Pub Date : 2016-08-01DOI: 10.1109/W-FiCloud.2016.44
Takamitsu Shioi, K. Hatano
Database systems have recently utilized both row-and a column-oriented storage systems, also termed as hybrid storage, as their storage devices for large scale data management. The hybrid storage based database systems should ideally be operated on distributed computing environments for query optimization, however, studies on query optimization of such database systems are not available in literature. Therefore, the selection of the storage type and the accurate estimation of query workload are critical factors for efficient query processing on distributed computing environments. In this paper, we describe a novel storage selection method of a RDBMS with a column-oriented storage function, which is a type of DBMSs with the hybrid storage, on distributed computing environments. Our storage selection method is designed for efficient query processing based on rule-and cost-based optimization in the research field of RDBMS, and it can help to improve query optimization of RDBMSs with the hybrid storage.
{"title":"Rule- and Cost-Based Optimization of OLAP Workloads on Distributed RDBMS with Column-Oriented Storage Function","authors":"Takamitsu Shioi, K. Hatano","doi":"10.1109/W-FiCloud.2016.44","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.44","url":null,"abstract":"Database systems have recently utilized both row-and a column-oriented storage systems, also termed as hybrid storage, as their storage devices for large scale data management. The hybrid storage based database systems should ideally be operated on distributed computing environments for query optimization, however, studies on query optimization of such database systems are not available in literature. Therefore, the selection of the storage type and the accurate estimation of query workload are critical factors for efficient query processing on distributed computing environments. In this paper, we describe a novel storage selection method of a RDBMS with a column-oriented storage function, which is a type of DBMSs with the hybrid storage, on distributed computing environments. Our storage selection method is designed for efficient query processing based on rule-and cost-based optimization in the research field of RDBMS, and it can help to improve query optimization of RDBMSs with the hybrid storage.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129782365","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 : 2016-08-01DOI: 10.1109/W-FiCloud.2016.29
Hamad Al-Mohannadi, Q. A. K. Mirza, A. P. Namanya, I. Awan, A. Cullen, Jules Pagna Disso
Cyber attack is a sensitive issue in the world of Internet security. Governments and business organisations around the world are providing enormous effort to secure their data. They are using various types of tools and techniques to keep the business running, while adversaries are trying to breach security and send malicious software such as botnets, viruses, trojans etc., to access valuable data. Everyday the situation is getting worse because of new types of malware emerging to attack networks. It is important to understand those attacks both before and after they happen in order to provide better security to our systems. Understanding attack models provide more insight into network vulnerability, which in turn can be used to protect the network from future attacks. In the cyber security world, it is difficult to predict a potential attack without understanding the vulnerability of the network. So, it is important to analyse the network to identify top possible vulnerability list, which will give an intuitive idea to protect the network. Also, handling an ongoing attack poses significant risk on the network and valuable data, where prompt action is necessary. Proper utilisation of attack modelling techniques provide advance planning, which can be implemented rapidly during an ongoing attack event. This paper aims to analyse various types of existing attack modelling techniques to understand the vulnerability of the network, and the behaviour and goals of the adversary. The ultimate goal is to handle cyber attack in efficient manner using attack modelling techniques.
{"title":"Cyber-Attack Modeling Analysis Techniques: An Overview","authors":"Hamad Al-Mohannadi, Q. A. K. Mirza, A. P. Namanya, I. Awan, A. Cullen, Jules Pagna Disso","doi":"10.1109/W-FiCloud.2016.29","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.29","url":null,"abstract":"Cyber attack is a sensitive issue in the world of Internet security. Governments and business organisations around the world are providing enormous effort to secure their data. They are using various types of tools and techniques to keep the business running, while adversaries are trying to breach security and send malicious software such as botnets, viruses, trojans etc., to access valuable data. Everyday the situation is getting worse because of new types of malware emerging to attack networks. It is important to understand those attacks both before and after they happen in order to provide better security to our systems. Understanding attack models provide more insight into network vulnerability, which in turn can be used to protect the network from future attacks. In the cyber security world, it is difficult to predict a potential attack without understanding the vulnerability of the network. So, it is important to analyse the network to identify top possible vulnerability list, which will give an intuitive idea to protect the network. Also, handling an ongoing attack poses significant risk on the network and valuable data, where prompt action is necessary. Proper utilisation of attack modelling techniques provide advance planning, which can be implemented rapidly during an ongoing attack event. This paper aims to analyse various types of existing attack modelling techniques to understand the vulnerability of the network, and the behaviour and goals of the adversary. The ultimate goal is to handle cyber attack in efficient manner using attack modelling techniques.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130392465","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 : 2016-08-01DOI: 10.1109/W-FiCloud.2016.55
Alisa Sotsenko, M. Jansen, M. Milrad, Juwel Rana
In this paper we present an approach for contextual big data analytics in social networks, particularly in Twitter. The combination of a Rich Context Model (RCM) with machine learning is used in order to improve the quality of the data mining techniques. We propose the algorithm and architecture of our approach for real-time contextual analysis of tweets. The proposed approach can be used to enrich and empower the predictive analytics or to provide relevant context-aware recommendations.
