Runtime Performance

2012 ◽  
pp. 139-173
Author(s):  
Tom Barker
Keyword(s):  
Runtime Performance

scholarly journals An empirical evaluation of cost-based federated SPARQL query processing engines

Semantic Web ◽  
2021 ◽  
pp. 1-26
Author(s):  
Umair Qudus ◽  
Muhammad Saleem ◽  
Axel-Cyrille Ngonga Ngomo ◽  
Young-Koo Lee
Keyword(s):  
Query Processing ◽  
Detailed Analysis ◽  
Performance Metrics ◽  
Empirical Evaluation ◽  
Sparql Query ◽  
Evaluation Metrics ◽  
Future Cost ◽  
Query Plan ◽  
Fine Grained ◽  
Runtime Performance

Finding a good query plan is key to the optimization of query runtime. This holds in particular for cost-based federation engines, which make use of cardinality estimations to achieve this goal. A number of studies compare SPARQL federation engines across different performance metrics, including query runtime, result set completeness and correctness, number of sources selected and number of requests sent. Albeit informative, these metrics are generic and unable to quantify and evaluate the accuracy of the cardinality estimators of cost-based federation engines. To thoroughly evaluate cost-based federation engines, the effect of estimated cardinality errors on the overall query runtime performance must be measured. In this paper, we address this challenge by presenting novel evaluation metrics targeted at a fine-grained benchmarking of cost-based federated SPARQL query engines. We evaluate five cost-based federated SPARQL query engines using existing as well as novel evaluation metrics by using LargeRDFBench queries. Our results provide a detailed analysis of the experimental outcomes that reveal novel insights, useful for the development of future cost-based federated SPARQL query processing engines.

Coordinated management of power usage and runtime performance

2008 ◽  
Author(s):  
Malgorzata Steinder ◽  
Ian Whalley ◽  
James E. Hanson ◽  
Jeffrey O. Kephart
Keyword(s):  
Runtime Performance

scholarly journals JINDY: A java library to support invokedynamic

2014 ◽  
Vol 11 (1) ◽  
pp. 47-68 ◽  
Author(s):  
Patricia Conde ◽  
Francisco Ortin
Keyword(s):  
Virtual Machine ◽  
Programming Language ◽  
Java Virtual Machine ◽  
Memory Consumption ◽  
Java Programming ◽  
Abstraction Level ◽  
Java Platform ◽  
Runtime Performance ◽  
And Performance ◽  
Java Library

Java 7 has included the new invokedynamic opcode in the Java virtual machine. This new instruction allows the user to define method linkage at runtime. Once the link is established, the virtual machine performs its common optimizations, providing better runtime performance than reflection. However, this feature has not been offered at the abstraction level of the Java programming language. Since the functionality of the new opcode is not provided as a library, the existing languages in the Java platform can only use it at the assembly level. For this reason, we have developed the JINDY library that offers invokedynamic to any programming language in the Java platform. JINDY supports three modes of use, establishing a trade-off between runtime performance and flexibility. A runtime performance and memory consumption evaluation is presented. We analyze the efficiency of JINDY compared to reflection, the MethodHandle class in Java 7 and the Dynalink library. The memory and performance costs compared to the invokedynamic opcode are also measured.

scholarly journals eHMCOKE: an enhanced overlapping clustering algorithm for data analysis

2021 ◽  
Vol 10 (4) ◽  
pp. 2212-2222
Author(s):  
Alvincent E. Danganan ◽  
Edjie Malonzo De Los Reyes
Keyword(s):  
Data Analysis ◽  
Clustering Algorithm ◽  
Median Absolute Deviation ◽  
Accuracy Rate ◽  
Absolute Deviation ◽  
Improvement Rate ◽  
Overlapping Clustering ◽  
Overlapping Clusters ◽  
Runtime Performance

Improved multi-cluster overlapping k-means extension (IMCOKE) uses median absolute deviation (MAD) in detecting outliers in datasets makes the algorithm more effective with regards to overlapping clustering. Nevertheless, analysis of the applied MAD positioning was not considered. In this paper, the incorporation of MAD used to detect outliers in the datasets was analyzed to determine the appropriate position in identifying the outlier before applying it in the clustering application. And the assumption of the study was the size of the cluster and cluster that are close to each other can led to a higher runtime performance in terms of overlapping clusters. Therefore, additional parameters such as radius of clusters and distance between clusters are added measurements in the algorithm procedures. Evaluation was done through experimentations using synthetic and real datasets. The performance of the eHMCOKE was evaluated via F1-measure criterion, speed and percentage of improvement. Evaluation results revealed that the eHMCOKE takes less time to discover overlap clusters with an improvement rate of 22% and achieved the best performance of 91.5% accuracy rate via F1-measure in identifying overlapping clusters over the IMCOKE algorithm. These results proved that the eHMCOKE significantly outruns the IMCOKE algorithm on mosts of the test conducted.

Improved Affine Partition Algorithm for Compile-Time and Runtime Performance

2011 ◽  
Vol 17 (8) ◽  
pp. 1179-1191
Author(s):  
Yuan Xinyu ◽  
Li Ying ◽  
Deng Shuiguang ◽  
Cheng Jie
Keyword(s):  
Runtime Performance

Exploring the Runtime Performance of Knowledge Graph Embedding Methods

2021 ◽  
Author(s):  
Angelica S. Valeriani ◽  
Guido Walter Di Donato ◽  
Marco D. Santambrogio
Keyword(s):  
Graph Embedding ◽  
Knowledge Graph ◽  
Runtime Performance ◽  
Embedding Methods

scholarly journals An Android Inline Hooking Framework for the Securing Transmitted Data

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4201
Author(s):  
Yu-an Tan ◽  
Shuo Feng ◽  
Xiaochun Cheng ◽  
Yuanzhang Li ◽  
Jun Zheng
Keyword(s):  
Source Code ◽  
Control Flow ◽  
Security Policies ◽  
Unauthorized Access ◽  
Shared Objects ◽  
Android Applications ◽  
Runtime Performance ◽  
And Control

Information leaks can occur through many Android applications, including unauthorized access to sensors data. Hooking is an important technique for protecting Android applications and add security features to them even without its source code. Various hooking frameworks are developed to intercept events and process their own specific events. The hooking tools for Java methods are varied, however, the native hook has few methods. Besides, the commonly used Android hook frameworks cannot meet the requirement of hooking the native methods in shared libraries on non-root devices. Even though some approaches are able to hook these methods, they have limitations or are complicated to implement. In the paper, a feasible hooking approach for Android native methods is proposed and implemented, which does not need any modifications to both the Android framework and app’s code. In this approach, the method’s reference address is modified and control flow is redirected. Beyond that, this study combines this approach with VirtualXposed which aims to run it without root privileges. This hooking framework can be used to enforce security policies and monitor sensitive methods in shared objects. The evaluation of the scheme demonstrates its capability to perform hook operation without a significant runtime performance overhead on real devices and it is compatible and functional for the native hook.

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