Pub Date : 2014-12-15DOI: 10.1109/CloudCom.2014.32
Tram Truong Huu, C. Tham, D. Niyato
Mobile devices like smartphones have become the computing device of choice for many users, heralding the era of mobile computing. Many applications have been developed to run on mobile devices. However, despite the increased processing and wireless network speeds of mobile devices, their resources are still limited in terms of processing capacity and battery lifetime. Some applications, in particular computationally intensive ones such as multimedia processing, often require more resources than a mobile device can afford. To overcome this hurdle, we propose a mobile ad-hoc cloud in which a mobile device can access resources from other sources, such as nearby mobile devices, to share the workload. The difficulty that arises with this concept is the mobility of nearby devices, i.e. A neighbouring device may move out of range before it can communicate its results back to the source node. In this paper, we propose a workload distribution scheme among these nearby mobile devices that takes into account the randomness of the connection time between cooperating devices. In order to cope with this randomness, we adopt a multi-stage stochastic programming approach which is able to take posterior recourse actions to compensate for inaccurate predictions. Numerical studies and simulations were carried out to evaluate the performance of this scheme. The results show that the stochastic programming approach outperforms a naive scheme and a baseline scheme that only considers the average connection time.
{"title":"A Stochastic Workload Distribution Approach for an Ad Hoc Mobile Cloud","authors":"Tram Truong Huu, C. Tham, D. Niyato","doi":"10.1109/CloudCom.2014.32","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.32","url":null,"abstract":"Mobile devices like smartphones have become the computing device of choice for many users, heralding the era of mobile computing. Many applications have been developed to run on mobile devices. However, despite the increased processing and wireless network speeds of mobile devices, their resources are still limited in terms of processing capacity and battery lifetime. Some applications, in particular computationally intensive ones such as multimedia processing, often require more resources than a mobile device can afford. To overcome this hurdle, we propose a mobile ad-hoc cloud in which a mobile device can access resources from other sources, such as nearby mobile devices, to share the workload. The difficulty that arises with this concept is the mobility of nearby devices, i.e. A neighbouring device may move out of range before it can communicate its results back to the source node. In this paper, we propose a workload distribution scheme among these nearby mobile devices that takes into account the randomness of the connection time between cooperating devices. In order to cope with this randomness, we adopt a multi-stage stochastic programming approach which is able to take posterior recourse actions to compensate for inaccurate predictions. Numerical studies and simulations were carried out to evaluate the performance of this scheme. The results show that the stochastic programming approach outperforms a naive scheme and a baseline scheme that only considers the average connection time.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"23 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126812736","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}
Pub Date : 2014-12-15DOI: 10.1109/CloudCom.2014.65
R. Lea, Michael Blackstock
Cloud based Smart City hubs are an attractive approach to addressing some of the complex issues faced when deploying PaaS infrastructure for Smart Cities. In this paper we introduce the general notion of IoT hubs and then discuss our work to generalize our IoT hub as a Smart City PaaS. We briefly describe our approach and discuss our experiences deploying two cloud-based Smart City hubs, one in the UK and the other in Canada.
{"title":"City Hub: A Cloud-Based IoT Platform for Smart Cities","authors":"R. Lea, Michael Blackstock","doi":"10.1109/CloudCom.2014.65","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.65","url":null,"abstract":"Cloud based Smart City hubs are an attractive approach to addressing some of the complex issues faced when deploying PaaS infrastructure for Smart Cities. In this paper we introduce the general notion of IoT hubs and then discuss our work to generalize our IoT hub as a Smart City PaaS. We briefly describe our approach and discuss our experiences deploying two cloud-based Smart City hubs, one in the UK and the other in Canada.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130643160","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}
Pub Date : 2014-12-15DOI: 10.1109/CloudCom.2014.21
M. Eldred, C. Adams, Alice Good
The literature on cloud computing has been dominated by examples and issues from small to mid-size companies. This paper reports on a large scale cloud pilot project within the petrochemical industry, perhaps one of the biggest examples of cloud computing pushing the boundaries of what you can do with sensitive data. The study aimed to explore the challenges and practicalities of initiating and evaluating cloud projects. Action research is used to examine the nuances throughout a million dollar cloud pilot which lasted over one year from start to finish. The study was able to identify some emergent issues affecting initiation, implementation, technical security challenges and evaluation of a significant change to the security provision of critical data within a large international company affecting many stakeholder groups. One emergent theme was that of the 'political cloud' which was represented by a clash between organisational behavior, the perception of security and internal politics within an organisation, much like the fault lines between tectonic plates. The paper hopes to make contribution by modeling some of the complexities of cloud computing data security and trust challenge by providing insights on the trust and protection of data within companies, particularly large international companies.
