A New Architecture of HSS Based on Cloud Computing

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1 A New Architecture of HSS Basedon Cloud Computing Tianpu Yang, Xiangming Wen, Yong Sun, Zhenmin Zhao, Yuedui Wang School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing, , China Abstract Ip Multimedia Subsystem (IMS) is the key technology of the next generation network (NGN) and the optimal solution of mobile and fixed network convergence which is approved by the public. Home Subscribe Server (HSS) is not only the data center of the system, but also the key of supporting the user mobility and call controlling. Since the growth of user data, the capacity of HSS storage and computing to the IMS system is very critical. Cloud computing is a successful example for solving the problem that originates from the massive growth of data by using distributed storage and computing in the internet industry. In this paper, a improved HSS architecture based on distributed cloud computing will be designed, thus it will have the better performance on data storage and delivery and the performance of the whole IMS system will be improved. Index Terms HSS; IMS; Cloud computing; Cloud storage; response time I. INTRODUCTION Since the 20th century, under the impact of Internet, as a representative of the new communication mode and IT technology, the traditional telecom network change relatively slow development step before into a rapid development track. No doubt, with the rapid development of economy and peoples increasing demanding for communication, the next generation network convergence also becomes an inevitable trend in the development of communication. Therefore, as the authority of the international organization for standardization of researching 3G network technology, 3GPP proposed to support IP multimedia business subsystems IMS(Ip Multimedia Subsystem) in Release 5 version[1]. IMS is the middle control layer between carrying network and the service network, providing access need of the fixed network and various business needs of the future network. It has become the direction of the next generation network development, which is helpful to realize sharing and convergence of the future fixed and mobile network in the core business control layer and provide the support of high-rise various business. IMS introduces HSS(Home Subscribe Server) function entity and defines it as a database which centralized store user business data in future 3G network. As mobile phones and mobile users growing in the future, capacity of HSS on carrying /11/$ IEEE data storage will become more and more. And adding roaming user information management, higher requirement is needed in the storage and processing ability of HSS. Cloud Computing is a development of the distributed parallel computing and Grid computing [2]. It make all application systems acquire computing abilities and storage space and information services through distributing computing tasks to resources pool which be constituted by a lot of computers. Cloud computing is a successful application in handling large amounts of data in Internet industry. This paper will design a distributed core network structure based on cloud storage and the cloud computing in computer application. II. IMS NETWORK FUNCTION ENTITY The 3GPP IMS introduces layering network structure and divides it into 3 layers, business network, core network and access network. Access network support multiple technologies, including the 3GPP GPRS, WLAN, etc, providing access, mobility management. IMS and the lower IP access network are mutually independent with each other. Core networks is responsible for business session controlling, providing Qos guarantee and billing management; Business network, including many kinds of business providing technology, promotes the development of multimedia services by opening business interface and simple protocol (SIP) controlling.the main function entity of the IMS system includes the following aspects. These function entities in IMS architecture position defined in 3GPP framework is shown in Figure 1. Figure 1. IMS network function entity defined by 3GPP IMS network function entity can be divided into three layers [3].

