scholarly journals TMaR: a two-stage MapReduce scheduler for heterogeneous environments

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Neda Maleki ◽  
Hamid Reza Faragardi ◽  
Amir Masoud Rahmani ◽  
Mauro Conti ◽  
Jay Lofstead
Keyword(s):  
Task Scheduling ◽  
Network Traffic ◽  
Input Data ◽  
Power Reduction ◽  
Heterogeneous Environments ◽  
Two Stage ◽  
Finish Time ◽  
Remote Storage ◽  
Simulation Results

Abstract In the context of MapReduce task scheduling, many algorithms mainly focus on the scheduling of Reduce tasks with the assumption that scheduling of Map tasks is already done. However, in the cloud deployments of MapReduce, the input data is located on remote storage which indicates the importance of the scheduling of Map tasks as well. In this paper, we propose a two-stage Map and Reduce task scheduler for heterogeneous environments, called TMaR. TMaR schedules Map and Reduce tasks on the servers that minimize the task finish time in each stage, respectively. We employ a dynamic partition binder for Reduce tasks in the Reduce stage to lighten the shuffling traffic. Indeed, TMaR minimizes the makespan of a batch of tasks in heterogeneous environments while considering the network traffic. The simulation results demonstrate that TMaR outperforms Hadoop-stock and Hadoop-A in terms of makespan and network traffic and achieves by an average of 29%, 36%, and 14% performance using Wordcount, Sort, and Grep benchmarks. Besides, the power reduction of TMaR is up to 12%.

Task scheduling algorithm based on improved genetic algorithm in cloud computing environment

2020 ◽  
Vol 13 ◽  
Author(s):  
Ge Weiqing ◽  
Cui Yanru
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Task Completion ◽  
Improved Genetic Algorithm ◽  
Fitness Functions ◽  
Task Scheduling Algorithm ◽  
Simulation Results

Background: In order to make up for the shortcomings of the traditional algorithm, Min-Min and Max-Min algorithm are combined on the basis of the traditional genetic algorithm. Methods: In this paper, a new cloud computing task scheduling algorithm is proposed, which introduces Min-Min and Max-Min algorithm to generate initialization population, and selects task completion time and load balancing as double fitness functions, which improves the quality of initialization population, algorithm search ability and convergence speed. Results: The simulation results show that the algorithm is superior to the traditional genetic algorithm and is an effective cloud computing task scheduling algorithm. Conclusion: Finally, this paper proposes the possibility of the fusion of the two quadratively improved algorithms and completes the preliminary fusion of the algorithm, but the simulation results of the new algorithm are not ideal and need to be further studied.

Design of 25-Gb/s Half-Rate Clock and Data Recovery Circuit for Optical Communication

2013 ◽  
Vol 385-386 ◽  
pp. 1278-1281 ◽  
Author(s):  
Zheng Fei Hu ◽  
Ying Mei Chen ◽  
Shao Jia Xue
Keyword(s):  
Optical Communication ◽  
Input Data ◽  
Clock And Data Recovery ◽  
Cmos Technology ◽  
Data Recovery ◽  
Phase Detector ◽  
Voltage Controlled Oscillator ◽  
Output Data ◽  
Data Phase ◽  
Simulation Results

A 25-Gb/s clock and data recovery (CDR) circuit with 1:2 demultiplexer which incorporates a quadrature LC voltage-controlled-oscillator and a half-rate bang-bang phase detector is presented in this paper. A quadrature LC VCO is presented to generate the four-phase output clocks. A half-rate phase detector including four flip-flops samples the 25-Gb/s input data every 20 ps and alignes the data phase. The 25-Gb/s data are retimed and demultiplexed into two 12.5-Gb/s output data. The CDR is designed in TSMC 65nm CMOS Technology. Simulation results show that the recovered clock exhibits a peak-to-peak jitter of 0.524ps and the recovered data exhibits a peak-to-peak jitter of 1.2ps. The CDR circuit consumes 121 mW from a 1.2 V supply.

