Pub Date : 2014-12-15DOI: 10.1109/CloudCom.2014.37
Yu-Jia Chen, Yi-Hsin Shen, Li-Chun Wang
To relieve the heavy loading caused by burst machine-to-machine (M2M) traffic and also satisfy various quality of service (QoS) requirements, load balancing techniques are often introduced in M2M networks. In recent years, software-defined networking (SDN) has shown the possibility of improving load balancing technique. In this paper, we propose traffic-aware load balancing mechanism for M2M networks using SDN. The proposed mechanism can satisfy different QoS requirements of M2M traffic by instant traffic identification and dynamic traffic rerouting, which leverage the capability of SDN to dynamically monitor and control the entire network.
{"title":"Traffic-Aware Load Balancing for M2M Networks Using SDN","authors":"Yu-Jia Chen, Yi-Hsin Shen, Li-Chun Wang","doi":"10.1109/CloudCom.2014.37","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.37","url":null,"abstract":"To relieve the heavy loading caused by burst machine-to-machine (M2M) traffic and also satisfy various quality of service (QoS) requirements, load balancing techniques are often introduced in M2M networks. In recent years, software-defined networking (SDN) has shown the possibility of improving load balancing technique. In this paper, we propose traffic-aware load balancing mechanism for M2M networks using SDN. The proposed mechanism can satisfy different QoS requirements of M2M traffic by instant traffic identification and dynamic traffic rerouting, which leverage the capability of SDN to dynamically monitor and control the entire network.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"45 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":"131696514","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.2014.135
Ting Yang, Young Choon Lee, Albert Y. Zomaya
Data Center (DC), the underlying infrastructure of cloud computing, becomes startling large with more powerful computing and communication capability to satisfy the wide spectrum of composite applications. In a large scale DC, a great number of switches connect servers into one complex network. The energy consumption of this communication network has skyrocketed and become the same league as the computing servers' costs. More than one-third of the total energy in DCs is consumed by communication links, switching and aggregation elements. Saving Data Center Network (DCN) energy to improve data center efficiency (power usage effectiveness or PUE) become the key technique in green computing. In this paper, we present VPTCA as an energy-efficient data center network planning solution that collectively deals with virtual machine placement and communication traffic configuration. VPTCA aims to reduce the DCN's energy consumption. In particular, interrelated VMs are assigned into the same server or pod, which effectively helps to reduce the amount of transmission load. In the layer of traffic message, VPTCA optimally uses switch ports and link bandwidth to balance the load and avoid congestions, enabling DCN to increase its transmission capacity, and saving a significant amount of network energy. In our evaluation via NS-2 simulations, the performance of VPTCA is measured and compared with two well-known DCN management algorithms, Global First Fit and Elastic Tree. Based on our experimental results, VPTCA outperforms existing algorithms in providing DCN more transmission capacity with less energy consumption.