{"title":"Using a Rich Context Model for Real-Time Big Data Analytics in Twitter","authors":"Alisa Sotsenko, M. Jansen, M. Milrad, Juwel Rana","doi":"10.1109/W-FiCloud.2016.55","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.55","url":null,"abstract":"In this paper we present an approach for contextual big data analytics in social networks, particularly in Twitter. The combination of a Rich Context Model (RCM) with machine learning is used in order to improve the quality of the data mining techniques. We propose the algorithm and architecture of our approach for real-time contextual analysis of tweets. The proposed approach can be used to enrich and empower the predictive analytics or to provide relevant context-aware recommendations.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125433455","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 : 2016-08-01DOI: 10.1109/W-FiCloud.2016.22
Rana Adnan Rihan, K. Khan
This paper deals with outsourcing of computing to cloud servers where clients' images are computed and stored. It proposes a technique that obfuscates images before sending them to servers. Cloud servers can perform computation such as comparison on images without knowing the actual images. The proposed technique is expected to ensure confidentiality of images. In order to achieve this, we propose a block cipher-based approach that requires less overhead from servers but images are not disclosed to servers during processing. In this work, we are experimenting how to obfuscate images, and send them to cloud servers for processing such as comparing two images in terms of their similarity. Cloud servers can process images without 'seeing and knowing' the actual images. The approach reveals no meaningful information about images to servers.
{"title":"Using Block Cipher for Confidentiality of Images in Cloud-Based Systems","authors":"Rana Adnan Rihan, K. Khan","doi":"10.1109/W-FiCloud.2016.22","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.22","url":null,"abstract":"This paper deals with outsourcing of computing to cloud servers where clients' images are computed and stored. It proposes a technique that obfuscates images before sending them to servers. Cloud servers can perform computation such as comparison on images without knowing the actual images. The proposed technique is expected to ensure confidentiality of images. In order to achieve this, we propose a block cipher-based approach that requires less overhead from servers but images are not disclosed to servers during processing. In this work, we are experimenting how to obfuscate images, and send them to cloud servers for processing such as comparing two images in terms of their similarity. Cloud servers can process images without 'seeing and knowing' the actual images. The approach reveals no meaningful information about images to servers.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121676452","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 : 2016-08-01DOI: 10.1109/W-FiCloud.2016.80
Darijo Raca, A. Zahran, C. Sreenan
HTTP Adaptive video Streaming (HAS) is the dominant traffic type on the Internet. When multiple video clients share a bottleneck link many problems arise, notably bandwidth underutilisation, unfairness and instability. Key findings from previous papers show that the "ON-OFF" behaviour of adaptive video clients is the main culprit. In this paper we focus on the network, and specifically the effects of network queue size when multiple video clients share network resources. We conducted experiments using the Mininet virtual network environment streaming real video content to open-source GPAC video clients. We explored how different network buffer sizes, ranging from 1xBDP to 30xBDP (bandwidth-delay-product), affect clients sharing a bottleneck link. Within GPAC, we implemented the published state-of-the-art adaptive video algorithms FESTIVE and BBA-2. We also evaluated impact of web cross-traffic. Our main findings indicate that the "rule-of-thumb" 1xBDP for network buffer sizing causes bandwidth underutilisation, limiting available bandwidth to 70% for all video clients across different round-trip-times (RTT). Interaction between web and HAS clients depends on multiple factors, including adaptation algorithm, bitrate distribution and offered web traffic load. Additionally, operating in an environment with heterogeneous RTTs causes unfairness among ompeting HAS clients. Based on our experimental results, we propose 2xBDP as a default network queue size in environments when multiple users share network resources with homogeneous RTTs. With heterogeneous RTTs, a BDP value based on the average RTTs for all clients improves fairness among competing clients by 60%.
