2018 Eleventh International Conference on Contemporary Computing (IC3)最新文献_第3页

Early Detection of Distributed Denial of Service Attack in Era of Software-Defined Network 软件定义网络时代分布式拒绝服务攻击的早期检测

2018 Eleventh International Conference on Contemporary Computing (IC3) Pub Date : 2018-08-01 DOI: 10.1109/IC3.2018.8530546

B. Joshi, Nitin Joshi, M. Joshi

引用次数: 4

Empirical Evidence of Heuristic and Cost Based Query Optimizations in Relational Databases 关系型数据库中启发式和基于成本的查询优化的经验证据

2018 Eleventh International Conference on Contemporary Computing (IC3) Pub Date : 2018-08-01 DOI: 10.1109/IC3.2018.8530467

S. Mehta, Parmeet Kaur, P. Lodhi, O. Mishra

引用次数: 3

An Intelligent Task Scheduling Approach for Cloud Using IPSO and A* Search Algorithm 基于IPSO和A*搜索算法的云智能任务调度方法

2018 Eleventh International Conference on Contemporary Computing (IC3) Pub Date : 2018-08-01 DOI: 10.1109/IC3.2018.8530545

B. P. Kavin, S. Ganapathy, A. Kannan

{"title":"An Intelligent Task Scheduling Approach for Cloud Using IPSO and A* Search Algorithm","authors":"B. P. Kavin, S. Ganapathy, A. Kannan","doi":"10.1109/IC3.2018.8530545","DOIUrl":"https://doi.org/10.1109/IC3.2018.8530545","url":null,"abstract":"Cloud computing technology is playing a vital role in this fast internet era for transferring, storing and accessing the large volume of confidential data which are official, medical and military. Efficient techniques for searching and processing the cloud data are essential for providing better service to the cloud users. For the fast processing and searching the data, many techniques were proposed by various researchers in the past. However, those techniques are not working in better results in cloud services. In a heterogeneous environment, achieving higher efficiency is an important issue in task scheduling. To solve this problem, many evolutionary algorithms have been adopted in the past. Even though it is a Nondeterministic Polynomial-hard problem, the local search algorithms are integrated for increasing convergence speed in population-based algorithms. In this paper, we propose a new task scheduling approach which combines an incremental particle swarm optimization and A * search algorithm for effective task scheduling. Moreover, the current particle swarm optimization algorithms and the heuristic algorithms gained in results on random and scientific Directed Acyclic Graph. The experiments show that the performance of the proposed approach is better when it is compared with the existing task scheduling approaches.","PeriodicalId":118388,"journal":{"name":"2018 Eleventh International Conference on Contemporary Computing (IC3)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131074134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Requirement Risk Prioritization Using Analytic Hierarchy Process: A Gateway to Identify Risky Requirements 用层次分析法确定需求风险优先级:识别风险需求的一种途径

2018 Eleventh International Conference on Contemporary Computing (IC3) Pub Date : 2018-08-01 DOI: 10.1109/IC3.2018.8530569

Priyanka Chandani, Chetna Gupta

引用次数: 6

Machine Learning Based Framework to Predict Performance Evaluation of On-Chip Networks 基于机器学习的片上网络性能预测框架

2018 Eleventh International Conference on Contemporary Computing (IC3) Pub Date : 2018-08-01 DOI: 10.1109/IC3.2018.8530505