数据中心(DC)是云计算的底层基础设施，随着更强大的计算和通信能力，它的规模变得惊人地大，以满足广泛的组合应用程序。在大型数据中心中，大量的交换机将服务器连接成一个复杂的网络。这种通信网络的能源消耗急剧上升，与计算服务器的成本相当。数据中心总能量的三分之一以上被通信链路、交换和聚合元件消耗。节能数据中心网络(DCN)以提高数据中心效率(power usage effectiveness, PUE)成为绿色计算的关键技术。在本文中，我们提出VPTCA作为一种节能的数据中心网络规划解决方案，它共同处理虚拟机放置和通信流量配置。VPTCA旨在减少DCN的能源消耗。特别是，将相互关联的vm分配到相同的服务器或pod中，这有助于有效地减少传输负载。在流量消息层，VPTCA优化利用交换机端口和链路带宽，均衡负载，避免拥塞，使DCN能够提高传输容量，节省大量网络能源。在我们通过NS-2模拟进行的评估中，测量了VPTCA的性能，并将其与两种知名的DCN管理算法Global First Fit和Elastic Tree进行了比较。实验结果表明，VPTCA算法在为DCN提供更大的传输容量和更低的能耗方面优于现有算法。
{"title":"Energy-Efficient Data Center Networks Planning with Virtual Machine Placement and Traffic Configuration","authors":"Ting Yang, Young Choon Lee, Albert Y. Zomaya","doi":"10.1109/CloudCom.2014.135","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.135","url":null,"abstract":"Data Center (DC), the underlying infrastructure of cloud computing, becomes startling large with more powerful computing and communication capability to satisfy the wide spectrum of composite applications. In a large scale DC, a great number of switches connect servers into one complex network. The energy consumption of this communication network has skyrocketed and become the same league as the computing servers' costs. More than one-third of the total energy in DCs is consumed by communication links, switching and aggregation elements. Saving Data Center Network (DCN) energy to improve data center efficiency (power usage effectiveness or PUE) become the key technique in green computing. In this paper, we present VPTCA as an energy-efficient data center network planning solution that collectively deals with virtual machine placement and communication traffic configuration. VPTCA aims to reduce the DCN's energy consumption. In particular, interrelated VMs are assigned into the same server or pod, which effectively helps to reduce the amount of transmission load. In the layer of traffic message, VPTCA optimally uses switch ports and link bandwidth to balance the load and avoid congestions, enabling DCN to increase its transmission capacity, and saving a significant amount of network energy. In our evaluation via NS-2 simulations, the performance of VPTCA is measured and compared with two well-known DCN management algorithms, Global First Fit and Elastic Tree. Based on our experimental results, VPTCA outperforms existing algorithms in providing DCN more transmission capacity with less energy consumption.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"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":"115699689","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.2014.60
Maciej Zbierski, Przemyslaw Makosiej
Computation offloading is one of the approaches used for increasing application efficiency and decreasing energy consumption on consumer devices, an issue especially important for mobile appliances. While some such systems have been previously designed, very little research has been directed towards offloading code from web applications, an alternative to native solutions recently gaining in popularity. In this paper we attempt to narrow down this gap by presenting the first practical system for offloading HTML5 web workers from mobile web applications. The system is transparent to the programmer, i.e. Does not require any additional modifications to the original application to indicate which code parts should be offloaded. The results of the experiments with various sample applications have shown that for sufficiently complicated computations the offloading system can decrease both the processing time and energy consumption by even several hundred percent.
{"title":"Bring the Cloud to Your Mobile: Transparent Offloading of HTML5 Web Workers","authors":"Maciej Zbierski, Przemyslaw Makosiej","doi":"10.1109/CloudCom.2014.60","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.60","url":null,"abstract":"Computation offloading is one of the approaches used for increasing application efficiency and decreasing energy consumption on consumer devices, an issue especially important for mobile appliances. While some such systems have been previously designed, very little research has been directed towards offloading code from web applications, an alternative to native solutions recently gaining in popularity. In this paper we attempt to narrow down this gap by presenting the first practical system for offloading HTML5 web workers from mobile web applications. The system is transparent to the programmer, i.e. Does not require any additional modifications to the original application to indicate which code parts should be offloaded. The results of the experiments with various sample applications have shown that for sufficiently complicated computations the offloading system can decrease both the processing time and energy consumption by even several hundred percent.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"7 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":"115915964","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.2014.93
D. Moldovan, G. Copil, Hong Linh Truong, S. Dustdar
With the increasing cloud popularity, substantial effort has been paid for the development of emerging elastic cloud services, consisting of different units distributed among virtual machines/containers in different clouds. Due to the software stack and deployment complexity in single and multi-cloud scenarios, developing and managing such services is impeded by a lack of tools and techniques for understanding the elasticity relationships among individual service units, which influence the service's overall elasticity. In this paper we characterize the elasticity relationships, and develop mechanisms for analyzing them, based on service monitoring information and elasticity requirements. From collected monitoring information we abstract the elasticity behavior of the whole cloud service and individual units, over which we design a customizable algorithm for relationships analysis. We illustrate our approach via several experiments with an elastic data service for M2M platforms, highlighting the importance of determining elasticity relationships for the development and operation of elastic services.