HTTP自适应视频流(HAS, Adaptive video Streaming)是目前Internet上占主导地位的流量类型。当多个视频客户端共享一个瓶颈链路时，会出现许多问题，特别是带宽利用率不足、不公平和不稳定。先前论文的主要发现表明，自适应视频客户端的“开-关”行为是罪魁祸首。在本文中，我们关注的是网络，特别是当多个视频客户端共享网络资源时，网络队列大小的影响。我们使用Mininet虚拟网络环境进行实验，将真实视频内容流式传输到开源GPAC视频客户端。我们探讨了不同的网络缓冲区大小(从1xBDP到30xBDP(带宽延迟产品))如何影响共享瓶颈链路的客户机。在GPAC中，我们实现了已发布的最先进的自适应视频算法节日和BBA-2。我们还评估了网络交叉流量的影响。我们的主要研究结果表明，网络缓冲区大小的“经验法则”1xBDP导致带宽利用率不足，将不同往返时间(RTT)的所有视频客户端的可用带宽限制为70%。web和HAS客户端之间的交互取决于多种因素，包括自适应算法、比特率分布和提供的web流量负载。此外，在具有异构rtt的环境中操作会导致竞争的HAS客户机之间的不公平。基于我们的实验结果，我们建议将2xBDP作为多用户与同质rtt共享网络资源的环境中的默认网络队列大小。对于异构rtt，基于所有客户机的平均rtt的BDP值可以将竞争客户机之间的公平性提高60%。
{"title":"Sizing Network Buffers: An HTTP Adaptive Streaming Perspective","authors":"Darijo Raca, A. Zahran, C. Sreenan","doi":"10.1109/W-FiCloud.2016.80","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.80","url":null,"abstract":"HTTP Adaptive video Streaming (HAS) is the dominant traffic type on the Internet. When multiple video clients share a bottleneck link many problems arise, notably bandwidth underutilisation, unfairness and instability. Key findings from previous papers show that the \"ON-OFF\" behaviour of adaptive video clients is the main culprit. In this paper we focus on the network, and specifically the effects of network queue size when multiple video clients share network resources. We conducted experiments using the Mininet virtual network environment streaming real video content to open-source GPAC video clients. We explored how different network buffer sizes, ranging from 1xBDP to 30xBDP (bandwidth-delay-product), affect clients sharing a bottleneck link. Within GPAC, we implemented the published state-of-the-art adaptive video algorithms FESTIVE and BBA-2. We also evaluated impact of web cross-traffic. Our main findings indicate that the \"rule-of-thumb\" 1xBDP for network buffer sizing causes bandwidth underutilisation, limiting available bandwidth to 70% for all video clients across different round-trip-times (RTT). Interaction between web and HAS clients depends on multiple factors, including adaptation algorithm, bitrate distribution and offered web traffic load. Additionally, operating in an environment with heterogeneous RTTs causes unfairness among ompeting HAS clients. Based on our experimental results, we propose 2xBDP as a default network queue size in environments when multiple users share network resources with homogeneous RTTs. With heterogeneous RTTs, a BDP value based on the average RTTs for all clients improves fairness among competing clients by 60%.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123209576","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 : 2016-08-01DOI: 10.1109/W-FICLOUD.2016.21
T. Pflanzner, A. Kertész, Bart Spinnewyn, Steven Latré
Currently a growing number of powerful devices join the Internet composing a world of smart devices, or things in the Internet of Things (IoT) perspective, significantly impacting the global traffic. There are also more and more cloud providers offering IoT-specific services, since cloud computing has the potential to satisfy IoT needs such as hiding data generation, processing and visualization tasks. Using the capabilities of smartphones, many things can be simulated simultaneously supporting most types of IoT devices. In this paper, we discuss the design and development of a mobile IoT simulator called MobIoTSim that helps researchers to learn IoT device handling without buying real sensors, and to test and demonstrate IoT applications utilizing multiple devices. We also show how to develop a gateway service in a cloud that can be connected to MobIoTSim to manage the simulated devices and to send back notifications by responding to critical sensor values. By using this tool, developers can examine the behaviour of IoT systems, and develop and evaluate IoT cloud applications more efficiently.
