EM_WOA: A budget-constrained energy consumption optimization approach for workflow scheduling in clouds

2022 ◽  
Author(s):  
Longxin Zhang ◽  
Lan Wang ◽  
Mansheng Xiao ◽  
Zhicheng Wen ◽  
Cheng Peng
Keyword(s):  
Energy Consumption ◽  
Workflow Scheduling ◽  
Optimization Approach ◽  
Energy Consumption Optimization

scholarly journals An Area Coverage and Energy Consumption Optimization Approach Based on Improved Adaptive Particle Swarm Optimization for Directional Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1192 ◽  
Author(s):  
Song Peng ◽  
Yonghua Xiong
Keyword(s):  
Energy Consumption ◽  
Cluster Head ◽  
Area Coverage ◽  
Optimization Approach ◽  
Directional Sensor Networks ◽  
Swarm Optimization ◽  
Coverage Ratio ◽  
Energy Consumption Optimization ◽  
Set Up ◽  
Directional Sensor

Coverage is a vital indicator which reflects the performance of directional sensor networks (DSNs). The random deployment of directional sensor nodes will lead to many covergae blind areas and overlapping areas. Besides, the premature death of nodes will also directly affect the service quality of network due to limited energy. To address these problems, this paper proposes a new area coverage and energy consumption optimization approach based on improved adaptive particle swarm optimization (IAPSO). For area coverage problem, we set up a multi-objective optimization model in order to improve coverage ratio and reduce redundancy ratio by sensing direction rotation. For energy consumption optimization, we make energy consumption evenly distribute on each sensor node by clustering network. We set up a cluster head selection optimization model which considers the total residual energy ratio and energy consumption balance degree of cluster head candidates. We also propose a cluster formation algorithm in which member nodes choose their cluster heads by weight function. We next utilize an IAPSO to solve two optimization models to achieve high coverage ratio, low redundancy ratio and energy consumption balance. Extensive simulation results demonstrate the our proposed approach performs better than other ones.

Stability of aerobic granular sludge under low energy consumption: Optimization of granular size distribution by a novel internal component

2021 ◽  
Author(s):  
Runjuan Cao ◽  
Yatong Ji ◽  
Taixing Han ◽  
Jingsong Deng ◽  
Liang Zhu ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Granular Sludge ◽  
Pollutant Removal ◽  
Low Energy ◽  
Aerobic Granular Sludge ◽  
Mesh Screen ◽  
Energy Consumption Optimization ◽  
Low Energy Consumption ◽  
Internal Component ◽  
The Stability

To enhance the stability and pollutant removal performance of an aerobic granular sludge (AGS), four groups of AGS reactors with different pore sizes of mesh screen (R1 is control reactor,...

Performance study and critical review on energy aware routing protocols in mobile sink based WSNs

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Aparna Ashok Kamble ◽  
Balaji Madhavrao Patil
Keyword(s):  
Wireless Networks ◽  
Energy Consumption ◽  
Routing Protocols ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Delivery Ratio ◽  
Optimization Approach ◽  
Performance Study ◽  
Energy Aware ◽  
Energy Aware Routing

Abstract Wireless networks involve spatially extended independent sensor nodes, and it is associated with each other’s to preserve and identify physical and environmental conditions of the particular application. The sensor nodes batteries are equipped with restricted energy for working with an energy source. Consequently, efficient energy consumption is themain important challenge in wireless networks, and it is outfitted witharestricted power storage capacity battery. Therefore, routing protocol with energy efficiency is essential in wireless sensor network (WSN) to offer data transmission and connectivity with less energy consumption. As a result, the routing scheme is the main factor for decreasing energy consumption and the network's lifetime. The energy-aware routing model is mainly devised for WSN with high network performance when transmitting data to a sink node. Hence, in this paper, the effectiveness of energy-aware routing protocols in mobile sink-based WSNs is analyzed and justified. Some energy-aware routing systems in mobile sink-based WSN techniques, such as optimizing low-energy adaptive clustering hierarchy (LEACH) clustering approach, hybrid model using fuzzy logic, and mobile sink. The fuzzy TOPSIS-based cluster head selection (CHS) technique, mobile sink-based energy-efficient CHS model, and hybrid Harris Hawk-Salp Swarm (HH-SS) optimization approach are taken for the simulation process. Additionally, the analytical study is executed using various conditions, like simulation, cluster size, nodes, mobile sink speed, and rounds. Moreover, the performance of existing methods is evaluated using various parameters, namely alive node, residual energy, delay, and packet delivery ratio (PDR).

scholarly journals Minimum Energy Trajectory Optimization for Driving Systems of Palletizing Robot Joints

2018 ◽  
Vol 2018 ◽  
pp. 1-26
Author(s):  
Ying He ◽  
Jiangping Mei ◽  
Zhiwei Fang ◽  
Fan Zhang ◽  
Yanqin Zhao
Keyword(s):  
Fourier Series ◽  
Energy Consumption ◽  
Total Energy ◽  
Dynamic Model ◽  
Trajectory Optimization ◽  
Joint Torque ◽  
Total Energy Consumption ◽  
Energy Consumption Model ◽  
Energy Consumption Optimization ◽  
Consumption Model

Palletizing robot is widely used in logistics operation. At present, people pay attention to not only the loading capacity and working efficiency of palletizing robots, but also the energy consumption in their working process. This paper takes MD1200-YJ palletizing robot as the research object and studies the problem of low energy consumption optimization of joint driving system from the perspective of trajectory optimization. Firstly, a multifactor dynamic model of palletizing robot is established based on the conventional inverse rigid body dynamic model of the robot, the Stribeck friction model and the spring balance torque model. And then based on joint torque, friction torque, motion parameter, and joule’s law, the useful work model, thermal loss model of joint motor, friction energy consumption model of joint system, and total energy consumption model of palletizing robot are established, and through simulation and experiment, the correctness of the multifactor dynamic model and energy consumption model is verified. Secondly, based on the Fourier series approximation method to construct the joint trajectory expression, the minimum total energy consumption as the optimization objective, with coefficients of Fourier series as optimization variables, the motion parameters of initial and final position, and running time constant as constraint conditions, the genetic algorithm is used to solve the optimization problem. Finally, through the simulation analysis the optimized Fourier series motion law and the 3-4-5 polynomial motion law are comprehensively evaluated to verify the effectiveness of the optimization method. Moreover, it provides the theoretical basis for the follow-up research and points out the direction of improvement.

scholarly journals The energy consumption optimization of the BLAS routines

2017 ◽  
Author(s):  
Radim Sojka ◽  
Lubomir Riha ◽  
David Horak ◽  
Jakub Kruzik ◽  
Martin Beseda ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Consumption Optimization
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