Proposal and Design for DTV Broadcasting Service Applying Cloud

Transcription

1 Proposal and Design for DTV Broadcasting Service Applying Cloud Computing Testbed 1 Jong Won Yang, 2 Sung Jun Kim, 3 Mi-Hye Kim 1, First Author KISTI, jwyang@kisti.re.kr 2, Corresponding KISTI, sjkim@kisti.re.kr 3 mhkim@chungbuk.ac.kr Abstract In this study, several servers are virtualized for a single physical equipment using cloud computing in order to build the TestBed. It makes possible to use it without any high cost duplicated infrastructures because it can be shared by several Ss and used as a low cost broadcasting infrastructure. In addition, it is possible to develop various methods for responding recently issued cyber terrors and crimes including other problems in server downs by excessive accesses, hacking, and security of broadcasting contents. 1 Introduction Keywords: Virtualization,Cloud Computing Testbed, Contents, DTV Establishing the Cloud Computing TestBed infrastructure is a basic service infrastructure for providing next-generation DTV broadcasting services. For applying a Cloud Computing environment, a technology for synchronizing/distributing contents and a distributed file system that stores/manages contents efficiently are required [1,5,6]. Also, a monitoring system for ensuring storages and QoS is required in providing contents according to the inquiry of users [3]. Servers required in establishing next-generation digital broadcasting service environments are GLB, caching, DB management, EPG, CMS, and virtualization management servers [2,4]. It is not an effective way for establishing these servers as an independent element in the viewpoint of Green-IT. In this study, several servers are virtualized for a single physical equipment using cloud computing in order to build the Cloud Computing TestBed. It makes possible to use it without any high cost duplicated infrastructures because it can be shared by several Ss and used as a low cost broadcasting infrastructure. 2 Diagram of the proposed Cloud Computing Testbed The Testbed for providing next-generation DTV broadcasting services consists of two major sections, server virtualization and storage virtualization sections. The server virtualization section consists of several servers for providing contents transmission services and contents synchronization. The storage virtualization section is to be designed as a Hadoop file system for storing contents according to the inquiry of users. A large capacity storage system for providing next-generation DTV infrastructures requires the extensibility and stability of the system. For guaranteeing the minimum performance in services while the extensibility is ensured, in the initial design of the system, a large capacity storage system is to be designed using two equipments in which a single equipment has 50 1TB HDDs. As each server has 50 1TB HDDs, it is not possible to integrate these all HDDs as a single storage. Journal of Convergence Information Technology(JCIT) Volume7, Number10, June 2012 doi: /jcit.vol7.issue

2 Fig. 1 Entire configuration of thetestbed Because the boot loader in S cannot recognize more than 2T, it is necessary to divide S and data sections into different sections. Also, the data, DB, and log spaces in S are shared by 1TB and the remained space of 48TB is used to the system in which such remained 48TB cannot be recognized by a file system in the use of a general ext File System. Although it can be recognized using XFS or JFS, in this study, a logical distributed file system is to be configured using the Hadoop, which is a distributed file system. Then, the remained 48TB is divided into 8 different sections, such as 7TB * 8. The storage system with a combination of 1TB + 7TB * 8 is integrated using the Hadoop as a space of 100TB for movies. Virtualization servers were installed based on corresponding S/W using the developed technologies and tested with various variables and cases in order to verify and test the integrated system of Cloud Computing TestBed. Virtualization servers consist of following types according to its application purposes. - DB Server - Active / Passive - Web Server - Active / Passive Virtualization Management Service Monitoring EPG/CMS Web Service - GLB/SCS Server - Active / Passive Load Balancing Service Management - Synchronization Server Root - Active / Passive - Caching Server The storage virtualization in cloud computing is a technology that provides idle system resources distributed in different storage controllers to a logical virtual disk resource by gathering them using a physical way. Most of the contents used in digital cable broadcasting services represent large capacities and the extensibility in configuring a large storage is essentially required. The system proposed in this study sustains the performance minimally required to provide services while it ensures its extensibility. 2.1 System Design Management of service server resources is a very important factor for providing stable and effective services in a digital cable broadcasting environment using cloud infrastructures. In this study, independent resource management of limited resources for each S(System perator) in a MS(Multi-System perator) environment by providing caching clouds to virtualized cloud infrastructures is provided. Also, multi-tenancy * This research is supported by Ministry of Culture, Sports and Tourism(MCST) and Korea Creative Content Agency(KCCA) in the Culture Technology(CT) Research & Developement Program