2 A. Business application layer It is composed by various application server (AS) and content server. AS is used to provide various value-added services to IMS users. Main nets unit is a series of multimedia business application platform provided by CAMEL, OSA/ Parlay and SIP technology. Currently, there are mainly three business providing ways in IMS domain. They are SIP - AS providing, Parlay gateways providing and SCP providing. It will use basic call server way to achieve for the traditional basic business. B. Controlling layer It is composed by network controlling servers. It is responsible for call session management, setting, modifying and releasing. IP multimedia business signaling controlling is finished in this layer. It mainly includes call session control function(cscf), home subscriber server(hss), border gateway control function(bgcf), media gateway control function (MGCF) and signaling gateway(sgw). Actually, the CSCF is responsible for IMS session controlling and divided into P- CSCF, I-CSCF and S-CSCF. P-CSCF transmits SIP session, finding the related I-CSCF, realizing QoS management, and collecting billing information; I-CSCF is responsible for selecting S-CSCF for users. S-CSCF provides users business management. HSS supports user roaming, saving user authentication information, encrypted information and integrity information, checking user validity when a user try to access to IMS resources information, supporting IMS to establish session process. HSS decides which entity control the session when user business is finished. BGCF finishes routing function to the PSTN/ISDN. MGCF provides SIP and H. 248 communication, and controls media gateways through the H SGW completes communication in signaling the transport layer in IP and CS domain. C. Connection layer It Includes all kinds of terminal (such as mobile SIP terminals, PDA, PC, STB, etc) and IP access network. The main equipments are SGSN (GPRS business support node), GGSN (GPRS gateway support node) and MGW (media gateway). Among them, SGSN and GGSN can support IMS by only reusing current network equipments to do related configuration, and need not to upgrade hardware. MGW is the function entity of media stream communication in IMS domain and CS domain, mainly to solve speech communication problems. Various networks can access IMS network because of different access technologies. For example, moving pattern can access IMS network through GGSN and SGSN. Fixed way, such as DSL access, can access IMS network through digital subscriber line access multiplex (DSLAM) and broadband access server (BRAS).Wireless access based on WiFi IP access, can access IMS network through wireless access gate(wag) and packet data gate (PDG). III. HSS FUNCTION MODEL The core characteristics of IMS is to use SIP to the call controlling, provide various business flexible and access irrelevant. IMS core network is composed by P -CSCF, I - CSCF, S - CSCF, HSS four parts [4]. HSS is responsible for managing and maintaining all kinds of data subscribed by access user, including fixed and mobile, broad bandwidth and narrow bandwidth. HSS also supports IMS business access authentication, roaming registration, mobile called routing addressing function. In addition, HSS can also provide information needed by S -CSCF to choice for I -CSCF and support signing data with AS each other. The data stored in HSS mainly includes user identity, registration information, access parameters and service trigger information. Figure 2. HSS function model defined by 3GPP From HSS function model above, HSS can be divided several function models which are showed in Figure 2. Mobility management: this function is used to support user mobility in the IMS core domain. Call/session establishment support: HSS supports call/session in IMS core domain.when a user is called, HSS offers user the current session controlling entity. User safety: HSS generates authentication data in IMS core domain. After generating integrity encryption key and encryption key, HSS provides these data to some related entities CSCF in core domain, and finishes certification of the user access. User identification: HSS can provide all marked relationships of user in system, and can determine the only user. Private user identity and public user identity are included in IMS core domain. Access right detection: when receiving request from CSCF, HSS provides mobile access authentication to user by checking if the user can roam to the network where the user will visit to. Business right detection: HSS not only provides authentication to user call establishing and business

transferring, but also provides relevant business changing information to basic CSCF entity. Application server support: HSS provides the user business signing information in IMS core domain.

