Compute Pub Date : 2017-11-16 DOI: 10.1145/3140107.3140121

Swati Sharma, Rishabh Kaushal

{"title":"Energy Conserving Secure VM Allocation in Untrusted Cloud Computing Environment","authors":"Swati Sharma, Rishabh Kaushal","doi":"10.1145/3140107.3140121","DOIUrl":"https://doi.org/10.1145/3140107.3140121","url":null,"abstract":"Cloud computing is the latest buzz in most of the IT organizations which are witnessing a a trend of migration from traditional computing to cloud computing, thereby reducing their infrastructure cost and improving efficiency and performance. Cloud computing provides services through virtualization layer, which helps to execute more than one operating systems and applications on a single machine. Being a crucial part of cloud computing, virtualization layer faces major security threats, most challenging being an insider threat wherein attacker can either compromise existing virtual machines (VMs) or create rogue VMs. The objective of this work is to propose virtual machine (VM) allocation algorithm which operates in an untrusted cloud computing environment with non-trustworthy VMs. Our approach is based on the notion of trust. Lack of trust is modeled by either introducing faults or monitoring SLAs per host on which VMs are hosted. Detailed experiments considering varying cloud infrastructure and varying workloads are conducted using CloudSim. Results show that proposed algorithm works well in untrusted environment while at the same time is energy efficient and reduces the computational costs by decreasing the number of migrations and SLA violations.","PeriodicalId":435920,"journal":{"name":"Compute","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114565099","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: 0

Word Level Language Identification system for Konkani-English Code-Mixed Social Media Text (CMST) Konkani-English码混合社交媒体文本的词级语言识别系统(CMST)

Compute Pub Date : 2017-11-16 DOI: 10.1145/3140107.3140132

Akshata Phadte, R. Wagh

引用次数: 5

Stopword Removal: Why Bother? A Case Study on Verbose Queries 停止词删除:为什么要麻烦?详细查询的案例研究

Compute Pub Date : 2017-11-16 DOI: 10.1145/3140107.3140125

Kripabandhu Ghosh, A. Bhattacharya

引用次数: 6

Predicting Success of Bollywood Movies Using Machine Learning Techniques 用机器学习技术预测宝莱坞电影的成功

Compute Pub Date : 2017-11-16 DOI: 10.1145/3140107.3140126

Sameer Ranjan Jaiswal, Divyanshu Sharma

引用次数: 10

Measuring Similarity among Legal Court Case Documents 法院案件文书相似性的测度

Compute Pub Date : 2017-11-16 DOI: 10.1145/3140107.3140119

A. Mandal, Raktim Chaki, S. Saha, Kripabandhu Ghosh, Arindam Pal, Saptarshi Ghosh

{"title":"Measuring Similarity among Legal Court Case Documents","authors":"A. Mandal, Raktim Chaki, S. Saha, Kripabandhu Ghosh, Arindam Pal, Saptarshi Ghosh","doi":"10.1145/3140107.3140119","DOIUrl":"https://doi.org/10.1145/3140107.3140119","url":null,"abstract":"Computing the similarity between two legal documents is an important challenge in the Legal Information Retrieval domain. Efficient calculation of this similarity has useful applications in various tasks such as identifying relevant prior cases for a given case document. Prior works have proposed network-based and text-based methods for measuring similarity between legal documents. However, there are certain limitations in the prior methods. Network-based measures are not always meaningfully applicable since legal citation networks are usually very sparse. On the other hand, only primitive text-based similarity measures, such as TF-IDF based approaches, have been tried till date. In this work, we focus on improving text-based methodologies for computing the similarity between two legal documents. In addition to TF-IDF based measures, we use advanced similarity measures (such as topic modeling) and neural network models (such as word embeddings and document embeddings). We perform extensive experiments on a large dataset of Indian Supreme Court cases, and compare among various methodologies for measuring the textual similarity of legal documents. Our experiments show that embedding based approaches perform better than other approaches. We also demonstrate that the proposed embedding-based methodologies significantly outperforms a baseline hybrid methodology involving both network-based and text-based similarity.","PeriodicalId":435920,"journal":{"name":"Compute","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127744563","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: 60

VAANI: A Voice-based Authentication System for Linux using Dynamic Threshold and Positive Selection 基于动态阈值和正选择的Linux语音认证系统VAANI

Compute Pub Date : 2017-11-16 DOI: 10.1145/3140107.3140108

Subhomoy Dey, Kishore Kashyap

引用次数: 0

Multi-structured Data Analytics using Interactive Visualization to aid Business Decision Making 使用交互式可视化辅助业务决策的多结构数据分析

Compute Pub Date : 2017-11-16 DOI: 10.1145/3140107.3140118

Ishan Verma, Lokendra Singh

引用次数: 2

ParseIT: A Question-Answer based Tool to Learn Parsing Techniques ParseIT:一个基于问答的工具来学习解析技术

Compute Pub Date : 2017-02-02 DOI: 10.1145/3140107.3140123

Amey Karkare, Nimisha Agrawal