3 like hierarchical management of contents according to service providers is supported. The core elements for providing such caching clouds are as follows. - Cloud Monitoring System This system performs monitoring for the resources that compose caching clouds. In the characteristic of cloud resources, as the monitoring is performed for virtualized resources, an extra measurement method like an API call for hypervisors is required. - Triggering System for Cloud Measuring Metrics In general, a triggering system is an automatic system that causes a specific situation as the assigned condition is satisfied. The assigned condition is limited as the metrics measured in a cloud monitoring system and various policies are needed to sensitively response services. - Cloud Scaling System This system dynamically controls the scale of caching cloud resources recently provided according to the calls in a triggering system. It is necessary to manage caching resources through a close relationship with a cloud load balancer for ensuring the continuity in services. - Cloud Load Balancer A cloud load balancer provides a load balancing function according to the access condition to multi-caching cloud resources. It is necessary to verify the resources added and deleted in providing services in order to sustain the continuity in services. A contents download server for responding the inquiries in variable contents download services that are required in a device, STB (Set-Top Box), is configured as a caching system and several systems are determined as a single cluster based on such a caching system using a load balancer in order to provide stable services. The multi-tenancy is to be provided for supporting MS in order to maximize the application rate of cloud infrastructure resources. For achieving it, the system design was performed to minimize influencing factors on the services between Ss by providing the caching clouds, which are configured by load balancer and cache system groups, for each S. 2.2 Cloud Computing Testbed Configuration In this study, the same condition as a practical Use Case is determined and its performance and possibility of providing services are tested. Fig. 2 illustrates the physical allocation of a server for practical Use Cases. Fig. 2 Pysical allocation for tests Two 50TBs are used in the Storage node, which is a large capacity storage, and the four Cache Servers distributed in different areas are used. Each cache server applies a virtualization technology in which four individual S and cache servers for each node are installed. STBs used by users request files through access to a cache server determined by a load balancer. A Player module for displaying movies to users and a RTSPClient module that presents EPG information received from a remote cache server to users and receives movies from the server are installed. The RTSPClient communicate to the Cache Server in a cache server node in which movies are already distributed by a synchronization module, SyncAgent. 129

4 Fig. 3 shows the configuration of the Storage node used for synchronizing it with a large capacity storage. Fig. 3 Configuration of the components in the Storage node Fuse-DFS is used to perform a link between the Hadoop, which manages a large capacity storage, and the SyncAgent, which is a synchronization module. Although the SyncAgent performs an actual function of implementing synchronizations, the SyncAgent module is installed at the Storage node in order to control the synchronization in the entire system. 3 Server Virtualization For providing the DTV, several servers are required in the aspect of management. A total of 24 virtualization servers are operated using 6 physical servers by applying the cloud computing that shows the most excellent advantage in the effective operation of resources and the cost reduction. Fig. 4 Configuration of server virtualization 3.1 Configuration of server virtualization layers The server virtualization is an essential element and designed using following components. The Xen virtualization environment is configured following some components for deploying server images. - Xen Hypervisor - Domain 0 - Domain Management and Control (Xen DM&C) - Domain U(Dom U) PV Guest - Domain U(Dom U) HVM Guest Fig. 5 Basic structure of the components 130

