{"title":"Real-Time Target Detection and Recognition with Deep Convolutional Networks for Intelligent Visual Surveillance","authors":"Wen Xu, Jing He, H. Zhang, B. Mao, Jie Cao","doi":"10.1145/2996890.3007881","DOIUrl":"https://doi.org/10.1145/2996890.3007881","url":null,"abstract":"Moving target detection and tracking, recognition, behaviours analysis are the key issues in the intelligent visual surveillance system (IVSS). The challenge is how to process the real-time video stream in an effective way in case that we could find the interested objects for analysis. However, the traditional video surveillance technology often does not meet the needs of real-time key frame recognition for the on-line intelligent video monitoring system. In our paper, we apply the state-of-the-art Faster R-CNN [7] that takes advantages of convolutional neural networks into our real-time target recognition system - Deep Intelligent Visual Surveillance (DIVS). The key aspects of our DIVS are consisted of four parts: (i) Getting the real-time video image from remote cameras, (ii) Processing the data with the deep learning framework caffe [23] built for Faster R-CNN, (iii) Storing the valuable data with MySQL, (iv) Data presentation on the website. Experiments based on our system validated the effectiveness, stability and accuracy of our proposed solutions.","PeriodicalId":350701,"journal":{"name":"2016 IEEE/ACM 9th International Conference on Utility and Cloud Computing (UCC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129725478","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}
{"title":"Security in Container-Based Virtualization through vTPM","authors":"Shohreh Hosseinzadeh, S. Laurén, V. Leppänen","doi":"10.1145/2996890.3009903","DOIUrl":"https://doi.org/10.1145/2996890.3009903","url":null,"abstract":"Cloud computing is a wide-spread technology that enables the enterprises to provide services to their customers with a lower cost, higher performance, better availability and scalability. However, privacy and security in cloud computing has always been a major challenge to service providers and a concern to its users. Trusted computing has led its way in securing the cloud computing and virtualized environment, during the past decades. In this paper, first we study virtualized trusted platform modules and integration of vTPM in hypervisor-based virtualization. Then we propose two architectural solutions for integrating the vTPM in container-based virtualization model.","PeriodicalId":350701,"journal":{"name":"2016 IEEE/ACM 9th International Conference on Utility and Cloud Computing (UCC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124147203","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}
J. M. Cortés-Mendoza, A. Tchernykh, A. Drozdov, Loic Didelot
{"title":"Robust Cloud VoIP Scheduling under VMs Startup Time Delay Uncertainty","authors":"J. M. Cortés-Mendoza, A. Tchernykh, A. Drozdov, Loic Didelot","doi":"10.1145/2996890.3007865","DOIUrl":"https://doi.org/10.1145/2996890.3007865","url":null,"abstract":"In this paper, we address cloud VoIP service orchestration and scheduling to provide appropriate levels of quality of service to users, and performance to VoIP service providers. We consider voice quality affected by call processing, and cost contributed by billing hours for used VMs in a cloud. We believe that this biobjective focus is reasonable and representative for real installations and applications. We conduct comprehensive simulation of our calls load balancing strategies on real data and show that not all approaches provide suitable quality of service. We analyze eight on-line dynamic non-clairvoyant scheduling strategies with variations in VM startup time delays to deal with realistic VoIP cloud environments. We show that the proposed strategies outperform currently in use strategies in terms of quality of service and provider cost. The robustness of these strategies is also discussed.","PeriodicalId":350701,"journal":{"name":"2016 IEEE/ACM 9th International Conference on Utility and Cloud Computing (UCC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133276261","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}
{"title":"A Load Balancing Strategy Based on Data Correlation in Cloud Computing","authors":"Guilin Shao, Jiming Chen","doi":"10.1145/2996890.3007852","DOIUrl":"https://doi.org/10.1145/2996890.3007852","url":null,"abstract":"by virtual machines and the reduce of resource utilization caused by migration of a single virtual machine in cloud computing , this paper proposes a load balancing strategy based on data correlation in cloud computing. This strategy finds out the migration unit based on the correlation between the data and the virtual machines used to deal with the same data, and construct the load-intensive data set to carry on the overall migration. The experimental results show that the load balancing strategy can reduce the communication overhead and improve the utilization of resources in a certain extent.","PeriodicalId":350701,"journal":{"name":"2016 IEEE/ACM 9th International Conference on Utility and Cloud Computing (UCC)","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122386290","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}
{"title":"A Fined-Grained Privacy-Preserving Access Control Protocol in Wireless Sensor Networks","authors":"Jie Cui, Hong Zhong, Xuan Tang, Jing Zhang","doi":"10.1145/2996890.3007850","DOIUrl":"https://doi.org/10.1145/2996890.3007850","url":null,"abstract":"For single-owner multi-user wireless sensor networks, there is the demand to implement the user privacy-preserving access control protocol in WSNs. Firstly, we propose a new access control protocol based on an efficient attribute-based signature. In the protocol, users need to pay for query, and the protocol achieves fine-grained access control and privacy protection. Then, the protocol is analyzed in detail. Finally, the comparison of protocols indicates that our scheme is more efficient. Our scheme not only protects the privacy of users and achieves fine-grained access control, but also provides the query command validation with low overhead. The scheme can better satisfy the access control requirements of wireless sensor networks.","PeriodicalId":350701,"journal":{"name":"2016 IEEE/ACM 9th International Conference on Utility and Cloud Computing (UCC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127526152","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}
