Asymptotically Optimal Approximation Algorithms for Coflow Scheduling

Many modern datacenter applications involve large-scale computations composed of multiple data flows that need to be completed over a shared set of distributed resources. Such a computation completes when all of its flows complete. A useful abstraction for modeling such scenarios is a {\em coflow}, which is a collection of flows (e.g., tasks, packets, data transmissions) that all share the same performance goal. In this paper, we present the first approximation algorithms for scheduling coflows over general network topologies with the objective of minimizing total weighted completion time. We consider two different models for coflows based on the nature of individual flows: circuits, and packets. We design constant-factor polynomial-time approximation algorithms for scheduling packet-based coflows with or without given flow paths, and circuit-based coflows with given flow paths. Furthermore, we give an $O(\log n/\log \log n)$-approximation polynomial time algorithm for scheduling circuit-based coflows where flow paths are not given (here $n$ is the number of network edges). We obtain our results by developing a general framework for coflow schedules, based on interval-indexed linear programs, which may extend to other coflow models and objective functions and may also yield improved approximation bounds for specific network scenarios. We also present an experimental evaluation of our approach for circuit-based coflows that show a performance improvement of at least 22% on average over competing heuristics.Comment: Fixed minor typo

A Software Application For The Selection Of Temperature Measuring Sensors Using The Analytic Hierarchy Process (AHP)

This study presents a computer program that applies analytic hierarchy process (AHP) method to objectively select the best temperature sensors for various applications from multiple nominated alternatives. The underlying decision method based on AHP methodology, ranks temperature sensors with different features with a score resulting from the synthesis of relative preferences of each alternative to the others at different levels considering independent evaluation criteria. At each level, relative preferences of each candidate alternative with respect to the upper immediate level are calculated from pair-wise comparisons among the candidate alternative sensors based on the specifications of sensors with respect to a selected application. These pair-wise relative comparison weights are embedded in the computer software and are retrieved whenever the user specifies the application, the restrictions, and the available alternative sensors that meet these restrictions. AHP method proves to provide a quantitative and rational alternative performance evaluation method; it permits simpler, easier and more organized decision making process than subjective opinions that are subject to erroneous judgments. In this study, the application of AHP method in selecting the best temperature sensor for a particular application is embedded via the use of a computer program built using C# programming language to help perform the selection process in an easy graphical user interface GUI, ready-to-use, and computerized way and thus provides aid to those working in industry and in need of such a software tool. The proposed computer program is versatile and applicable to multitude of temperature sensors selection situations. A case study from the automotive industry which is the catalytic convertor application is presented. This application demands the use of temperature sensors capable of monitoring high temperatures in the order of 500°C-750°C, with a maximum temperature of ~870°C [1]. The selection process is conducted from among three alternative sensor categories, these are: thermocouples, thermisters, and RTD thermometers. The computer program is robust and applicable to a wider range of temperature sensors selection situations with a variety of applications and different arrays of candidate sensors

Selection of Temperature Measuring Sensors Using the Analytic Hierarchy Process

This study presents an analytic hierarchy process (AHP) method to objectively select the best temperature sensor from among different alternative sensors in a certain industrial application. The underlying decision method based on AHP methodology, ranks temperature sensors with different features with a score resulting from the synthesis of relative preferences of each alternative with respect to the others at different levels considering independent evaluation criteria and sub-criteria. At each level, relative preferences of each candidate alternative with respect to the upper immediate level are calculated from pair-wise comparisons among the candidate alternative sensors with respect to a selected application. Pair-wise comparison matrices are compiled based on views of experts in this field. Seven alternative sensors were considered: the thermocouple, the thermister, the resistance temperature detector (RTD), the bimetallic strip thermometer, the mercury-in-glass thermometer, the optical disappearing filament pyrometer, and the liquid crystal display semi conductor thermometer (LCD). Three industrial applications were also considered: Automotives, Chemical Processes, and Heating, Ventilating and Air Conditioning. A case study is conducted which involves selecting the best sensor for an automotive catalytic converter. The thermocouple is found to be the most preferred sensor for this application with the largest score of 0.37849, the second ranked sensor is the RTD with a score of 0.34589, and the least preferred sensor is the thermister with a score of 0.27560. To test the robustness of the proposed work, a sensitivity analysis was conducted in which variations in the relative preferences of the alternative sensors against sub-criteria and criteria were employed