5 3.2 Caching Virtualization Layer The core idea of the expansion ability of the caching service layer is the server virtualization logic. For minimizing users contents requests and loads of the storage system, a caching server is required for the corresponding broad casting service. As the caching server stores the contents, which are largely used, it makes possible to provide high quality services to users and has a specific storage space for uploading bidirectional services. Fig. 6 shows the expansion of the caching cloud service by the load balancing service according to the amount of users (subscribers ) requests and virtualization management logics. Fig. 6 Caching Service 4 Verification and extension of Cloud Computing Testbed 4.1 State of H/W configurations Table 1 shows the state of H/W configurations for designing the Cloud Computing Testbed proposed in this study. Table 1. State of H/W configurations Item VM S/W Term Server Virtualization (6 EA) Storage Virtualization (2 EA) CentS 5.3 MySQL 5.x Tomcat 6.x Apache 2.x Java 1.6.x C++ PHP 5.x CentS 5.3 Java 1.6.x Hadoop 0.20.x DB Server Service Monitoring Server EPG/SMS Server GLB/SCS Server Synchronization Server Caching Server RDP Connection- STB Server Hadoop 4.2 State of S/W applications Table 2 shows the state of S/W applications. 131

6 Table2. State of S/W Application Item Service Module Cache manager Synchronization server Monitoring Contents Services Contents Distribution Storage User QoS Load balancer Service Demon Contents synchronization Hadoop monitoring STB monitoring Storage Contents Storage Hadoop 4.3 Appropriateness and application of S/W Table 3 represents the evaluation of the appropriateness of the cache manager, load balancer, service demon, and contents synchronization applied in this study. Table 3. Appropriateness of S/W Item Term Check Cache Manager Is it easy to install a corresponding module to the S of Cloud Computing TestBed? Is it is to install a corresponding module to the S of Cloud Computing TestBed? Load Balancer Service Demon Contents Synchronization Is it is to install a corresponding module to the S of Cloud Computing TestBed? Is it is to install a corresponding module to the S of Cloud Computing TestBed? Hadoop Monitoring Is it is to install a corresponding module to the S of Cloud Computing TestBed? 132

7 STB Monitoring Is it is to install a corresponding module to the S of Cloud Computing TestBed? Is it is to install a corresponding module to the S of Cloud Computing TestBed? Hadoop 5 Conclusion In this study, several servers are virtualized for a single physical equipment using cloud computing in order to build the Cloud Computing TestBed. It makes possible to use it without any high cost duplicated infrastructures because it can be shared by several Ss and used as a low cost broadcasting infrastructure. Various excellent digital broadcasting environments can be considered using different resources established using the proposed Cloud Computing TestBed. Although it is operated by a single source, other open sources and licensed programs can be used to develop and search low cost and high efficiency sources through some tests and comparisons. In addition, it is possible to develop various methods for responding recently issued cyber terrors and crimes including other problems in server downs by excessive accesses, hacking, and security of broadcasting contents. Based on the results of this study, a storage cloud resource information system will be established by integrating the software information in storage cloud resources in addition to the hardware of storage cloud resources. Then, it will be used to provide the effective and extensible storage cloud resource information system through managing the static information, which is not changed, in storage cloud resources and the dynamic information in storage cloud resources that is varied in information and contents in real-time. 6 REFERENCES [1] Jong Won Yang, KJ Hum, KS Hyun and YH Bang, SD Lee "Design and Proposal of a Next Generation Digital Cable Broadcasting Service-Based System Using Cloud Storage Computing Environments," Proceedings of the 2nd International Conference on Interaction Sciences: ICIS 2009,Seoul, Republic of Korea, pp.1461~1465, [2] Jong Won Yang, SD Lee, JH Jang System Design and Virtualization Method for Next Generation D- CATV Base Cloud Computing Service, IMS2010, Seoul Republic of Korea, pp166~171, [3] obodziń, skibogdan "Tests of Cloud Computing and Storage System features for use in H1 Collaboration Data Preservation mode" Journal of physics. Conference seriesv.331 no.6, pp , [4] Arun Iyengar and Jim Challenger, "Improving Web Server Performance by Caching Dynamic Data" USITS'97 Proceedings of the USENIX Symposium on Internet Technologies and Systems on USENIX Symposium on Internet Technologies and Systems [5] Wikipedia, [6] Dave Thomas, Enabling Application Agility Software as a Service, Cloud Computing and Dynamic Languages, Journal of bject Technology, Vol.7, No.4, May-June