, and throughput of network. One way to cope with energy consumption issue is energy harvesting techniques used in wireless sensor network–based Internet of things. However, some recent studies addressed the problems of clustering and routing in energy harvesting wireless sensor networks which either concentrate on energy efficiency or quality of service. There is a need of an adequate approach that can perform efficiently in terms of energy utilization as well as to ensure the quality of service. In this article, a novel protocol named energy-efficient multi-attribute-based clustering scheme (E2-MACH) is proposed which addresses the energy efficiency and communication reliability. It uses selection criteria of reliable cluster head based on a weighted function defined by multiple attributes such as link statistics, neighborhood density, current residual energy, and the rate of energy harvesting of nodes. The consideration of such parameters in cluster head selection helps to preserve the node’s energy and reduce its consumption by sending data over links possessing better signal-to-noise ratio and hence ensure minimum packet loss. The minimized packet loss ratio contributes toward enhanced network throughput, energy consumption, and lifetime with better service availability for Internet of things applications. A set of experiments using network simulator 2 revealed that our proposed approach outperforms the state-of-the-art low-energy adaptive clustering hierarchy and other recent protocols in terms of first-node death, overall energy consumption, and network throughput.

scholarly journals Optimizing Hybrid Metaheuristic Algorithm with Cluster Head to Improve Performance Metrics on the IoT

2021 ◽  
Author(s):  
Malik bader alazzam ◽  
Fawaz Alassery
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Smart Grids ◽  
Weather Prediction ◽  
Cluster Head ◽  
Optimization Techniques ◽  
The Internet ◽  
Wide Range ◽  
Whale Optimization ◽  
The Internet Of Things

Abstract The Internet of Things (IoT) has subsequently been applied to a variety of sectors, including smart grids, farming, weather prediction, power generation, wastewater treatment, and so on. So if the Internet of Things has enormous promise in a wide range of applications, there still are certain areas where it may be improved. Designers had focused our present research on reducing the energy consumption of devices in IoT networks, which will result in a longer network lifetime. The far more suitable Cluster Head (CH) throughout the IoT system is determined in this study to optimize energy consumption. Whale Optimization Algorithm (WOA) with Evolutionary Algorithm (EA) is indeed a mixed meta-heuristic algorithm used during the suggested study. Various quantifiable metrics, including the variety of adult nodes, workload, temperatures, remaining energy, and a target value, were utilized IoT network groups. The suggested method then is contrasted to several cutting-edge optimization techniques, including the Artificial Bee Colony method, Neural Network, Adapted Gravity Simulated annealing. The findings show that the suggested hybrid method outperforms conventional methods.

scholarly journals Design of a Traffic-Aware Governor for Green Routers

2014 ◽  
Vol 2014 ◽  
pp. 1-12
Author(s):  
Alfio Lombardo ◽  
Vincenzo Riccobene ◽  
Giovanni Schembra
Keyword(s):  
Quality Of Service ◽  
Energy Consumption ◽  
Energy Saving ◽  
Analytical Model ◽  
Case Scenario ◽  
Proposed Model ◽  
Traffic Impacts ◽  
Reduction Of Energy Consumption

Today the reduction of energy consumption in telecommunications networks is one of the main goals to be pursued by manufacturers and researchers. In this context, the paper focuses on routers that achieve energy saving by applying the frequency scaling approach. The target is to propose an analytical model to support designers in choosing the main configuration parameters of the Router Governor in order to meet Quality of Service (QoS) requirements while maximizing energy saving gain. More specifically, the model is used to evaluate the input traffic impacts on the choice of the active router clock frequencies and on the overall green router performance. A case study based on the open NetFPGA reference router is considered to show how the proposed model can be easily applied to a real case scenario.

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