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Quality Engineering of Distributed System with Hassle Free Load Curve Optimization

J. Jeyachitra, K. Iyakutti, K. Alagarsamy
2013 International Journal of Computer Applications  
However the traffic classification using non-parametric and non engineering approach fails to balance the load effectively in distributed system.  ...  So, in this work, we plan to improve the quality of load balancing in the distributed system by adapting Hassle-free Curved Optimization (HCO) traffic engineering principle.  ...  The load balancing rate is measured based on the number of tasks in the distributed system.  ... 
doi:10.5120/13441-1219 fatcat:ydkakp7vufh4pnxtrneeoblgny

Robust distributed stream processing

Chuan Lei, E. A. Rundensteiner, J. D. Guttman
2013 2013 IEEE 29th International Conference on Data Engineering (ICDE)  
RLD provides ǫ-optimal query performance under load fluctuations without suffering from the performance penalty caused by load migration. RLD is based on three key strategies.  ...  First, we model robust distributed stream processing as a parametric query optimization problem. The notions of robust logical and robust physical plans then are overlays of this parameter space.  ...  Similarly, parametric query optimization finds a set of plans that are optimal for different parameter settings.  ... 
doi:10.1109/icde.2013.6544877 dblp:conf/icde/LeiRG13 fatcat:2y62y6qzxrhifeyqdflsn6caxm

Outlier Detection Techniques for SQL and ETL Tuning

Saptarsi Goswami, Samiran Ghosh, Amlan Chakrabarti
2011 International Journal of Computer Applications  
The same philosophy we have used for optimization of extraction, transform, load (ETL) jobs in one of our previous work. We give a brief introduction of the same in section four.  ...  These queries need to conform to best practices and need to be tuned to ensure optimal performance.  ...  The statistics based techniques will be either parametric (assumes a data distribution model) or non-parametric.  ... 
doi:10.5120/2907-3819 fatcat:pawopl4fzfb4tio6dps6esd3qa

Algorithms for index-assisted selectivity estimation

P.M. Aoki
1999 Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337)  
The standard mechanisms for query selectivity estimation used in relational database systems rely on properties specific to the attribute types.  ...  The query optimizer in an object-relational database system will, in general, be unable to exploit these mechanisms for user-defined types, requiring the user to create entirely new estimation mechanisms  ...  Data Sets We explicitly chose to conduct experiments on selected data sets rather than on synthetic data sets generated using simple parametric distributions.  ... 
doi:10.1109/icde.1999.754938 dblp:conf/icde/Aoki99 fatcat:66kivnf5gndzhl753m7maham4q

Estimating Query Result Sizes for Proxy Caching in Scientific Database Federations

Tanu Malik, Randal Burns, Nitesh Chawla, Alex Szalay
2006 ACM/IEEE SC 2006 Conference (SC'06)  
With accurate estimates, near-optimal cache performance can be obtained. On the other extreme, inaccurate estimates can render the cache totally ineffective.  ...  CAROT estimates query result sizes by learning the distribution of query results, not by examining or sampling data, but from observing workload.  ...  Non-parametric approaches [12, 15, 27] are mainly histogram based.  ... 
doi:10.1109/sc.2006.27 fatcat:yzq67pfs7za3ndj736tqdljapy

Data management and query---Estimating query result sizes for proxy caching in scientific database federations

Tanu Malik, Randal Burns, Nitesh V. Chawla, Alex Szalay
2006 Proceedings of the 2006 ACM/IEEE conference on Supercomputing - SC '06  
With accurate estimates, near-optimal cache performance can be obtained. On the other extreme, inaccurate estimates can render the cache totally ineffective.  ...  CAROT estimates query result sizes by learning the distribution of query results, not by examining or sampling data, but from observing workload.  ...  Acknowledgments The authors sincerely thank Jim Gray for his help with the selectivity estimation methods proposed for query optimizers.  ... 
doi:10.1145/1188455.1188562 dblp:conf/sc/MalikBCS06 fatcat:6avilhqbkzh6flkugosxtic57u

Slicing long-running queries

Nicolas Bruno, Vivek Narasayya, Ravi Ramamurthy
2010 Proceedings of the VLDB Endowment  
load balancing.  ...  We study different ways to extend a traditional query optimizer to enable query slicing and experimentally evaluate the benefits of each approach.  ...  Second, the dominance condition on the skyline operator is extended so that (i) plans parameterized on different columns do not dominate each other, and (ii) parametric plan p1 dominates parametric plan  ... 
doi:10.14778/1920841.1920910 fatcat:v362fzp7uzhixh4nnt4fmdkw7q

Optimal Load Factor for Approximate Nearest Neighbor Search under Exact Euclidean Locality Sensitive Hashing