{"title":"CL-SLAM: Cross-Layer SLA Monitoring Framework for Cloud Service-Based Applications","authors":"Mohan Baruwal Chhetri, Quoc Bao Vo, R. Kowalczyk","doi":"10.1145/2996890.2996906","DOIUrl":"https://doi.org/10.1145/2996890.2996906","url":null,"abstract":"Modern applications are increasingly being composed from multiple components that require and consume services at dierent layers of the cloud stack. The diverse, dynamic and unpredictable nature of both cloud services and application workloads makes quality-assured provision of such cloud service-based applications (CSBAs) a major challenge. While elasticity and autoscaling gives CSBA providers the ability to scale cloud resources on-demand, they require a comprehensive, system-wide view of the application performance in order to make timely, cost-eective and performanceecient scaling decisions. In this paper, we propose, develop and validate CL-SLAM a Cross-Layer SLA Monitoring Framework for CSBAs. Its main features include (a) realtime, fine-grained visibility into CSBA performance, (b) visual descriptive analytics to identify correlations and interdependencies between cross-layer performance metrics, (c) temporal profiling of CSBA performance, (d) proactive monitoring, detection and root-cause analysis of SLA violation, and (e) support for both reactive and proactive adaptation in support of quality-assured CSBA provision. We validate our approach through a prototype implementation.","PeriodicalId":350701,"journal":{"name":"2016 IEEE/ACM 9th International Conference on Utility and Cloud Computing (UCC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128939378","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}
{"title":"Deadline Distribution Strategies for Scientific Workflow Scheduling in Commercial Clouds","authors":"Vahid Arabnejad, K. Bubendorfer, Bryan K. F. Ng","doi":"10.1145/2996890.2996905","DOIUrl":"https://doi.org/10.1145/2996890.2996905","url":null,"abstract":"Commercial clouds have become a viable platform for performing a significant range of large scale scientific analyses – due to the offerings of elasticity, specialist hardware, software infrastructure and pay-as-you-go cost model. Such clouds represent a low upfront capital cost alternative to the use of dedicated eScience infrastructure. However, there are still significant technical hurdles associated with obtaining the best performance for the cost - it is easy to provision commercial clouds inefficiently resulting in great and potentially unanticipated expense. In this paper we introduce a new heuristic scheduling algorithm Deadline Distribution Ratio (DDR) to address the workflow scheduling problem with the objectives of minimizing the cost of Cloud computing resources while satisfying a given deadline. Within this context, we also investigate a range of different deadline distribution strategies and their effect on the overall scheduling performance. We then compare the DDR algorithm against three other published algorithms, using five different scientific workflows generated using the pegasus workflow generator, on a CloudSim simulation that implements a pricing model based on AWS. In general, the DDR algorithm returns the lowest costs across the majority of deadlines and workflows, while maintaining a high scheduling success rate.","PeriodicalId":350701,"journal":{"name":"2016 IEEE/ACM 9th International Conference on Utility and Cloud Computing (UCC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129023887","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}
{"title":"Towards Provisioning of Real-Time Smart City Services Using Clouds","authors":"K. Soomro, Z. Khan, Khawar Hasham","doi":"10.1145/2996890.3007860","DOIUrl":"https://doi.org/10.1145/2996890.3007860","url":null,"abstract":"ICT is becoming an enabler for smart city applications by making effective use of various data resources generated daily in an urban environment. Mostly this data is utilised by city authorities for city planning purposes and often citizens become indirect beneficiaries of such applications. In this paper we present an algorithm for real-time processing of streaming data from multiple sources. We also present the design and proof of concept of an application that performs mining and analysis of open data available through city portals and social networks and generates an information service in real time for use by city administrations. The prototype utilises streaming data from Twitter and open data from Bristol to demonstrate a hypothetical scenario using Apache Storm. The output is presented in the form of visual maps using OpenStreetMaps as a backend and the prototype highlights various challenges which are discussed in detail.","PeriodicalId":350701,"journal":{"name":"2016 IEEE/ACM 9th International Conference on Utility and Cloud Computing (UCC)","volume":"352 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131722480","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}
{"title":"Exploiting Novel Software Development Paradigms to Increase the Sustainability of Data Centers","authors":"A. Carrega, M. Repetto","doi":"10.1145/2996890.3007878","DOIUrl":"https://doi.org/10.1145/2996890.3007878","url":null,"abstract":"The application of effective energy management strategies in data centers is often hindered by the substantial conflict between the interests of cloud users and infrastructure owners. As a matter of fact, cloud users require that the service level they are paying for is tightly met, whereas data center owners try to cut down their operational expenses. In this paper, we propose a novel consolidation algorithm that exploits emerging software development paradigms. Our approach enables cloud users to indicate their willingness to apply energy saving mechanisms to some of their virtual resources, hence giving infrastructure managers the ability to apply more efficient workload consolidation and to switch their hardware to very low-power states. The result is an optimal trade-off between energy consumption and performance.","PeriodicalId":350701,"journal":{"name":"2016 IEEE/ACM 9th International Conference on Utility and Cloud Computing (UCC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132776937","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}
{"title":"Towards a Smart Learning Environment for Smart City Governance","authors":"R. Hammad, D. Ludlow","doi":"10.1145/2996890.3007859","DOIUrl":"https://doi.org/10.1145/2996890.3007859","url":null,"abstract":"Educational services provided to various stakeholders need to be actively developed to accommodate the diversity of learning models and to get the advantages of available resources (e.g. data) in smart cities governance. Despite the substantial literature on smart cities, for Technology-Enhanced Learning (TEL) and its related domains such as learning analytics and big data, little effort has been given to the creation of connectivity to smart cities governance to meet stakeholders' demands, even though this connection may generate various challenges arising from conflict of interests between stakeholders and organisations. This paper proposes a structural framework for successful application of smart learning environments in the context of smart city governance. It reflects on selected challenges and proposes some future directions.","PeriodicalId":350701,"journal":{"name":"2016 IEEE/ACM 9th International Conference on Utility and Cloud Computing (UCC)","volume":"110 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114000890","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}