{"title":"On Analyzing Elasticity Relationships of Cloud Services","authors":"D. Moldovan, G. Copil, Hong Linh Truong, S. Dustdar","doi":"10.1109/CLOUDCOM.2014.93","DOIUrl":"https://doi.org/10.1109/CLOUDCOM.2014.93","url":null,"abstract":"With the increasing cloud popularity, substantial effort has been paid for the development of emerging elastic cloud services, consisting of different units distributed among virtual machines/containers in different clouds. Due to the software stack and deployment complexity in single and multi-cloud scenarios, developing and managing such services is impeded by a lack of tools and techniques for understanding the elasticity relationships among individual service units, which influence the service's overall elasticity. In this paper we characterize the elasticity relationships, and develop mechanisms for analyzing them, based on service monitoring information and elasticity requirements. From collected monitoring information we abstract the elasticity behavior of the whole cloud service and individual units, over which we design a customizable algorithm for relationships analysis. We illustrate our approach via several experiments with an elastic data service for M2M platforms, highlighting the importance of determining elasticity relationships for the development and operation of elastic services.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"12 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":"117040747","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.2014.118
Jiaqi Tan, Utsav Drolia, Rolando Martins, R. Gandhi, P. Narasimhan
The rapid growth in mobile devices will give rise to the trend of the leasing out of compute and data resources on mobile devices to third-parties for applications to be run on multiple mobile devices. However, these third-party applications running on leased mobile devices are typically written by unknown entities, and cannot be trusted by mobile device owners. Current mobile device platforms (e.g. Android) have permissions and access control systems designed for mobile apps that are written by reputable developers and vetted by authoritative app stores, and they are not suitable for untrusted apps. We propose STOVEPipe, an observable access control system for user data on mobile devices for untrusted third-party applications. STOVEPipe ensures that untrusted code is isolated and cannot directly access system data, and performs all data accesses on behalf of untrusted apps. This enables STOVEPipe to observe all data accessed by untrusted apps, implement content-based access control, perform accounting and auditing on accessed data easily, and perform privacy-preserving data transformations.
{"title":"STOVEPipe: Observable Access Control of User Data for Untrusted Applications on Mobile Devices","authors":"Jiaqi Tan, Utsav Drolia, Rolando Martins, R. Gandhi, P. Narasimhan","doi":"10.1109/CloudCom.2014.118","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.118","url":null,"abstract":"The rapid growth in mobile devices will give rise to the trend of the leasing out of compute and data resources on mobile devices to third-parties for applications to be run on multiple mobile devices. However, these third-party applications running on leased mobile devices are typically written by unknown entities, and cannot be trusted by mobile device owners. Current mobile device platforms (e.g. Android) have permissions and access control systems designed for mobile apps that are written by reputable developers and vetted by authoritative app stores, and they are not suitable for untrusted apps. We propose STOVEPipe, an observable access control system for user data on mobile devices for untrusted third-party applications. STOVEPipe ensures that untrusted code is isolated and cannot directly access system data, and performs all data accesses on behalf of untrusted apps. This enables STOVEPipe to observe all data accessed by untrusted apps, implement content-based access control, perform accounting and auditing on accessed data easily, and perform privacy-preserving data transformations.","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":"124823251","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.2014.12
Shinya Kitajima, S. Kikuchi, Y. Matsumoto
Generally, the automation operations for cloud management achieved by replacing manual operations with operations using automation tools. The developers of automation scripts often refer to the existing automation scripts so that they can develop new automation scripts by just modifying smaller parts in the existing automation scripts. In order to facilitate the development of automation scripts, we propose a method of appropriately identifying the existing automation scripts to refer to in developing automation scripts.