Selection of Temperature Measuring Sensors Using the Analytic Hierarchy Process

This study presents an analytic hierarchy process (AHP) method to objectively select the best temperature sensor from among different alternative sensors in a certain industrial application. The underlying decision method based on AHP methodology, ranks temperature sensors with different features with a score resulting from the synthesis of relative preferences of each alternative with respect to the others at different levels considering independent evaluation criteria and sub-criteria. At each level, relative preferences of each candidate alternative with respect to the upper immediate level are calculated from pairwise comparisons among the candidate alternative sensors with respect to a selected application. Pair-wise comparison matrices are compiled based on views of experts in this field. Seven alternative sensors were considered: the thermocouple, the thermister, the resistance temperature detector (RTD), the bimetallic strip thermometer, the mercury-in-glass thermometer, the optical disappearing filament pyrometer, and the liquid crystal display semi conductor thermometer (LCD). Three industrial applications were also considered: Automotives, Chemical Processes, and Heating, Ventilating and Air Conditioning. A case study is conducted which involves selecting the best sensor for an automotive catalytic converter. The thermocouple is found to be the most preferred sensor for this application with the largest score of 0.37849, the second ranked sensor is the RTD with a score of 0.34589, and the least preferred sensor is the thermister with a score of 0.27560. To test the robustness of the proposed work, a sensitivity analysis was conducted in which variations in the relative preferences of the alternative sensors against sub-criteria and criteria were employed

A Software Application for the Selection of Temperature Measuring Sensors Using the Analytic Hierarchy Process (AHP)

This study presents a software application that applies the Analytic Hierarchy Process (AHP) to objectively select the best temperature sensors. Three industrial applications and seven sensor alternatives are considered. The developed application performs the selection process in a computerised, easy–to–use graphical user interface. The underlying decision method ranks temperature sensors with scores resulting from the synthesis of relative preferences of each alternative at different levels considering independent evaluation criteria. Pair–wise relative comparison matrices collected from experts are embedded and are retrieved according to user specifications. A case study is conducted which involves selecting the best sensor for an automotive catalytic converter. The thermocouple is found to be the most preferred sensor with the largest score of 0.37849, the second ranked sensor is the RTD with a score of 0.34589, and the least preferred sensor is the thermister with a score of 0.27560. Sensitivity analysis shows that the selection of the best sensor is dependent on the relative weights of the criteria as well as the chosen application. AHP is shown to provide a quantitative evaluation method which is simpler, easier and more organised than subjective opinions

A Brain-Inspired Multi-Modal Perceptual System for Social Robots: An Experimental Realization

We propose a multi-modal perceptual system that is inspired by the inner working of the human brain; in particular, the hierarchical structure of the sensory cortex and the spatial-temporal binding criteria. The system is context independent and can be applied to many on-going problems in social robotics, including but not limited to person recognition, emotion recognition, and multi-modal robot doctor to name a few. The system encapsulates the parallel distributed processing of real-world stimuli through different sensor modalities and encoding them into features vectors which in turn are processed via a number of dedicated processing units (DPUs) through hierarchical paths. DPUs are algorithmic realizations of the cell assemblies in neuroscience. A plausible and realistic perceptual system is presented via the integration of the outputs from these units by spiking neural networks. We will also discuss other components of the system including top-down influences and the integration of information through temporal binding with fading memory and suggest two alternatives to realize these criteria. Finally, we will demonstrate the implementation of this architecture on a hardware platform as a social robot and report experimental studies on the system