{"title":"Trust Challenges in a High Performance Cloud Computing Project","authors":"M. Eldred, C. Adams, Alice Good","doi":"10.1109/CloudCom.2014.21","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.21","url":null,"abstract":"The literature on cloud computing has been dominated by examples and issues from small to mid-size companies. This paper reports on a large scale cloud pilot project within the petrochemical industry, perhaps one of the biggest examples of cloud computing pushing the boundaries of what you can do with sensitive data. The study aimed to explore the challenges and practicalities of initiating and evaluating cloud projects. Action research is used to examine the nuances throughout a million dollar cloud pilot which lasted over one year from start to finish. The study was able to identify some emergent issues affecting initiation, implementation, technical security challenges and evaluation of a significant change to the security provision of critical data within a large international company affecting many stakeholder groups. One emergent theme was that of the 'political cloud' which was represented by a clash between organisational behavior, the perception of security and internal politics within an organisation, much like the fault lines between tectonic plates. The paper hopes to make contribution by modeling some of the complexities of cloud computing data security and trust challenge by providing insights on the trust and protection of data within companies, particularly large international companies.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130667983","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}
Pub Date : 2014-12-15DOI: 10.1109/CloudCom.2014.161
João Loff, J. Garcia
Elasticity is a key feature in cloud computing, and perhaps what distinguishes it from other computing paradigms. Despite the advantages of elasticity, realizing its full potential is hard due to multiple challenges stemming from the need to estimate workload demand. A desirable solution would require predicting system workload and allocating resources a priori, i.e., A predictive approach. Instead, what is mainly available are reactive solutions, requiring difficult parameter tuning. Since each Cloud Provider (CP) has its own implementation idiosyncrasies, it's impossible for developers to: (i) learn only about one platform and re-use that knowledge in others, (ii) migrate developed elasticity solutions between different CPs, and (iii) to develop reusable predictive elasticity rules or algorithms. This paper makes three contributions to provide an effective elasticity environment. First, Vadara, a totally generic elasticity framework, that transparently connects and abstracts several CPs API behaviour, and enables the use of pluggable CP-agnostic elasticity strategies. Second, it presents a predictive workload forecasting approach, which ensembles several individual forecasting methods, and introduces a padding system based on the most recent prediction errors for both under- and over-provisioning. Finally, results show (1) Vadara's successful connection to well-known CPs, (2) the improvements made regarding under- and over-provisioning due to our padding system, and (3) the effectiveness of our ensemble forecasting technique.
{"title":"Vadara: Predictive Elasticity for Cloud Applications","authors":"João Loff, J. Garcia","doi":"10.1109/CloudCom.2014.161","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.161","url":null,"abstract":"Elasticity is a key feature in cloud computing, and perhaps what distinguishes it from other computing paradigms. Despite the advantages of elasticity, realizing its full potential is hard due to multiple challenges stemming from the need to estimate workload demand. A desirable solution would require predicting system workload and allocating resources a priori, i.e., A predictive approach. Instead, what is mainly available are reactive solutions, requiring difficult parameter tuning. Since each Cloud Provider (CP) has its own implementation idiosyncrasies, it's impossible for developers to: (i) learn only about one platform and re-use that knowledge in others, (ii) migrate developed elasticity solutions between different CPs, and (iii) to develop reusable predictive elasticity rules or algorithms. This paper makes three contributions to provide an effective elasticity environment. First, Vadara, a totally generic elasticity framework, that transparently connects and abstracts several CPs API behaviour, and enables the use of pluggable CP-agnostic elasticity strategies. Second, it presents a predictive workload forecasting approach, which ensembles several individual forecasting methods, and introduces a padding system based on the most recent prediction errors for both under- and over-provisioning. Finally, results show (1) Vadara's successful connection to well-known CPs, (2) the improvements made regarding under- and over-provisioning due to our padding system, and (3) the effectiveness of our ensemble forecasting technique.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124384767","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}
Pub Date : 2014-12-15DOI: 10.1109/CloudCom.2014.77
Ryota Kawashima, H. Matsuo
Network Virtualization Overlays (NVO3) provides multi-tenancy services in cloud data centers with existing networking equipment. IP tunneling is an essential technology to logically separate each virtual traffic, in particular, Stateless Transport Tunneling (STT) is considered to achieve better performance using TCP Segmentation Offload (TSO) feature. Currently, there is no openly available implementation of STT, and its implementation and performance characteristics have not been studied in academic field so far. We have therefore implemented STT protocol and conducted performance evaluation by comparing with VXLAN protocol. In practice, the STT implementation has been done using a virtual NIC offloading framework, co-virtual switch (CVSW). CVSW is a software component that extends virtual NICs and provides high-level packet processing framework such as Open Flow Match-Action. In this paper, we describe implementation details of STT and performance evaluation results from various perspectives. The results showed that the actual performance of STT was almost equal to non-tunneling VM-to-VM communication and was two-times higher than that of VXLAN. Furthermore, we clarify the high-performance nature of STT is brought from both byte-stream characteristic of TCP and Generic Receive Offload (GRO) feature rather than widely believed TSO.