3 transferring, but also provides relevant business changing information to basic CSCF entity. Application server support: HSS provides the user business signing information in IMS core domain. CAMEL business support: HSS, SIP application server and OSA SCS interact with each other to support applications in IMS core domain; HSS and IM - SSF interact to support relevant CAMEL business in IMS core domain. IV. CLOUD COMPUTING There is little consensus on how to define the Cloud [5]. We add yet another definition to the already saturated list of definitions for Cloud Computing: A large-scale distributed computing paradigm that is driven by economies of scale, in which a pool of abstracted, virtualized, dynamically-scalable, managed computing power, storage, platforms, and services are delivered on demand to external customers over the Internet. Some examples of emerging Cloud computing infrastructures are Microsoft Azure [6], Amazon EC2, Google App Engine, and Aneka [7]. Figure 3 shows the layered design of Cloud computing architecture. Physical Cloud resources along with core middleware capabilities form the basis for delivering IaaS and PaaS. The user-level middleware aims at providing SaaS capabilities. The top layer focuses on application services (SaaS) by making use of services provided by the lower layer services. PaaS/SaaS services are often developed and provided by 3rd party service providers, who are different from the IaaS providers [8]. The Cloud storage brings us large benefits. First, users are charged only for their use of storage and transfer of content, which is typically in the order of cents per gigabyte. Second, users do not need to install physical storage devices in their own datacenter or offices, which will reduce IT and hosting costs. Third, storage maintenance tasks, such as backup, data replication, and purchasing additional storage devices are offloaded to the responsibility of a service provider, allowing organizations to focus on their core business. Because of the advantages of the Cloud storage, numerous Cloud storage providers have recently emerged to provide Internet-enabled content storage and delivery capabilities in several continents[4]. The most representative cloud storage service provider is Amazon[9]. Amazon through S3 provides a simple web services interface that can be used to store and retrieve any amount of data, at any time, from anywhere on the web. It gives any user access to the same highly scalable, reliable, secure, fast, inexpensive infrastructure that Amazon uses to run its own global network of web sites. V. IMPROVED HSS ARCHITECTURE The improved HSS architecture includes resource pool layer and management layer [10]. It is shown in Figure 4. Resource pool layer is composed by some same type of structures or close to the same type of structure resources through collecting a lot of same kind resources, such as computing resources pool, data resource pool, etc. Constructing the resource pool is mainly the physical resource integration and management work. Figure 4. improved HSS architecture Figure 3. Layered Cloud Computing architecture Cloud storage is a new concept developed from the concept of the Cloud computing, which is a system that uses application software to make large amounts of storage equipments implement collaborative work and provide data storage and business visit service by hosting application, the grid technology, distributed file system, and so on. Management intermediate layer is responsible for managing the distributed HSS resources, scheduling many application tasks, and making resource provide the service for application effectively and safely. HSS intermediate management layer is responsible for resource management, task management, user management and safety management. Resource management is responsible for balancing to use cloud resources node, detecting note fault and trying to restore it or screen it, and making a statistics of the information of the use of resources. Task management is responsible for implementing the tasks submitted by the user or application, including finishing deployment and management of user tasks image, task

execution environment of user program, and billing to the use of user, etc.

4 scheduling, task execution, and the management of task life cycle period. User management is an essential step to realize the business model of cloud computing, including providing customer interaction interface, managing and identifying the user's identity, creating execution environment of user program, and billing to the use of user, etc. Safety management guarantee overall security of cloud computing facilities, including identity authentication, visiting authorization and safety audit, etc. VI. SIMULATION AND CONCLUSION In order to evaluate the performance of the improved HSS architecture, the CloudAnalyst will be used for simulation, which is a toolkit for modeling and simulation of Cloud Computing developed by The Cloud Computing and Distributed Systems (CLOUDS) Laboratory, University of Melbourne[11]. In the simulation, we will find that the performance of the improved HSS architecture will be improved through the changing of the response time of the data sources by comparing the improved architecture with the traditional architecture. A. The response time of the traditional model Traditionally, there is only one DataCenter used to store data in a big zone. These data include kinds of information which is often used when a user is communicating, such as user data. So when a user starts to use this system in the zone, the DataCenter is the only access to acquire the data. In the simulation experiments, we design a DataCenter(DC1) located region 0 to simulate HSS which is used for user data concentration storage in the traditional core network and provides the user data to support users in the zone. And four users (U1, U2, U3 and U4) are created in different regions. U1 stays in the region0, U2 stays in the region1, U3 stays in the region2 andu4 stays in the region3.all Us need to visit the DC1 to get the data they needed. The simulation result is depicted in Figure5 and Figure6. Figure 6. Simulation result 1.2 According to the simulation results, it can be seen clearly that the average response time is ms between U1 and DC1, while it is ms between U2 and DC1, ms between U3 and DC1 and ms between U4 and DC1. Obviously, ms, ms and ms are too long to be accepted by the Us, which is a great drawback of the traditional model. B. The response time of the improved HSS architecture based on Cloud storage The improved HSS architecture based on Cloud storage distributed constructing model will set data center distributed which is used to store the user data and choose the nearest or freest data center to provide the fastest and most safety data transmission to the user in the zone through the load balance and a shortest path policy, so the data transmission time shortens and the data center load pressure reduces too. In this simulation for the improved HSS architecture based on Cloud storage, four DataCenters (DC1, DC2, DC3 anddc4) served by fives WMs are created in region0, region1, region2 and region3. And four users (U1, U2, U3 andu4) are created in different regions. U1 stays in the region0, U2 stays in the region1, U3 stays in the region2 and U4 stays in the region3.since the implement of the data delivery, all the Us can get the data needed from the most appropriate DC. The simulation result is depicted in Figure6 and Figure7. Figure 5. Simulation result 1.1