{"title":"MobIoTSim: Towards a Mobile IoT Device Simulator","authors":"T. Pflanzner, A. Kertész, Bart Spinnewyn, Steven Latré","doi":"10.1109/W-FICLOUD.2016.21","DOIUrl":"https://doi.org/10.1109/W-FICLOUD.2016.21","url":null,"abstract":"Currently a growing number of powerful devices join the Internet composing a world of smart devices, or things in the Internet of Things (IoT) perspective, significantly impacting the global traffic. There are also more and more cloud providers offering IoT-specific services, since cloud computing has the potential to satisfy IoT needs such as hiding data generation, processing and visualization tasks. Using the capabilities of smartphones, many things can be simulated simultaneously supporting most types of IoT devices. In this paper, we discuss the design and development of a mobile IoT simulator called MobIoTSim that helps researchers to learn IoT device handling without buying real sensors, and to test and demonstrate IoT applications utilizing multiple devices. We also show how to develop a gateway service in a cloud that can be connected to MobIoTSim to manage the simulated devices and to send back notifications by responding to critical sensor values. By using this tool, developers can examine the behaviour of IoT systems, and develop and evaluate IoT cloud applications more efficiently.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126003978","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 : 2016-08-01DOI: 10.1109/W-FiCloud.2016.51
Jisun An, Hoyoun Cho, Haewoon Kwak, M. Hassen, B. Jansen
The use of personas is an interactive design technique with considerable potential for product and content development. However, personas have typically been viewed as fairly static. In this research, we implement an approach for creating personas in real time, based on automated analysis of actual social media data, integrating data from Facebook, Twitter, and YouTube channels for a large commercial organization. From Twitter, we gather user insights representing interests and viewpoints, leveraging approximately 195,000 follower profiles. From YouTube, we gather demographic data and topical interests, leveraging more than 188,000 subscriber profiles and millions of user interactions. From Facebook, we collect instances of hundreds of thousands of link sharing by more than 54,000 social media followers, specifically examining the domains these users share. We integrate the social media data from all three platforms in order to demonstrating that this data can be used to develop personas in real-time. The research results provide insights into competitive marketing, topical interests, and preferred system features for the users of the online news medium. Research implications are that personas can be generated in real-time, instead of being the result of a laborious, time-consuming development process.
{"title":"Towards Automatic Persona Generation Using Social Media","authors":"Jisun An, Hoyoun Cho, Haewoon Kwak, M. Hassen, B. Jansen","doi":"10.1109/W-FiCloud.2016.51","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.51","url":null,"abstract":"The use of personas is an interactive design technique with considerable potential for product and content development. However, personas have typically been viewed as fairly static. In this research, we implement an approach for creating personas in real time, based on automated analysis of actual social media data, integrating data from Facebook, Twitter, and YouTube channels for a large commercial organization. From Twitter, we gather user insights representing interests and viewpoints, leveraging approximately 195,000 follower profiles. From YouTube, we gather demographic data and topical interests, leveraging more than 188,000 subscriber profiles and millions of user interactions. From Facebook, we collect instances of hundreds of thousands of link sharing by more than 54,000 social media followers, specifically examining the domains these users share. We integrate the social media data from all three platforms in order to demonstrating that this data can be used to develop personas in real-time. The research results provide insights into competitive marketing, topical interests, and preferred system features for the users of the online news medium. Research implications are that personas can be generated in real-time, instead of being the result of a laborious, time-consuming development process.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130222133","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 : 2016-08-01DOI: 10.1109/W-FiCloud.2016.40
A. Gradvohl
Despite companies' demand for data streams processing systems to handle large volumes of flowing data, we did not find many software to assess these sort of systems. In fact, up to date, there are few papers proposing metrics to evaluate these systems or describing software for benchmarks. Most of the papers focus on metrics such as throughput, latency and memory consumption. However, there are other metrics, which system administrators and users should consider, such as information latency, the correctness of results, adaptability on different workloads and others. Therefore, in this paper, we summarized some key metrics used to assess systems for processing online data streams. In addition, we discuss three benchmark tools found in the literature to assess this type of system. At the end of this paper, we propose a new benchmark tool for complex event processing distributed systems called B2-4CEP, which incorporate the metrics described in this paper.