{"title":"Implementation and Performance Analysis of STT Tunneling Using vNIC Offloading Framework (CVSW)","authors":"Ryota Kawashima, H. Matsuo","doi":"10.1109/CloudCom.2014.77","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.77","url":null,"abstract":"Network Virtualization Overlays (NVO3) provides multi-tenancy services in cloud data centers with existing networking equipment. IP tunneling is an essential technology to logically separate each virtual traffic, in particular, Stateless Transport Tunneling (STT) is considered to achieve better performance using TCP Segmentation Offload (TSO) feature. Currently, there is no openly available implementation of STT, and its implementation and performance characteristics have not been studied in academic field so far. We have therefore implemented STT protocol and conducted performance evaluation by comparing with VXLAN protocol. In practice, the STT implementation has been done using a virtual NIC offloading framework, co-virtual switch (CVSW). CVSW is a software component that extends virtual NICs and provides high-level packet processing framework such as Open Flow Match-Action. In this paper, we describe implementation details of STT and performance evaluation results from various perspectives. The results showed that the actual performance of STT was almost equal to non-tunneling VM-to-VM communication and was two-times higher than that of VXLAN. Furthermore, we clarify the high-performance nature of STT is brought from both byte-stream characteristic of TCP and Generic Receive Offload (GRO) feature rather than widely believed TSO.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115851917","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}
Pub Date : 2014-12-15DOI: 10.1109/CLOUDCOM.2014.46
Cristina Montañola-Sales, J. Casanovas, B. Onggo, Zengxiang Li
Agent-based modeling is one of the promising modeling tools that can be used in the study of population dynamics. Two of the main obstacles hindering the use of agent-based simulation in practice are its scalability when the analysis requires large-scale models as in policy research, and its ease-of-use especially for users with no programming experience. While there has been a significant work on the scalability issue, ease-of-use aspect has not been addressed in the same intensity. This paper presents a graphical user interface designed for a simulation tool which allows modelers with no programming background to specify agent-based demographic models and run them on parallel environments. The interface eases the definition of models to describe individual and group dynamics processes with both qualitative and quantitative data. The main advantage is to allow users to transparently run the models on high performance computing infrastructures.
