2015 IEEE Fourth Symposium on Network Cloud Computing and Applications (NCCA)最新文献

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Exploiting Classes of Virtual Machines for Scalable IaaS Cloud Management 利用虚拟机类进行可扩展的IaaS云管理
C. Canali, R. Lancellotti
{"title":"Exploiting Classes of Virtual Machines for Scalable IaaS Cloud Management","authors":"C. Canali, R. Lancellotti","doi":"10.1109/NCCA.2015.13","DOIUrl":"https://doi.org/10.1109/NCCA.2015.13","url":null,"abstract":"A major challenge of IaaS cloud data centers is the placement of a huge number of Virtual Machines (VMs) over a physical infrastructure with a high number of nodes. The VMs placement process must strive to reduce as much as possible the number of physical nodes to improve management efficiency, reduce energy consumption and guarantee economical savings. However, since each VM is considered as a black box with independent characteristics, the VMs placement task presents scalability issues due to the amount of involved data and to the resulting number of constraints in the underlying optimization problem. For large data centers, this condition often leads to the impossibility to reach an optimal solution for VMs placement. Existing solutions typically exploit heuristics or simplified formulations to solve the placement problem, at the price of possibly sub-optimal solutions. We propose an innovative VMs placement technique, namely Class-Based, that takes advantage from existing solutions to automatically group VMs showing similar behavior. The Class-Based technique solves a placement-problem that considers only some representatives for each class, and that can be replicated as a building block to solve the global VMs placement problem. Our experiments demonstrate that the proposed technique is viable and can significantly improve the scalability of the VMs placement in IaaS Cloud systems with respect to existing alternatives.","PeriodicalId":309782,"journal":{"name":"2015 IEEE Fourth Symposium on Network Cloud Computing and Applications (NCCA)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124810444","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: 18
Experiments with Smart Workload Allocation to Cloud Servers 智能工作负载分配到云服务器的实验
Lan Wang, E. Gelenbe
{"title":"Experiments with Smart Workload Allocation to Cloud Servers","authors":"Lan Wang, E. Gelenbe","doi":"10.1109/NCCA.2015.15","DOIUrl":"https://doi.org/10.1109/NCCA.2015.15","url":null,"abstract":"We present experiments that compare three on-line real time techniques for task allocation to different cloud servers: an adaptive random neural network (RNN) based on reinforcement algorithm, an algorithm based on \"sensible routing'', one which uses a simple analytical model to select the server is estimated to give the best response as a function of workload, and round-robin task allocation. Measurements indicate that the RNN based algorithm can make accurate decisions when it exploits frequent measurement updates.","PeriodicalId":309782,"journal":{"name":"2015 IEEE Fourth Symposium on Network Cloud Computing and Applications (NCCA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131131484","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: 14
The Network Perspective of Cloud Security 云安全的网络视角
Fabio Pierazzi, Andrea Balboni, Alessandro Guido, Mirco Marchetti
{"title":"The Network Perspective of Cloud Security","authors":"Fabio Pierazzi, Andrea Balboni, Alessandro Guido, Mirco Marchetti","doi":"10.1109/NCCA.2015.21","DOIUrl":"https://doi.org/10.1109/NCCA.2015.21","url":null,"abstract":"The cloud computing paradigm has become really popular, and its adoption is constantly increasing. Hence, also network activities and security alerts related to cloud services are increasing and are likely to become even more relevant in the upcoming years. In this paper, we propose the first characterization of real security alerts related to cloud activities and generated by a network sensor at the edge of a large network environment over several months. Results show that the characteristics of cloud security alerts differ from those that are not related to cloud activities. Moreover, alerts related to different cloud providers exhibit peculiar and different behaviors that can be identified through temporal analyses. The methods and results proposed in this paper are useful as a basis for the design of novel algorithms for the automatic analysis of cloud security alerts, that can be aimed at forecasting, prioritization, anomaly and state-change detection.","PeriodicalId":309782,"journal":{"name":"2015 IEEE Fourth Symposium on Network Cloud Computing and Applications (NCCA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133096952","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: 1
