Survey on Various MapReduce Scheduling Algorithms

2019 ◽  
pp. 499-515
Author(s):  
Vaibhav Pandey ◽  
Poonam Saini
Keyword(s):  
Social Networking ◽  
Programming Model ◽  
Scheduling Algorithms ◽  
Optimal Decision ◽  
Quality Requirements ◽  
Hadoop Mapreduce ◽  
Optimal Decision Making ◽  
Mapreduce Scheduling

The advent of social networking and internet of things (IoT) has resulted in exponential growth of data in the last few years. This, in turn, has increased the need to process and analyze such data for optimal decision making. In order to achieve better results, there is an emergence of newly-built architectures for parallel processing. Hadoop MapReduce (MR) is a programming model that is considered as one of the most powerful computation tools for processing the data on a given cluster of commodity nodes. However, the management of clusters along with various quality requirements necessitates the use of efficient MR scheduling. The chapter discusses the classification of MR scheduling algorithms based on their applicability with required parameters of quality of service (QoS). After classification, a detailed study of MR schedulers has been presented along with their comparison on various parameters.

scholarly journals Subjective optimality in finite sequential decision-making

2021 ◽  
Vol 17 (12) ◽  
pp. e1009633
Author(s):  
Yeonju Sin ◽  
HeeYoung Seon ◽  
Yun Kyoung Shin ◽  
Oh-Sang Kwon ◽  
Dongil Chung
Keyword(s):  
Decision Making ◽  
Time Window ◽  
Programming Model ◽  
Secretary Problem ◽  
Optimal Decision ◽  
Sequential Decision Making ◽  
Sequential Decision ◽  
Model Based ◽  
Subjective Valuation ◽  
Optimal Decision Making

Many decisions in life are sequential and constrained by a time window. Although mathematically derived optimal solutions exist, it has been reported that humans often deviate from making optimal choices. Here, we used a secretary problem, a classic example of finite sequential decision-making, and investigated the mechanisms underlying individuals’ suboptimal choices. Across three independent experiments, we found that a dynamic programming model comprising subjective value function explains individuals’ deviations from optimality and predicts the choice behaviors under fewer and more opportunities. We further identified that pupil dilation reflected the levels of decision difficulty and subsequent choices to accept or reject the stimulus at each opportunity. The value sensitivity, a model-based estimate that characterizes each individual’s subjective valuation, correlated with the extent to which individuals’ physiological responses tracked stimuli information. Our results provide model-based and physiological evidence for subjective valuation in finite sequential decision-making, rediscovering human suboptimality in subjectively optimal decision-making processes.

Study on the Application of QFD Technology in the Whole Conceptual Design of Special-Shaped Stone Machining Center

2011 ◽  
Vol 308-310 ◽  
pp. 739-746
Author(s):  
Nan Xiao ◽  
Yu Hou Wu ◽  
Yan Liu ◽  
Ke Zhang
Keyword(s):  
Quality Function Deployment ◽  
Decision Model ◽  
Limited Resource ◽  
Optimal Decision ◽  
Shape Design ◽  
Machining Center ◽  
Engineering Measures ◽  
Optimal Decision Making ◽  
Decision Making Model

The Quality Function Deployment (QFD) model and the optimal decision-making model is applied to the design of special-shaped stone Machining Center. Through the establishment of Design of house of quality of Machining Center, it can convert the users' needs and requirements of improvement on machining center into engineering measures of shape design of machining center in manufacturing engineering and at the same time combine resource consumption of various engineering measures implemented and resources of enterprises together. In the constrains of limited resource, in order to make the design of machining center meet the customers’ needs to the maximum extent and enhance the competitiveness of machine tool in the market, the optimal decision model can be used to select the vital engineering measurement on re-designing machining tool.

scholarly journals AQUiD: Automated Quality Assessment Using Digital Image Processing