Ruben Buaba, Abdollah Homaifar, Eric Kihn
2013 International Journal of Computer Applications  
The minimization of ρ at a specific approximation factor c, is dependent on the load factor, α. Over the years, = 4has been used by researchers.  ...  Experiments on the Defense Meteorological Satellite Program imagery datasethave shown that = 5saves more than 75%on memory space; cuts the computational complexity by more than 70%andanswers query two  ...  PRACTICALLSH IMPLEMENTATION We present a real-world problem and solve it using LSH parameterization based on existing optimal load factor of = 4and our proposed optimal load factor, = 5.  ... 
doi:10.5120/12096-8258 fatcat:wmqgs4pzwndl7m6m4ostholl44

Adaptive selectivity estimation using query feedback

Chungmin Melvin Chen, Nick Roussopoulos
1994 Proceedings of the 1994 ACM SIGMOD international conference on Management of data - SIGMOD '94  
Experimental results show that the estimation accuracy of this approach is comparable to traditional methods based on statistics gathering.  ...  The real attribute value distribution is adaptively approximated by a curvetting function using a query feedback mechanism.  ...  A study on error propagation IC91] revealed that selectivity estimation errors can increase exponentially with the number of joins and thus a ect the decisions in query optimization.  ... 
doi:10.1145/191839.191874 dblp:conf/sigmod/ChenR94 fatcat:sgx7rjp3tvf4lltgsyq5cf4jra

Adaptive selectivity estimation using query feedback

Chungmin Melvin Chen, Nick Roussopoulos
1994 SIGMOD record  
Experimental results show that the estimation accuracy of this approach is comparable to traditional methods based on statistics gathering.  ...  The real attribute value distribution is adaptively approximated by a curvetting function using a query feedback mechanism.  ...  A study on error propagation IC91] revealed that selectivity estimation errors can increase exponentially with the number of joins and thus a ect the decisions in query optimization.  ... 
doi:10.1145/191843.191874 fatcat:5fcywwxgkneufdang2ahadnsgi

Assessment and Optimization of User Imprecise Queries in Cloud Environments

Pichaimuthu Mohankumar, Balusamy Balamurugan
2017 International Journal of Intelligent Engineering and Systems  
Moreover, optimism significance relies on user satisfactions.  ...  To address optimization issues in this paper, we proposed the techniques for optimizing the queries to provide customers with fast data retrieval.  ...  Parametric query optimization Classical query optimization associates each query plan with one scalar cost value.  ... 
doi:10.22266/ijies2017.0630.14 fatcat:hp3z7uso7vbchafsj4ceejg3xi

Resource Usage Estimation of Data Stream Processing Workloads in Datacenter Clouds [article]

Alireza Khoshkbarforoushha, Rajiv Ranjan, Raj Gaire, Prem P. Jayaraman, John Hosking, Ehsan Abbasnejad
2015 arXiv   pre-print
The proposed approach is a flexible and convenient means of modeling unknown distribution models.  ...  queries; and (iii) variable resource consumption behavior of continuous queries.  ...  , conditioned on query features and data arrival rate distribution model.  ... 
arXiv:1501.07020v1 fatcat:3zvy2tglgfc6dnfsnv4jwlwkra

Distribution Based Workload Modelling of Continuous Queries in Clouds

Alireza Khoshkbarforoushha, Rajiv Ranjan, Raj Gaire, Ehsan Abbasnejad, Lizhe Wang, Albert Y. Zomaya
2017 IEEE Transactions on Emerging Topics in Computing  
in consistent definition of cloud elasticity rules; and ii) a distribution based admission controller which is able to efficiently admit or reject incoming queries based on probabilistic SLAs compliance  ...  Such resource estimation for processing continuous queries over streaming data is challenging due to: (i) uncertain stream arrival patterns, (ii) need to process different mixes of queries, and (iii) varying  ...  However, this approach is only a simple approximation of distribution based on a number of already collected query execution times.  ... 
doi:10.1109/tetc.2016.2597546 fatcat:mh4gm3zzlzbsvblburug3mgali

Remembrance of Inferences Past [article]

Ishita Dasgupta, Eric Schulz, Noah D. Goodman, Samuel J. Gershman
2017 bioRxiv   pre-print
When sequentially answering two related queries about natural scenes, participants' responses to the second query systematically depend on the structure of the first query.  ...  Using a cognitive load manipulation, we find evidence that people amortize summary statistics of previous inferences, rather than storing the entire distribution.  ...  This material is based upon work supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF-1231216.  ... 
doi:10.1101/231837 fatcat:kqgca26hivhx7cattbzwtvv6oq

A probabilistic model for assigning queries at the edge

Kostas Kolomvatsos, Christos Anagnostopoulos
2019 Computing  
The proposed scheme matches the characteristics of the incoming queries and edge nodes trying to conclude the optimal allocation.  ...  The aim is to support the goal of eliminating further the latency by allocating queries to nodes that exhibit a low load and high processing speed, thus, they can respond in the minimum time.  ...  Queries asking for analytics should be responded on top of data that 'match' to queries conditions.  ... 
doi:10.1007/s00607-019-00767-8 fatcat:unpkzhofknavlowtwx6e6plx64
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