Efficient Resources Allocation and Energy Reduction with Virtual Machines for Cloud Computing

Cloud computing is an internet provisioned method for sharing the resources on demand by network management, storage, services, applications and the serves that necessitate management optimal effort. VMM (virtual machine migration) plays a major role in enhancing the resource utilization, application isolation, processing nodes, fault tolerance in VMs for enhancing nodes portability and for maximizing the efficiency of physical server. For balancing the clouds with resources for the enhanced performance, varied users are served with application deployment in the cloud environment is considered as the major task. The user can rent or request the resources when it becomes significant. The emphasis of this paper is on different energy VM energy efficient module as per machine learning methods. While allocating the VMs to the host machines, MBFD (Modified Best Fit Decreasing) is considered and the classification of host machine capability such as overloaded, normal loaded and underloaded is executed according to SVM (Support vector machine). SVM is utilized as a classifier for analyzing the MBFD algorithm and for the classification of the host as per the job properties. In this procedure, the numbers of jobs that are not allocated are examined via simulation which is computed by means of time consumption, energy consumption and a total number of migrations.

Two-Hop Energy Consumption Balanced Routing Algorithm for Solar Insecticidal Lamp Internet of Things

Due to the sparsity deployment of nodes, the full connection requirement, and the unpredictable electromagnetic interference on communication caused by high voltage pulse current of Solar Insecticidal Lamps Internet of Things (SIL-IoTs), a Two-Hop Energy Consumption Balanced routing algorithm (THECB) is proposed in this research work. THECB selects next-hop nodes according to 1-hop and 2-hop neighbors’ information. In addition, the greedy forwarding mechanism is expressed in the form of probability; that is, each neighbor node is given a weight between 0 and 1 according to the distance. THECB reduces the data forwarding traffic of nodes whose discharge numbers are relatively higher than those of other nodes so that the unpredictable electromagnetic interference on communication can be weakened. We compare the energy consumption, energy consumption balance, and data forwarding traffic over various discharge numbers, network densities, and transmission radius. The results indicate that THECB achieves better performance than Two-Phase Geographic Greedy Forwarding plus (TPGFPlus), which ignores the requirement of the node-disjoint path.

Approximation Algorithm for Scheduling a Chain of Tasks for Motion Estimation on Heterogeneous Systems MPSoC

Co-design embedded system are very important step in digital vehicle and airplane. The multicore and multiprocessor SoC (MPSoC) started a new computing era. It is becoming increasingly used because it can provide designers much more opportunities to meet specific performances. Designing embedded systems includes two main phases: (i) HW/SW Partitioning performed from high-level (eclipse C/C++ or python (machine learning and deep learning)) functional and architecture models (with virtual prototype and real prototype). And (ii) Software Design performed with significantly more detailed models with scheduling and partitioning tasks algorithm DAG Directed Acyclic Graph and GGEN Generation Graph Estimation Nodes (there are automatic DAG algorithm). Partitioning decisions are made according to performance assumptions that should be validated on the more refined software models for ME block and GGEN algorithm. In this paper, we focus to optimize a execution time and amelioration for quality of video with a scheduling and partitioning tasks in video codec. We show how they can be modeled the video sequence test with the size of video in height and width (three models of scheduling tasks in four processor). This modeling with DAG and GGEN are partitioning at different platform in OVP (partitioning, SW design). We can know the optimization of consumption energy and execution time in SoC and MPSoC platform.

Household Water and Energy Consumption Changes during COVID-19 Pandemic Lockdowns: Cases of the Kazakhstani Cities of Almaty, Shymkent, and Atyrau

The COVID-19 pandemic has changed the daily behaviors of people by forcing them to spend the majority of their time in their residences, particularly during social distancing measures. The increased time spent at home is expected to influence, among other things, the daily consumption of utilities: specifically, water and energy. A prolonged presence of residents at home during COVID-19 lockdowns might increase strain on water and energy resources, which are mostly from non-renewable sources in several countries, including Kazakhstan; however, such potentially important effects have not yet been studied for the country. The present research aims to evaluate how the COVID-19 pandemic lockdowns have affected the water and energy consumption in residential housings in cities of varying sizes in Kazakhstan, providing a novel understanding of the effect of pandemic lockdowns on household energy and water consumption. Energy and water consumption data of Almaty, Shymkent, and Atyrau have been first obtained from the local service companies, and then, the usage behavior was analyzed for the periods before, during, and after the COVID-19 pandemic lockdown. After, statistical tests were conducted to check the hypotheses regarding the effect of COVID-19 pandemic lockdowns on the consumption of energy and water. The findings indicate that residential energy and water consumption increased during the lockdown periods in large and medium cities. Nevertheless, this growth is not highly significant compared to similar non-pandemic timeframes. This result could indicate a particular risk for sustainable resources consumption and put pressure on the supply companies. Moreover, in case of further lockdown measures, current building systems are at risk of increased pressure, and eventually, of failure.