Characterization of Finfish Hatchery Waste for Value Added Product

Commercial fish hatchery generates waste both organic and inorganic; the sources are primarily from uneaten food and fish feces. Conventional methods of treating hatchery wastes will increase the operating cost and become extra burden in production. It is necessary to develop a new research application of this nonconventional resource and reduce the negative impacts of hatchery waste on the environment. The whole project is to utilize hatchery waste through bioprocess for probiotic fortified live feed production. In this study, the chemical composition of hatchery waste was determined to understand the suitability waste to get value-added derived products through bioprocess. Composite samples were collected everyday and dried in an oven at a temperature of 65˚C until complete dryness. Dried samples were mixed well and grinded into fine powder. The analytical parameters like total solids, ammonium nitrogen, nitrite, nitrate and phosphate were determined from the freshly collected samples. Total nitrogen, total phosphorus and total potassium were determined from the dry samples. Total solids, ammonium nitrogen, nitrite, nitrate and phosphate-phosphorus were observed in the ranged from 75 - 82 mg/L, 0.25 - 8.5 mg/L, 0.05 - 1.9 mg/L, 0.04 - 6.7 mg/L and 4.1 - 16.7 mg/L respectively. On the other hand, the mean content of 3.75% total nitrogen, 1.80% total phosphorus and 0.15% potassium were determined in dry hatchery wastes. The analytical parameters are useful and demonstrate that the nutrients in both fresh and dry waste will be supportive for the growth of microbes in the bioprocess system

Growth of Copper Sulfate Pentahydrate Single Crystals by Slow Evaporation Technique

Single crystals of CuSO4.5H2O (CSP) were grown by slow evaporation solution technique at room temperature from its aqueous solution with molarity (0.25, 0.5 and 1.5) M. The sizes of the crystals were up to (39×12×3) mm3, (33.05×30.5×4.7) mm3 and (19.12×15.3×5.5) mm3 respectively. XRD patterns were recorded for powder of single crystals to find the parameters of crystals. FTIR studies confirm the presence of various functional groups in the crystals. The optical absorption was study by using UV-Vis analysis. The spectra show low absorbance in the range between 300 nm and 550 nm. Energy gap (Eg) of crystals was found to be (4.17, 4.19 and 4.25) eV at the molarity of (0.25, 0.5 and 1.5) M respectively

1-(4-Chloro­benzo­yl)-3-cyclo­hexyl-3-methyl­thio­urea

In the title compound, C15H19ClN2OS, the dihedral angle between the amide and thio­urea fragments is 58.07 (17)°. The cyclo­hexane group adopts a chair conformation and is twisted relative to the thio­urea fragment, forming a dihedral angle of 87.32 (18)°. In the crystal, N—H⋯S hydrogen bond links the mol­ecules into chains running parallel to the a-axis direction

Pengaruh Kompensasi Terhadap Kepuasan Kerja Dan Intention to Leave (Studi Pada Karyawan Bank Jatim Cabang Malang)

The purpose of this research is to analyse and explain the influence of significant financial compensation towards job satisfaction, non financial compensation towards job satisfaction, financial compensation against the employee intention to leave, non financial compensation against the employee intention to leave and job satisfaction against the employee intention to leave. This research uses a survey research with type of explanatory research by spreading out questionnaire. The data analysis used is descriptive analysis and inferential statistical analysis using Path Analysis. The results showed the financial compensation have significant influence towards job satisfaction, non financial compensation effect significantly to job satisfaction, financial compensation is not has significant effect against the employee intention to leave, non financial compensation is not has significant effect against the employee intention to leave and job satisfaction has significant effect against the employee intention to leave. Recommendations for future research is to develop research in other places that have high working pressure and high turnover as a research object and replace or add other variables that could be associated with the employee intention to leave