A New Method of Rolling Prediction for Gas Emission Based on Wavelet Neural Network

2011 ◽  
Vol 383-390 ◽  
pp. 1500-1506
Author(s):  
Yu Min Pan ◽  
Xiao Yu Zhang ◽  
Peng Qian Xue
Keyword(s):  
Neural Network ◽  
Input Data ◽  
Wavelet Neural Network ◽  
New Method ◽  
Neutral Network ◽  
Gas Emission ◽  
Sample Data ◽  
Simulation Results

A new method of rolling prediction for gas emission based on wavelet neural network is proposed in this paper. In the method, part of the sample data is selected, which length is constant, and the data is reselected as the next prediction step. Then a wavelet neutral network is adopted to prediction which input data is rolling, the sequence model of rolling prediction is thus constructed. Simulation results have proved that the method is valid and feasible.

scholarly journals An Efficient Power Optimized 32 bit BCD Adder Using Multi-Channel Technique

2017 ◽  
Vol 6 (02) ◽  
pp. 07-12
Author(s):  
Diksha Siddhamshittiwar
Keyword(s):  
Average Power ◽  
Full Adder ◽  
Deep Submicron ◽  
Power Reduction ◽  
Vlsi Circuits ◽  
Power Gating ◽  
Static Power ◽  
Simulation Results ◽  
Efficient Power ◽  
Standby Mode

Static power reduction is a challenge in deep submicron VLSI circuits. In this paper 28T full adder circuit, 14T full adder circuit and 32 bit power gated BCD adder using the full adders respectively were designed and their average power was compared. In existing work a conventional full adder is designed using 28T and the same is used to design 32 bit BCD adder. In the proposed architecture 14T transmission gate based power gated full adder is used for the design of 32 bit BCD adder. The leakage supremacy dissipated during standby mode in all deep submicron CMOS devices is reduced using efficient power gating and multi-channel technique. Simulation results were obtained using Tanner EDA and TSMC_180nm library file is used for the design of 28T full adder, 14T full adder and power gated BCD adder and a significant power reduction is achieved in the proposed architecture.

Reduction of Torsional Vibration in Resonance Phenomena for Tractor Power Take-Off Drivelines Using Torsional Damper

2021 ◽  
Vol 64 (2) ◽  
pp. 365-376
Author(s):  
Da-Vin Ahn ◽  
In-Kyung Shin ◽  
Jooseon Oh ◽  
Woo-Jin Chung ◽  
Hyun-Woo Han ◽  
...  
Keyword(s):  
Angular Velocity ◽  
Torsional Vibration ◽  
Simulation Software ◽  
Drive Shaft ◽  
Torsional Stiffness ◽  
List Type ◽  
Two Stage ◽  
Mass Moment ◽  
Simulation Results ◽  
Agricultural Tractors

HighlightsRattling of tractor power take-off drivelines can be detrimental to operators.A novel driveline model, which includes a torsional damper, was constructed.The behavior of the model was validated against that of an actual tractor driveline.The validated model was used to determine the optimal torsional damper parameters.These optimal parameters were validated by laboratory tests.Abstract. Rattle noise and high levels of vibration in agricultural tractors lower the productivity of the operators and may cause serious health issues in them. This study examined a method for preventing resonance and reducing the torsional vibration that causes rattling in tractor power take-off (PTO) drivelines in the idle state using a two-stage torsional damper. The PTO driveline was simplified to a 6-DOF model based on the principle of equivalent mass moment of inertia using commercial simulation software. The variations in the angular velocity of the PTO drive shaft in an actual tractor were measured and compared to the simulation results using a single-stage torsional damper to validate the model. Using this validated PTO driveline model, the pre spring of a two-stage torsional damper was investigated to determine its optimal torsional stiffness to minimize torsional vibration. The simulation results showed that the variations in the angular velocity of the PTO drive shaft decreased as the torsional stiffness of the pre spring decreased; accordingly, an appropriate torsional stiffness reduced the variation in the angular velocity delivered to the PTO drive shaft. The optimal torsional stiffness of the pre spring was determined by considering the manufacturing limitations of the torsional damper and the magnitude of the input engine torque. A pre spring with this optimal torsional stiffness was installed on an actual PTO driveline to measure the angular velocity transmissibility, which was the ratio of the variation in the angular velocity of the engine flywheel to the variation in the angular velocity of the PTO drive shaft, and the results were compared with those of the simulation. When the angular velocity of the engine was 850 rpm, the angular velocity transmissibility of the PTO drive shaft was 0.4 in the actual test, similar to the value of 0.29 obtained using the simulation. Thus, the simulation-optimized pre spring was able to avoid the resonance domain, while considerably reducing the torsional vibration that leads to rattling. The results of this study support the safe operation of agricultural tractors and guide the evaluation of torsional damper configurations of different vehicles. Keywords: PTO driveline, Resonance, Simulation model, Torsional damper, Torsional vibration, Tractor rattle.