2020 ◽  
pp. 295-300
Keyword(s):  
Oil Quality ◽  
Coconut Oil ◽  
Texture Features ◽  
High Quality ◽  
Quality Requirements ◽  
The People ◽  
Coconut Kernel ◽  
Growth Of Bacteria

Products in the market are expected to satisfy the consumer’s quality requirements. Agriculture being one of the main occupation of the people of India, the raw products must be sorted to determine whether they fit the quality description so that high quality products are obtained as the end result. The proposed method is designed to ensure the availability of good quality coconut oil in the market by assessing the quality of each individual sample going into the production line. 70% of moisture content present naturally in copra(dried coconut kernel) is dried to almost 7% for coconut oil production. To prevent the growth of bacteria and fungus on the surface of the copra, sulphur is added as a preservative. Allergenic reactions and lung performance restrictions can be caused due to the presence of sulphur in copra. The presence of moisture may also adversely affect oil quality. The texture features such as wrinkles, moulds, fungi growth on the surface also deplete the oil quality. The features of different kinds of copra are analysed and is used train the machine. The machine learning methodology is adopted for the classification of copra as usable and unusable.

Epistemic Uncertainties in Decision Making

2005 ◽  
Author(s):  
Michael Havbro Faber ◽  
Marc A. Maes
Keyword(s):  
Decision Making ◽  
Decision Analysis ◽  
Optimal Decision ◽  
Bayesian Decision ◽  
Typical Situation ◽  
Controversial Problem ◽  
Optimal Decision Making ◽  
Definition Of ◽  
Assessment Problems

The present paper reviews and outlines the interpretation of uncertainties with a view to the various different categorizations introduced in the literature. A framework is then presented for risk based decision making taking basis in the Bayesian decision theory and recent methodical developments in risk assessment. It is emphasized that in principle all types of uncertainties should be included in formal decision analysis and that not doing so corresponds to informal decision analysis the quality of which may be difficult to judge. The controversial problem in engineering decision making of how to take into account uncertainties associated with the definition of the system being analyzed is outlined. For the typical situation where a discrete set of possible system representations is possible it is shown how a decision problem may be formulated for the identification of the optimal system to be considered as basis for decision making. The presented decision framework takes into account all prevailing uncertainties, epistemic as well as aleatory. Examples related to structural design and assessment problems relevant for offshore engineering are given illustrating how not to account for all types of uncertainties leads to sub-optimal decision making.

scholarly journals Plithogenic n-Super Hypergraph in Novel Multi-Attribute Decision Making

2020 ◽  
pp. 08-30
Author(s):  
Florentin .. ◽  
◽  
◽  
Nivetha Martin
Keyword(s):  
Decision Making ◽  
Research Work ◽  
Decision Makers ◽  
Optimal Decision ◽  
The Novel ◽  
Multi Attribute Decision Making ◽  
Vertex Classification ◽  
Optimal Decision Making ◽  
Novel Concept

An optimal decision-making environment demands feasible Multi-Attribute Decision-Making methods. Plithogenic n – Super Hypergraph introduced by Smarandache is a novel concept and it involves many attributes. This article aims to bridge the concept of Plithogenic n-Super Hypergraph in the vicinity of optimal decision making. This research work introduces the novel concepts of enveloping vertex, super enveloping vertex, dominant enveloping vertex, classification of the dominant enveloping vertex (input, intervene, output dominant enveloping vertices), plithogenic connectors. An application of Plithogenic n-super hypergraph in making optimum decisions is discussed under various decision-making scenarios. Several insights are drawn from this research work and will certainly benefit the decision-makers to overcome the challenges in building decisions.