{"title":"A User Interface for Large-Scale Demographic Simulation","authors":"Cristina Montañola-Sales, J. Casanovas, B. Onggo, Zengxiang Li","doi":"10.1109/CLOUDCOM.2014.46","DOIUrl":"https://doi.org/10.1109/CLOUDCOM.2014.46","url":null,"abstract":"Agent-based modeling is one of the promising modeling tools that can be used in the study of population dynamics. Two of the main obstacles hindering the use of agent-based simulation in practice are its scalability when the analysis requires large-scale models as in policy research, and its ease-of-use especially for users with no programming experience. While there has been a significant work on the scalability issue, ease-of-use aspect has not been addressed in the same intensity. This paper presents a graphical user interface designed for a simulation tool which allows modelers with no programming background to specify agent-based demographic models and run them on parallel environments. The interface eases the definition of models to describe individual and group dynamics processes with both qualitative and quantitative data. The main advantage is to allow users to transparently run the models on high performance computing infrastructures.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"788 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134603459","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}
Pub Date : 2014-12-15DOI: 10.1109/CloudCom.2014.134
R. Mohamad, D. Kolovos, R. Paige
Analysis of resource usage and precise correlation with the workload that triggered it is essential in order to conduct capacity planning in computing environments. Virtualisation enables resource optimisation and is widely used in grid, cluster and cloud computing. We present an automated approach for resource usage analysis in a virtualised environment that can support capacity planning for web applications. The approach uses Domain Specific Modelling Languages (DSMLs) and model management techniques, which support tool interoperation and provide precise ways for describing resource and request logs and requirements, and automatically generate different outputs that feed into the capacity planning process. The approach is demonstrated using a proof-of-concept example involving a media streaming web application, and the results of the analysis are presented and discussed.
为了在计算环境中进行容量规划，分析资源使用情况以及与触发它的工作负载之间的精确关联是必不可少的。虚拟化可以实现资源优化，并广泛应用于网格、集群和云计算。我们提出了一种在虚拟化环境中进行资源使用分析的自动化方法，该方法可以支持web应用程序的容量规划。该方法使用领域特定建模语言(Domain Specific modeling Languages, dsml)和模型管理技术，它们支持工具互操作，并为描述资源、请求日志和需求提供精确的方法，并自动生成不同的输出，这些输出提供给容量规划过程。该方法通过一个涉及媒体流web应用程序的概念验证示例进行了演示，并给出了分析结果并进行了讨论。
{"title":"Resource Requirement Analysis for Web Applications Running in a Virtualised Environment","authors":"R. Mohamad, D. Kolovos, R. Paige","doi":"10.1109/CloudCom.2014.134","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.134","url":null,"abstract":"Analysis of resource usage and precise correlation with the workload that triggered it is essential in order to conduct capacity planning in computing environments. Virtualisation enables resource optimisation and is widely used in grid, cluster and cloud computing. We present an automated approach for resource usage analysis in a virtualised environment that can support capacity planning for web applications. The approach uses Domain Specific Modelling Languages (DSMLs) and model management techniques, which support tool interoperation and provide precise ways for describing resource and request logs and requirements, and automatically generate different outputs that feed into the capacity planning process. The approach is demonstrated using a proof-of-concept example involving a media streaming web application, and the results of the analysis are presented and discussed.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"15 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132982950","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}
Pub Date : 2014-12-15DOI: 10.1109/CloudCom.2014.36
Akane Koto, K. Kono, H. Yamada
Live migration of virtual machines (VMs) is widely used for managing cloud computing platforms. However, live migration causes performance interference on cloud services running on migrated VMs or other VMs collocating with the services during or after migration. Although migration time and downtime are mainly for measuring live migration performance, cloud administrators must take live migration-performance interference into consideration. Since many live migration policies and implementations have been proposed recently, cloud administrators are required to choose an appropriate migration policy and/or implementation. For this study, we conducted several experiments and compared several migration methods quantitatively. According to our experimental results, we reveal the trade-offs of each migration policy and implementation that are not just related to downtime and migration time and present guidelines for selecting appropriate policies and implementations.
{"title":"A Guideline for Selecting Live Migration Policies and Implementations in Clouds","authors":"Akane Koto, K. Kono, H. Yamada","doi":"10.1109/CloudCom.2014.36","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.36","url":null,"abstract":"Live migration of virtual machines (VMs) is widely used for managing cloud computing platforms. However, live migration causes performance interference on cloud services running on migrated VMs or other VMs collocating with the services during or after migration. Although migration time and downtime are mainly for measuring live migration performance, cloud administrators must take live migration-performance interference into consideration. Since many live migration policies and implementations have been proposed recently, cloud administrators are required to choose an appropriate migration policy and/or implementation. For this study, we conducted several experiments and compared several migration methods quantitatively. According to our experimental results, we reveal the trade-offs of each migration policy and implementation that are not just related to downtime and migration time and present guidelines for selecting appropriate policies and implementations.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126575767","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}
Pub Date : 2014-12-15DOI: 10.1109/CloudCom.2014.70
X. Yan, W. Zhou, Yun Gao, Zhang Zhang, Jizhong Han, Ge Fu
With the popularity of various software applications in cloud computing, software exception becomes an important issue. How to detect the exceptions more quickly seems to be crucial for the software service company. To solve the above problem, this paper presents an efficient log anomaly detection method named PADM (Page Rank-based Anomaly Detection Method) based on the graph computing algorithm. In this method, the logs are transformed into a graph to represent the complex relationship between the log records, then we design an extended Page Rank algorithm based on the graph to get the importance score for each log. After that, we compare the scores to that of the training logs to determine whether they are abnormal or not. Finally, we compare PADM with other anomaly detection methods on the real logs, and the results show that it outperforms the currently widely used mechanisms with higher accuracy, lower time complexity and better scalability.