Digital Library Recommender System on Hadoop 基于Hadoop的数字图书馆推荐系统
A. Ismail, Haytham Tawfeek al Feel
{"title":"Digital Library Recommender System on Hadoop","authors":"A. Ismail, Haytham Tawfeek al Feel","doi":"10.1109/NCCA.2015.27","DOIUrl":"https://doi.org/10.1109/NCCA.2015.27","url":null,"abstract":"DBLP that is considered a digital repository of a massive amount of scientific papers does not have an easy and scalable way for users to find what they need. Our paper introduces a digital library recommender system named DLRS that facilitates the searching process in big data environment based on Hadoop and Hive-Ql as a query engine using MapReduce parallel programming framework.","PeriodicalId":309782,"journal":{"name":"2015 IEEE Fourth Symposium on Network Cloud Computing and Applications (NCCA)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131303064","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: 6
Towards Practical Homomorphic Encryption in Cloud Computing 云计算中实用的同态加密
Adil Bouti, J. Keller
{"title":"Towards Practical Homomorphic Encryption in Cloud Computing","authors":"Adil Bouti, J. Keller","doi":"10.1109/NCCA.2015.20","DOIUrl":"https://doi.org/10.1109/NCCA.2015.20","url":null,"abstract":"Secure computing in clouds faces many challenges related to data confidentiality and integrity. Classical security models focus on securing data from outside attacks, e.g. from other cloud users. Yet, breach of data confidentiality by the cloud provider has received far less attention. In previous work, we presented a protocol to delegate computations into clouds, providing security against other cloud users and cloud providers through encrypted data. The protocol is based on homomorphic properties of encryption algorithms. However,that protocol was only practical in certain circumstances. In the present paper we introduce some practical extensions to our algorithm to improve its efficiency. Additionally we extend the algorithm to support multiparty computation while preserving its homomorphic properties. We then show how these optimization blocks can be used for applying the scheme to efficient face recognition using Eigenface recognition algorithm.","PeriodicalId":309782,"journal":{"name":"2015 IEEE Fourth Symposium on Network Cloud Computing and Applications (NCCA)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122033365","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: 11
A Generic Architecture for Scalable and Highly Available Content Serving Applications in the Cloud 用于云中可扩展和高可用性内容服务应用程序的通用架构
Evie Kassela, I. Konstantinou, N. Koziris
{"title":"A Generic Architecture for Scalable and Highly Available Content Serving Applications in the Cloud","authors":"Evie Kassela, I. Konstantinou, N. Koziris","doi":"10.1109/NCCA.2015.22","DOIUrl":"https://doi.org/10.1109/NCCA.2015.22","url":null,"abstract":"The cloud computing paradigm allows service providers to offer scalable and highly available applications to their end users. Typical cases where this is required are content serving applications, where a large number of connected users manage arbitrary data amounts. In the Big Data era, where the amount of information that is being produced and consumed grows exponentially, centralized legacy approaches are inefficient, as they cannot adequately scale according to the number of connected users or the dataset sizes. In these cases, an efficient cloudification of content serving applications is required in order to benefit from the cloud's offerings. In this work, we present a generic architecture that can be used by almost any content serving application in order to offer scalable and highly available data management operations to their users by employing cloud management techniques. We describe the architectural blocks of our approach along with how they can be efficiently deployed in a cloud environment. We document our experiences with an actual deployment of a typical content serving application over ~okeanos, an Openstack compatible public cloud service. We describe the open source frameworks that we have selected from a plethora of existing tools, we justify our choices and we describe our initial observations during their operation. We give a detailed overview of how we installed and configured these systems to achieve high availability and scalability in a public cloud setting. Finally, we document our initial performance evaluation where we showcase the system's ability to handle increasing workloads by elastically scaling its resources.","PeriodicalId":309782,"journal":{"name":"2015 IEEE Fourth Symposium on Network Cloud Computing and Applications (NCCA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115593146","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: 1
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