An Efficient Speculative Task Detection Algorithm for MapReduce Schedulers

2019 ◽  
Vol 13 ◽  
Author(s):  
Utsav Upadhyay ◽  
Geeta Sikka
Keyword(s):  
Large Scale ◽  
File System ◽  
Programming Model ◽  
Detection Algorithm ◽  
Hadoop Mapreduce ◽  
Hadoop Distributed File System ◽  
Hadoop Clusters ◽  
Improved Accuracy ◽  
Self Adaptive

The MapReduce programming model was developed and designed for Google File System to efficiently process large distributed datasets. The open source implementation of the Google project was called Apache Hadoop. Hadoop architecture comprises of Hadoop Distributed File System (HDFS) and Hadoop MapReduce. HDFS provides support to Hadoop for effectively managing large datasets over the cluster and MapReduce helps in efficient large-scale distributed datasets processing. MapReduce incorporates strategies to re-executes speculative task on some other node in order to finish computation quickly, enhancing the overall Quality of Service (QoS). Several mechanisms were suggested over default Hadoop’s Scheduler, such as Longest Approximate Time to End (LATE), Self-Adaptive MapReduce scheduler (SAMR) and Enhanced Self-Adaptive MapReduce scheduler (ESAMR), to improve speculative re-execution of tasks over the cluster. This paper presents an efficient speculative task detection algorithm for MapReduce schedulers. Our studies suggest the importance of keeping a regular track of node’s performance in order to re-execute speculative tasks more efficiently. We have successfully improved the QoS offered by Hadoop clusters over jobs in terms of reducing the detection time of speculative tasks (~ 15%) and improved accuracy of correct speculative task detection (~10%).

scholarly journals Subjective optimality in finite sequential decision-making

2020 ◽  
Author(s):  
Yeonju Shin ◽  
HeeYoung Seon ◽  
Yun Kyoung Shin ◽  
Oh-Sang Kwon ◽  
Dongil Chung
Keyword(s):  
Decision Making ◽  
Time Window ◽  
Programming Model ◽  
Secretary Problem ◽  
Optimal Decision ◽  
Sequential Decision Making ◽  
Sequential Decision ◽  
Model Based ◽  
Subjective Valuation ◽  
Optimal Decision Making

AbstractMany decisions in life are sequential and constrained by a time window. Although mathematically derived optimal solutions exist, it has been reported that humans often deviate from making optimal choices. Here, we used a secretary problem, a classic example of finite sequential decision-making, and investigated the mechanisms underlying individuals’ suboptimal choices. Across three independent experiments, we found that a dynamic programming model comprising subjective value function explains individuals’ deviations from optimality and predicts the choice behaviors under fewer opportunities. We further identified that pupil dilation reflected the levels of decision difficulty and subsequent choices to accept or reject the stimulus at each opportunity. The value sensitivity, a model-based estimate that characterizes each individual’s subjective valuation, correlated with the extent to which individuals’ physiological responses tracked stimuli information. Our results provide model-based and physiological evidence for subjective valuation in finite sequential decision-making, rediscovering human suboptimality in subjectively optimal decision-making processes.

scholarly journals Penerapan Analytical Network Process Dalam Menentukan Ras Ayam Serama Simple Additive Weighting (SAW)

2019 ◽  
Vol 3 (1) ◽  
pp. 28-34
Author(s):  
Wirhan Fahrozi ◽  
Samsir Samsir
Keyword(s):  
Optimal Decision ◽  
Accurate Information ◽  
Weighting Method ◽  
Network Process ◽  
New Type ◽  
Chicken Breeds ◽  
Simple Additive Weighting ◽  
Optimal Decision Making ◽  
Dwarf Chicken

Serama chicken is the result of dwarf chicken crossing and is a new type of ornamental poultry currently popular in Indonesia. So it becomes a consideration for lovers of serama to get information about quality of serama chickens that need to get accurate information about quality of serama chickens that still needs to be discussed for the assessment of serama chickens, therefore the author tries to implement it in the form of a Decision Support System in determining chicken breeds as well as by applying the Simple Additive Weighting method to assist in optimal decision making. So that the expected results of the quality of the serama chicken can help in determining the standard of serama chicken assessment.

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