scholarly journals An Energy-Efficient Two-Stage Cooperative Routing Scheme in Wireless Multi-Hop Networks

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1002 ◽  
Author(s):  
Jianming Cheng ◽  
Yating Gao ◽  
Ningbo Zhang ◽  
Hongwen Yang
Keyword(s):  
Energy Efficiency ◽  
Network Lifetime ◽  
Cooperative Transmission ◽  
Transmission Model ◽  
Two Stage ◽  
Routing Scheme ◽  
Cooperative Routing ◽  
Link Cost ◽  
Simulation Results ◽  
End To End

Cooperative routing is one of the most widely used technologies for improving the energy efficiency and energy balance of wireless multi-hop networks. However, the end-to-end energy cost and network lifetime are greatly restricted if the cooperative transmission model is not designed properly. The main aim of this paper is to explore a two-stage cooperative routing scheme to further improve the energy efficiency and prolong the network lifetime. A two-stage cooperative (TSC) transmission model is firstly designed in which the core helper is introduced to determine the helper set for cooperation. Then, the two-stage link cost is formulated where x, the weight of residual energy, is introduced to be adjusted for different design goals. By selecting the optimal helper set, the two-stage link cost of each link can be optimized. Finally, based on the designed TSC transmission model and the optimized two-stage link cost, a distributed two-stage cooperative routing (TSCR) scheme is further proposed to minimize the end-to-end cooperative routing cost. Simulation results evaluate the effect of x on the different performance metrics. When x equals 0, TSCR can achieve the shortest end-to-end transmission delay and highest energy efficiency, while a larger x can achieve a longer network lifetime. Furthermore, simulation results also show that the proposed TSCR scheme can effectively improve both the energy efficiency and network lifetime compared with the existing schemes.

A PSO Algorithm Based Task Scheduling in Cloud Computing

2019 ◽  
Vol 10 (4) ◽  
pp. 1-17 ◽  
Author(s):  
Mohit Agarwal ◽  
Gur Mauj Saran Srivastava
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Virtual Machines ◽  
Pso Algorithm ◽  
Emerging Technology ◽  
The Internet ◽  
Hard Problem ◽  
Swarm Optimization ◽  
Np Hard Problem ◽  
Simulation Results

Cloud computing is an emerging technology which involves the allocation and de-allocation of the computing resources using the internet. Task scheduling (TS) is one of the fundamental issues in cloud computing and effort has been made to solve this problem. An efficient task scheduling mechanism is always needed for the allocation to the available processing machines in such a manner that no machine is over or under-utilized. Scheduling tasks belongs to the category of NP-hard problem. Through this article, the authors are proposing a particle swarm optimization (PSO) based task scheduling mechanism for the efficient scheduling of tasks among the virtual machines (VMs). The proposed algorithm is compared using the CloudSim simulator with the existing greedy and genetic algorithm-based task scheduling mechanism. The simulation results clearly show that the PSO-based task scheduling mechanism clearly outperforms the others as it results in almost 30% reduction in makespan and increases the resource utilization by 20%.

Trim Down Redundant Transmission in Data Synchronization

2013 ◽  
Vol 284-287 ◽  
pp. 2789-2793
Author(s):  
Chun Hao Wen ◽  
Richard Chun Hung Lin
Keyword(s):  
Heuristic Algorithm ◽  
Network Traffic ◽  
Numerical Results ◽  
Collaborative Networks ◽  
Data Synchronization ◽  
Finish Time ◽  
Synchronization Scheme ◽  
Push And Pull

Data synchronization distributes data to users of various configurations, and poses many challenges in today’s collaborative networks. In this paper, we propose a data synchronization scheme to reduce the finish time of distributing data with the understanding that users are free to join late or leave, which is common if the desired data is received. Our scheme involves a heuristic algorithm to push-and-pull segments of data. The numerical results yield significant lesser finish time than the conventional P2P approaches. Besides, there are no redundant transmissions and no need of searching data pieces in our approach, which help to reduce the network traffic and receiving time of data.

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