An Effective Cloud Workflow Scheduling Approach Combining PSO and Idle Time Slot-Aware Rules

Workflow scheduling is a key issue and remains a challenging problem in cloud computing.Faced with the large number of virtual machine(VM)types offered by cloud providers,cloud users need to choose the most appropriate VM type for each task.Multiple task scheduling sequences exist in a workflow application.Different task scheduling sequences have a significant impact on the scheduling performance.It is not easy to determine the most appropriate set of VM types for tasks and the best task scheduling sequence.Besides,the idle time slots on VM instances should be used fully to increase resources'utilization and save the execution cost of a workflow.This paper considers these three aspects simultaneously and proposes a cloud workflow scheduling approach which combines particle swarm optimization(PSO)and idle time slot-aware rules,to minimize the execution cost of a workflow application under a deadline constraint.A new particle encoding is devised to represent the VM type required by each task and the scheduling sequence of tasks.An idle time slot-aware decoding procedure is proposed to decode a particle into a scheduling solution.To handle tasks'invalid priorities caused by the randomness of PSO,a repair method is used to repair those priorities to produce valid task scheduling sequences.The proposed approach is compared with state-of-the-art cloud workflow scheduling algorithms.Experiments show that the proposed approach outperforms the comparative algorithms in terms of both of the execution cost and the success rate in meeting the deadline.

Efects of idle time on biological phosphorus removal by sequencing batch reactors

Three identical sequencing batch reactors （SBRs） were operated to investigate the effects of various idle times on the biological phosphorus （P） removal. The idle times were set to 3 hr （R1）, 10 hr （R2） and 17 hr （R3）. The results showed that the idle time of a SBR had potential impact on biological phosphorus removal, especially when the influent phosphorus concentration increased. The phosphorus removal efficiencies of the R2 and R3 systems declined dramatically compared with the stable R1 system, and the Prelease and P-uptake rates of the R3 system in particular decreased dramatically. The PCR-DGGE analysis showed that uncultured Pseudomonas sp. （GQ183242.1） and β-Proteobacteria （AY823971） were the dominant phosphorus removal bacteria for the R1 and R2 systems, while uncultured γ-Proteobacteria were the dominant phosphorus removal bacteria for the R3 system. Glycogen-accumulating organisms （GAOs）, such as uncultured Sphingomonas sp. （AM889077）, were found in the R2 and R3 systems. Overall, the R1 system was the most stable and exhibited the best phosphorus removal efficiency. It was found that although the idle time can be prolonged to allow the formation of intracellular polymers when the phosphorus concentration of the influent is low, systems with a long idle time can become unstable when the influent phosphorus concentration is increased.

AN IMPROVED EPON UPSTREAM TRANSMISSION SCHEME WITH ZERO INTER-PERIOD IDLE LOSS

Existing Ethernet Passive Optical Network(EPON) Dynamic Bandwidth Allocation(DBA) algorithms suffer from the disadvantage of idle time loss,which lower the upstream bandwidth utili-zation.This letter proposes an improved upstream transmission scheme with idle-time eliminating mechanism.Theoretical analysis and numerical calculation prove that the improved scheme can ef-fectively eliminate the idle time and enhance the efficiency of upstream link utilization.Simulation results have shown that the bandwidth utilization can be raised up to 15% in heavy-load scenarios while the time delay performance of Assured Forwarding(AF) and Best Effort(BE) services are improved simultaneously.

Taboo Search Algorithm for Item Assignment in Synchronized Zone Automated Order Picking System

The idle time which is part of the order fulfillment time is decided by the number of items in the zone; therefore the item assignment method affects the picking efficiency. Whereas previous studies only focus on the balance of number of kinds of items between different zones but not the number of items and the idle time in each zone. In this paper, an idle factor is proposed to measure the idle time exactly. The idle factor is proven to obey the same vary trend with the idle time, so the object of this problem can be simplified from minimizing idle time to minimizing idle factor. Based on this, the model of item assignment problem in synchronized zone automated order picking system is built. The model is a form of relaxation of parallel machine scheduling problem which had been proven to be NP-complete. To solve the model, a taboo search algorithm is proposed. The main idea of the algorithm is minimizing the greatest idle factor of zones with the 2-exchange algorithm. Finally, the simulation which applies the data collected from a tobacco distribution center is conducted to evaluate the performance of the algorithm. The result verifies the model and shows the algorithm can do a steady work to reduce idle time and the idle time can be reduced by 45.63% on average. This research proposed an approach to measure the idle time in synchronized zone automated order picking system. The approach can improve the picking efficiency significantly and can be seen as theoretical basis when optimizing the synchronized automated order picking systems.

Assembly Line Balancing Using Fuzzy Logic: A Case Study of a Tricycle Assembly Line

The application of fuzzy logic in balancing a single model tricycle assembly line is presented in this study. MATLAB simulation software was used in the analysis of the primary and secondary data obtained from the assembly line under study. Results obtained from the study show that the efficiency of the line increased from 88.1% to 92.4%. The total idle time was also reduced by 56.5%. This indicates an improvement in the efficiency of the line, reduction of bottleneck, and even distribution of tasks along the line for the company under study.