随着云计算中各种软件应用的普及，软件异常成为一个重要的问题。对于这家软件服务公司来说，如何更快地发现异常似乎至关重要。为了解决上述问题，本文提出了一种基于图计算算法的高效日志异常检测方法PADM (Page rank based anomaly detection method)。该方法将日志转换成一个图来表示日志记录之间的复杂关系，然后在此图的基础上设计一个扩展的Page Rank算法来获得每条日志的重要性评分。之后，我们将分数与训练日志的分数进行比较，以确定它们是否异常。最后，将PADM与其他异常检测方法在真实日志上进行了比较，结果表明，PADM具有更高的精度、更低的时间复杂度和更好的可扩展性，优于目前广泛使用的机制。
{"title":"PADM: Page Rank-Based Anomaly Detection Method of Log Sequences by Graph Computing","authors":"X. Yan, W. Zhou, Yun Gao, Zhang Zhang, Jizhong Han, Ge Fu","doi":"10.1109/CloudCom.2014.70","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.70","url":null,"abstract":"With the popularity of various software applications in cloud computing, software exception becomes an important issue. How to detect the exceptions more quickly seems to be crucial for the software service company. To solve the above problem, this paper presents an efficient log anomaly detection method named PADM (Page Rank-based Anomaly Detection Method) based on the graph computing algorithm. In this method, the logs are transformed into a graph to represent the complex relationship between the log records, then we design an extended Page Rank algorithm based on the graph to get the importance score for each log. After that, we compare the scores to that of the training logs to determine whether they are abnormal or not. Finally, we compare PADM with other anomaly detection methods on the real logs, and the results show that it outperforms the currently widely used mechanisms with higher accuracy, lower time complexity and better scalability.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133699403","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}
Pub Date : 2014-12-15DOI: 10.1109/CloudCom.2014.162
Y. Demchenko, Emanuel Gruengard, S. Klous
This paper presents current results and ongoing work to develop effective educational courses on the Big Data (BD) and Data Intensive Science and Technologies (DIST) that is been done at the University of Amsterdam in cooperation with KPMG and by the Laureate Online Education (online partner of the University of Liverpool). The paper introduces the main Big Data concepts: multicomponent Big Data definition and Big Data Architecture Framework that provide the basis for defining the course structure and Common Body of Knowledge for Data Science and Big Data technology domains. The paper presents details on approach, learning model, and course content for two courses at the Laureate Online Education/University of Liverpool and at the University of Amsterdam. The paper also provides background information about existing initiatives and activities related to information exchange and coordination on developing educational materials and programs on Big Data, Data Science, and Research Data Management.
{"title":"Instructional Model for Building Effective Big Data Curricula for Online and Campus Education","authors":"Y. Demchenko, Emanuel Gruengard, S. Klous","doi":"10.1109/CloudCom.2014.162","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.162","url":null,"abstract":"This paper presents current results and ongoing work to develop effective educational courses on the Big Data (BD) and Data Intensive Science and Technologies (DIST) that is been done at the University of Amsterdam in cooperation with KPMG and by the Laureate Online Education (online partner of the University of Liverpool). The paper introduces the main Big Data concepts: multicomponent Big Data definition and Big Data Architecture Framework that provide the basis for defining the course structure and Common Body of Knowledge for Data Science and Big Data technology domains. The paper presents details on approach, learning model, and course content for two courses at the Laureate Online Education/University of Liverpool and at the University of Amsterdam. The paper also provides background information about existing initiatives and activities related to information exchange and coordination on developing educational materials and programs on Big Data, Data Science, and Research Data Management.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128862181","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}
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