Anil Kumar, B. Talawar

{"title":"Machine Learning Based Framework to Predict Performance Evaluation of On-Chip Networks","authors":"Anil Kumar, B. Talawar","doi":"10.1109/IC3.2018.8530505","DOIUrl":"https://doi.org/10.1109/IC3.2018.8530505","url":null,"abstract":"Chip Multiprocessors(CMPs) and Multiprocessor System-on-Chips(MPSoCs) are meeting the ever increasing demand for high performance in processing large scale data and applications. There is a corresponding increase in the volume and frequency of traffic in the Network-on-Chip(NoC) architectures like CMPs and SoCs. NoC performance parameters like network latency, flit latency and hop count are critical measures which directly influence the overall performance of the architecture and execution time of the application. Unfortunately, cycle-accurate software simulators become slow for interactive use with an increase in architectural size of NoC. In order to provide the chip designer with an efficient framework for accurate measurements of NoC performance parameters, we propose a Machine Learning(ML) framework. Which is designed using different ML regression algorithms like Support Vector Regression(SVR) with different kernels and Artificial Neural Networks(ANN) with different activation functions. The proposed learning framework can be used to analyze the performance parameters of Mesh and Torus based NoC architectures. Results obtained are compared against the widely used cycle-accurate Booksim simulator. Experiments were conducted by variables like topology size from $2times 2$ to $30times 30$ with different virtual channels, traffic patterns and injection rates. The framework showed an approximate prediction error of 5% to 8% and overall minimum speedup of $1500times$ to $2000times$.","PeriodicalId":118388,"journal":{"name":"2018 Eleventh International Conference on Contemporary Computing (IC3)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133430976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Audio Acoustic Features Based Tagging and Comparative Analysis of its Classifications 基于声学特征的标记及其分类比较分析

2018 Eleventh International Conference on Contemporary Computing (IC3) Pub Date : 2018-08-01 DOI: 10.1109/IC3.2018.8530512

Somya Goel, Raghav Pangasa, Suma Dawn, Anuja Arora

引用次数: 4

An Overview of Pixel Value Differencing Based Data Hiding Techniques 基于像素值差异的数据隐藏技术综述

2018 Eleventh International Conference on Contemporary Computing (IC3) Pub Date : 2018-08-01 DOI: 10.1109/IC3.2018.8530673

Akanksha Singh, Mukesh Rawat, A. Shukla, Amod Kumar, Balvinder Singh

引用次数: 1

Determination of Optimal Thread Pool for Cloud Based Concurrent Enhanced No-Escape Search 基于云的并发增强无escape搜索的最优线程池确定

2018 Eleventh International Conference on Contemporary Computing (IC3) Pub Date : 2018-08-01 DOI: 10.1109/IC3.2018.8530645

Harshit Gujral, Abhinav Sharma, S. Mittal

{"title":"Determination of Optimal Thread Pool for Cloud Based Concurrent Enhanced No-Escape Search","authors":"Harshit Gujral, Abhinav Sharma, S. Mittal","doi":"10.1109/IC3.2018.8530645","DOIUrl":"https://doi.org/10.1109/IC3.2018.8530645","url":null,"abstract":"In this era of high demand for cloud-computing, concurrent and high-performance processing is the viable option to enhance performance and use available resources efficiently. Thread pool architecture is widely implemented in order to improve resource utilization and enhance performance. Studies in this field suggest that Thread pool size is mostly determined by heuristics, trials, or practical experience. This process lacks precision and theoretical justification. In this paper, a novel Hyperbola-based Thread-Pool Analysis (HTA) technique for determining optimal Thread Pool size by considering available bandwidth (upload/download speed) and workload (file-size) has been proposed for any cloud-based concurrent process. Here, HTA has been developed in the context of No-Escape Search (NES), a cloud-based content indexing and search system, proposed by authors in an earlier work. Results of HTA indicate an accuracy of 97.63% in estimation of optimal thread pool size. Incorporating HTA with No-Escape Search resulted a significant decrease in insertion time by 2236 folds and retrieval time by 1747 folds. Additionally, this paper also presents design of enhanced NES with features like pictorial representation of files for the visual summary, more efficient deletion algorithm using lazy delete and duplicate files detection in order to ensure efficient indexing.","PeriodicalId":118388,"journal":{"name":"2018 Eleventh International Conference on Contemporary Computing (IC3)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127006741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Framework for Freight Truck Return-Trip Assignment System 货车回程分配系统框架

2018 Eleventh International Conference on Contemporary Computing (IC3) Pub Date : 2018-08-01 DOI: 10.1109/IC3.2018.8530500

Sumit Mishra, Vishal Singh, D. Bhattacharya

引用次数: 1

Modeling Recommendation System for Real Time Analysis of Social Media Dynamics 面向社交媒体动态实时分析的建模推荐系统

2018 Eleventh International Conference on Contemporary Computing (IC3) Pub Date : 2018-08-01 DOI: 10.1109/IC3.2018.8530458

Shipra Goel, Muskan Banthia, Adwitiya Sinha

引用次数: 4