{"title":"Identification of Related Management Scripts for Efficient Automation of Cloud Management Tasks","authors":"Shinya Kitajima, S. Kikuchi, Y. Matsumoto","doi":"10.1109/CloudCom.2014.12","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.12","url":null,"abstract":"Generally, the automation operations for cloud management achieved by replacing manual operations with operations using automation tools. The developers of automation scripts often refer to the existing automation scripts so that they can develop new automation scripts by just modifying smaller parts in the existing automation scripts. In order to facilitate the development of automation scripts, we propose a method of appropriately identifying the existing automation scripts to refer to in developing automation scripts.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"36 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":"128193890","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.2014.138
Rawand Guerfel, Zohra Sbaï, R. Ayed
Cloud computing has become a widely used concept. It is characterized by its elasticity, its on demand services and the unlimited provided resources. However, because of the complexity of customers service requests, their provision became an increasingly difficult task. In fact, in order to meet these requirements, services should be combined to implement a composite one performing the requested task. It is in this sense that the use of SOA architecture, which provides service composition, seems a useful solution. This paper investigates existing works on services discovery and composition in SOA as well as Cloud architectures. We study and compare these works and present an architecture of services composition based on SOA architecture and Cloud computing.
{"title":"On Service Composition in Cloud Computing: A Survey and an Ongoing Architecture","authors":"Rawand Guerfel, Zohra Sbaï, R. Ayed","doi":"10.1109/CloudCom.2014.138","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.138","url":null,"abstract":"Cloud computing has become a widely used concept. It is characterized by its elasticity, its on demand services and the unlimited provided resources. However, because of the complexity of customers service requests, their provision became an increasingly difficult task. In fact, in order to meet these requirements, services should be combined to implement a composite one performing the requested task. It is in this sense that the use of SOA architecture, which provides service composition, seems a useful solution. This paper investigates existing works on services discovery and composition in SOA as well as Cloud architectures. We study and compare these works and present an architecture of services composition based on SOA architecture and Cloud computing.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"125 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":"127430688","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.2014.56
Shu Qin Ren, Shibin Cheng, Yu Zhang, E. S. Lim, K. L. Yong, Zengxiang Li
With more applications moving to cloud, scalable storage systems, composed of a cluster of storage servers and gateways, are deployed as the back-end infrastructure to accommodate high-volume data. In such an environment, it is a challenge to provide predictable and controllable storage performance for multitenanted users with multiple applications, due to performance violation from misbehaving applications. In this paper, we propose a two-level QoS controller over scalable storage system. On the higher level, I/O throughput rented by each tenant is guaranteed and strictly limited by a CAP value. On the lower level, this rented service can be on-demand served among multiple applications under the same tenant. Thus our distributed controller not only shields performance violation from "noisy" tenants but also allows tenants to fully utilizing the rented I/O throughput. Furthermore, the QoS controller is implemented in an efficient manner, by reusing the communication channels among gateways and storage servers and piggybacking control signals on data communications. The experimental results have shown that the two-level QoS controller can guarantee I/O throughput at tenant level by controlling the CAP value while accelerating applications by on-demand serving at a very little computation cost.
{"title":"Two-Level Storage QoS to Manage Performance for Multiple Tenants with Multiple Workloads","authors":"Shu Qin Ren, Shibin Cheng, Yu Zhang, E. S. Lim, K. L. Yong, Zengxiang Li","doi":"10.1109/CloudCom.2014.56","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.56","url":null,"abstract":"With more applications moving to cloud, scalable storage systems, composed of a cluster of storage servers and gateways, are deployed as the back-end infrastructure to accommodate high-volume data. In such an environment, it is a challenge to provide predictable and controllable storage performance for multitenanted users with multiple applications, due to performance violation from misbehaving applications. In this paper, we propose a two-level QoS controller over scalable storage system. On the higher level, I/O throughput rented by each tenant is guaranteed and strictly limited by a CAP value. On the lower level, this rented service can be on-demand served among multiple applications under the same tenant. Thus our distributed controller not only shields performance violation from \"noisy\" tenants but also allows tenants to fully utilizing the rented I/O throughput. Furthermore, the QoS controller is implemented in an efficient manner, by reusing the communication channels among gateways and storage servers and piggybacking control signals on data communications. The experimental results have shown that the two-level QoS controller can guarantee I/O throughput at tenant level by controlling the CAP value while accelerating applications by on-demand serving at a very little computation cost.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"2013 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":"132158171","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.2014.173
Mon-Yen Luo, Jun-Yi Chen
Network virtualization is crucial in data centers environments for interconnecting all physical and virtualized resources to create a complete semblance of an integrated computing infrastructure. Much of the existing research on data center networking has focused on network mechanisms inside the datacenter. Little attention has been paid to networking mechanisms for integrating multiple data centers. In this paper we introduce Virtual Transits, a flexible platform providing a novel solution to dynamically build and manage virtual networks across multiple data centers. Virtual Transits can also incorporate several important datacenter networking schemes into a coherent platform that enables seamless integration of intracloud and intercloud traffic. Through our implementation and performance evaluation on a real deployment, we show that our system provides a promising and efficient solution for inter-cloud networking, test beds federation, and software-defined networking test beds.