{"title":"Investigating Metrics to Build a Benchmark Tool for Complex Event Processing Systems","authors":"A. Gradvohl","doi":"10.1109/W-FiCloud.2016.40","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.40","url":null,"abstract":"Despite companies' demand for data streams processing systems to handle large volumes of flowing data, we did not find many software to assess these sort of systems. In fact, up to date, there are few papers proposing metrics to evaluate these systems or describing software for benchmarks. Most of the papers focus on metrics such as throughput, latency and memory consumption. However, there are other metrics, which system administrators and users should consider, such as information latency, the correctness of results, adaptability on different workloads and others. Therefore, in this paper, we summarized some key metrics used to assess systems for processing online data streams. In addition, we discuss three benchmark tools found in the literature to assess this type of system. At the end of this paper, we propose a new benchmark tool for complex event processing distributed systems called B2-4CEP, which incorporate the metrics described in this paper.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114344218","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 : 2016-08-01DOI: 10.1109/W-FiCloud.2016.19
S. Aldawood, Frank Fowley, C. Pahl, D. Taibi, Xiaodong Liu
With an increasing number of service providers in the cloud market, the competition between these is also increasing. Each provider attempts to attract customers by providing a high quality service with lowest possible cost and at the same time trying to make profit. Often, cloud resources are advertised and brokered in a spot market style, i.e., traded for immediate delivery. This paper proposes an architecture for a brokerage model specifically for multi-cloud resource spot markets that integrates the resource brokerage function across several cloud providers. We use a tuple space architecture to facilitate coordination. This architecture supports specifically multiple cloud providers selling unused resources in the spot market. To support the matching process by finding the best match between customer requirements and providers, offers are matched with regard the lowest possible cost available for the customer in the market at the time of the request. The key role of this architecture is to provide the coordination techniques built on a tuple space, adapted to the cloud spot market.
{"title":"A Coordination-Based Brokerage Architecture for Multi-cloud Resource Markets","authors":"S. Aldawood, Frank Fowley, C. Pahl, D. Taibi, Xiaodong Liu","doi":"10.1109/W-FiCloud.2016.19","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.19","url":null,"abstract":"With an increasing number of service providers in the cloud market, the competition between these is also increasing. Each provider attempts to attract customers by providing a high quality service with lowest possible cost and at the same time trying to make profit. Often, cloud resources are advertised and brokered in a spot market style, i.e., traded for immediate delivery. This paper proposes an architecture for a brokerage model specifically for multi-cloud resource spot markets that integrates the resource brokerage function across several cloud providers. We use a tuple space architecture to facilitate coordination. This architecture supports specifically multiple cloud providers selling unused resources in the spot market. To support the matching process by finding the best match between customer requirements and providers, offers are matched with regard the lowest possible cost available for the customer in the market at the time of the request. The key role of this architecture is to provide the coordination techniques built on a tuple space, adapted to the cloud spot market.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121111814","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 : 2016-08-01DOI: 10.1109/W-FiCloud.2016.67
Tasneem M. Yousif, Aysha K. Alharam, W. El-Medany, Abeer A. AlKhalaf, Zainab Fardan
This paper presents a remote monitoring system using web-based/mobile application for detecting explosive gases. ROBODEM (Robot-Detection-Explosive-Materials) system aims to develop a remotely controlled explosive gas detection system handled by a LEGO-Mindstrom-NXT robot. The main controller has been designed using Ardunio-Uno microcontroller with IP camera for live video streaming, GPS for live tracking and gas detection system using MQ6 and MQ5 sensors, and. This robot can be controlled either indoor using Bluetooth or outdoor using the Internet. ROBODEM provides sensors results, daily reports, an alarm and notification emails/SMS. The prototype has been tested experimentally and the results are analyzed and discussed.
{"title":"GPRS-Based Robotic Tracking System with Real Time Video Streaming","authors":"Tasneem M. Yousif, Aysha K. Alharam, W. El-Medany, Abeer A. AlKhalaf, Zainab Fardan","doi":"10.1109/W-FiCloud.2016.67","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.67","url":null,"abstract":"This paper presents a remote monitoring system using web-based/mobile application for detecting explosive gases. ROBODEM (Robot-Detection-Explosive-Materials) system aims to develop a remotely controlled explosive gas detection system handled by a LEGO-Mindstrom-NXT robot. The main controller has been designed using Ardunio-Uno microcontroller with IP camera for live video streaming, GPS for live tracking and gas detection system using MQ6 and MQ5 sensors, and. This robot can be controlled either indoor using Bluetooth or outdoor using the Internet. ROBODEM provides sensors results, daily reports, an alarm and notification emails/SMS. The prototype has been tested experimentally and the results are analyzed and discussed.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123942732","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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