MAC chastised Dynamism Efficient in Wireless Device Lattice Spending Mistralapproach

In Wireless sensor Network, several researchers have provided different routing protocol for sensor networks, particularly routing protocols depending on clusters protocols. Reliability of nodes is necessary parameter in effective sensor networks. We use MAC protocol for controlling the network packets. This is because the usage of cluster based routing has several merits like minimized control messages, re-usability of bandwidth and enhanced power control. Different cluster based routing protocol is proposed by many researchers for the purpose of reducing the consumption energy in wireless sensor networks. Those techniques reduces the energy consumption but with several disadvantages like lack of QoS, inefficient transmission, etc., To overcome those problems, modified QoS enhanced base station controlled in Mistrial Approach (flooding Technique) for wireless sensor networks is proposed in this work. Here we reduce the number of retransmission and detect the overlay packets in networks using proposed approach. Simulation results show the better energy consumption, Maximum Life time & Efficient Bandwidth is achieved by flooding management when compared to the conventional techniques

Process of separating acetonitrile and water using LTTMs as entrainer

New extractive distillation configurations, which use low transition temperature mixtures (LTTMs) as entrainers, have attracted widespread attention among scholars due to their green processes. Furthermore, the design and comparison of different processes can promote the application of new solvents in the future. In this study, two extractive distillation processes, the extractive distillation column (ED) and the extraction dividing wall column (EDW), were selected from previous work. The separation process of acetonitrile (ACN)-water ternary mixtures was studied, and GC3:1(choline chloride/glycolic acid mixture (molar mass 1:3)) and EC2:1((choline chloride/ethylene glycol 1:2 molar mass) were used as entrainers. Minimum consumption energy and the purity of ACN and water were set as the goals, and our sensitivity analysis and economic evaluation results showed that both ED and EDW were effective. As a result, LTTMs can be used in extractive distillation for azeotrope separation.

Proposing a Method for Assessing Fuel Consumption and Pollutants Emissions with the Use of Continuously Variable Transmission in Town Cars

The 21st century brings countless social, economic, environmental, and technological challenges to humanity and, to face them, the United Nations (UN) created the Sustainable Development Goals (SDGs). The auto industry, which is part of the private sector, aims to reach them. In this context, this study aims to evaluate the consumption and emissions of pollutants by using an automatic transmission of the CVT (Continuously Variable Transmission) type concerning the automatic transmission of the "Planetary" type. This study will be based on the Consumption/Energy Efficiency tables, published annually by INMETRO (National Institute of Metrology, Quality, and Technology) and whose data will be processed and evaluated using the Quik Sense Software. Thus, the work aims to appraise the advantages of vehicles with automatic transmission of the CVT type about fuel consumption, energy efficiency and emissions, in markets such as Brazil, where these vehicles use ethanol or a mixture of gasoline with up to 27 as fuel % Ethanol. This research can contribute to studies of emission control and approval, benefiting the automotive industry in general, government agencies, the environment, the economy, and society, contributing to the UN's SDGs achievement.

The Multidimensionality of Consumption: Energy Lifestyles

This chapter enhances the previous understanding of Energy Lifestyles by identifying groups with distinct patterns of energy behavior across six areas of life. In contrast to most previous studies, the identification of groups is exclusively conducted on the basis of behavior-related data, whereas the characterization of the groups follows in a second step using psychological and socio-demographic variables. This chapter explicitly considers the multidimensionality of behavior and provides a comprehensive overview of different Energy Lifestyles and their potential roles in energy transition. The finding that there are almost no “average users” points out that policy designs must go beyond average figures based on the national emission figures and need to focus on different Energy Lifestyles.