{"title":"Virtual Transits: A Flexible Platform for Network Virtualization across Data Centers","authors":"Mon-Yen Luo, Jun-Yi Chen","doi":"10.1109/CloudCom.2014.173","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.173","url":null,"abstract":"Network virtualization is crucial in data centers environments for interconnecting all physical and virtualized resources to create a complete semblance of an integrated computing infrastructure. Much of the existing research on data center networking has focused on network mechanisms inside the datacenter. Little attention has been paid to networking mechanisms for integrating multiple data centers. In this paper we introduce Virtual Transits, a flexible platform providing a novel solution to dynamically build and manage virtual networks across multiple data centers. Virtual Transits can also incorporate several important datacenter networking schemes into a coherent platform that enables seamless integration of intracloud and intercloud traffic. Through our implementation and performance evaluation on a real deployment, we show that our system provides a promising and efficient solution for inter-cloud networking, test beds federation, and software-defined networking test beds.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"12 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":"130836243","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.2014.97
Moisés Rodrigues, P. Endo, Jonatas Vitalino, G. Gonçalves, D. Sadok, F. Wuhib
Resource management in distributed environments, such as Cloud virtualized networks, is one of the main concerns of infrastructure providers. Despite the many advantages of centralized solutions, their unique point of failure and the lack of scalability make us consider the use of distributed and autonomic solutions. Beyond this, centralized solutions would be inefficient to deal with dynamic and peak situations. By using simple rules, each autonomic node can independently act and react according to the scenario's changes without the knowledge of the whole system, making autonomic management robust and adaptable. The main goal of this paper is to present the Role-Based Self-Appointment for Live Streaming (RBSA4LS) prototype, developed considering Software Defined Network technologies. The prototyped was developed and used to evaluate RBSA4LS performance. Our results show a significant decrease in network traffic and an increase of client Quality of Experience (QoE).
{"title":"Prototyping an Autonomic Cloud Infrastructure to Manage Live Streaming Applications Using a Software Defined Network: Performance Analysis and Challenges","authors":"Moisés Rodrigues, P. Endo, Jonatas Vitalino, G. Gonçalves, D. Sadok, F. Wuhib","doi":"10.1109/CloudCom.2014.97","DOIUrl":"https://doi.org/10.1109/CloudCom.2014.97","url":null,"abstract":"Resource management in distributed environments, such as Cloud virtualized networks, is one of the main concerns of infrastructure providers. Despite the many advantages of centralized solutions, their unique point of failure and the lack of scalability make us consider the use of distributed and autonomic solutions. Beyond this, centralized solutions would be inefficient to deal with dynamic and peak situations. By using simple rules, each autonomic node can independently act and react according to the scenario's changes without the knowledge of the whole system, making autonomic management robust and adaptable. The main goal of this paper is to present the Role-Based Self-Appointment for Live Streaming (RBSA4LS) prototype, developed considering Software Defined Network technologies. The prototyped was developed and used to evaluate RBSA4LS performance. Our results show a significant decrease in network traffic and an increase of client Quality of Experience (QoE).","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":"131015354","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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