Figure 7. Simulation result 2.1 Figure 8. Simulation result 2.2 According to the simulation results, the average response times between U and DC in four regions are all 50ms.

5 Figure 7. Simulation result 2.1 Figure 8. Simulation result 2.2 According to the simulation results, the average response times between U and DC in four regions are all 50ms. Comparing them with the result of traditional model, the average response times for U2, U3 and U4 are greatly reduced. Obviously, the improved HSS architecture system based on Cloud Storage can provide users with better service. C. Discussion of the results No doubt, from the result of the simulation on comparing the traditional mode with the HSS mode in the Table 1, we can find that the response time of the improved HSS mode based on distributed cloud storage system is shorter than the traditional mode. This is mainly because of the improved version which adopts the distributed processing, and makes the data dynamic equilibrium when the data center transmits data, thus make the response time reduced. Summarizing the data from the simulation results above and put them in a table, we can see clearly that the response time of U1 almost have no change but the others have changed a lot by comparing the improved HSS model with the traditional model. Analyzing the reasons, it is largely due to the improved HSS model adopt distributed architecture make different Us acquire the data from the nearest DCs and not have to acquire the data from DC1. So this saves a lot of response time. TABLE I. THE COMPARATION OF SIMULATION RESULTS Userbase Avg(ms)/traditional model Avg(ms)/improved model U U U U is used to store large user data to make it base on cloud storage distributed architecture. Thus, it can not only make the user data be stored in different data center which is a backup to increase security, but also make the distributed data center dynamic distribute corresponding data center to serve the user according to distance, free degree when user visit the datacenter to acquire the data needed to improve network usage. In the simulation experiments we simulate the system response time on comparing the improved network model with the traditional model. Obviously, from the results of simulation, the improved distributed HSS architecture is significantly better than the traditional network in response time. ACKNOWLEDGMENT This work was supported by the Beijing Municipal Science&Technology Commission (No.Z ), the National S&T Major Project of China (No.2009ZX ) and the Fund of National Nature Science of China (No ). REFERENCES [1] 3GPP TS Service requirements for the IP multimedia co re network subsystem, [2] Michael Armburst, Armando Fox, and Rean Griffith, et al. Above the Clouds: A Berkeley View of Cloud Computing, mimeo, UC Berkeley, RAD Laboratory, [3] 3GPP TS Network architecture. [4] 3GPP TS V6.7.0, IP Multimedia Subsystem(IMS): Stage 2. [5] Twenty Experts Define Cloud Computing, SYS-CON Media Inc, [6] D. Chappell. Introducing the Azure services platform. White paper, Oct [7] X. Chu et al. Aneka: Next-generation enterprise grid platform for e-science and e-business applications. Proceedings of the 3rd IEEE International Conference on e-science and Grid Computing, [8] R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg, and I. Brandic. Cloud Computing and Emerging IT Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility. Future Generation Computer Systems, 25(6): , Elsevier Science, June [9] Giuseppe DeCandia, Deniz Hastorun, Madan Jampani, Gunavardhan Kakulapati,Avinash Lakshman, Alex Pilchin, Swaminathan Sivasubramanian, Peter Vosshall and Werner Vogels. Dynamo: Amazon s Highly Available Key-value Store. [10] Peng Liu, Cloud Computing, Publishing House of Electronic Industry, [11] B. Wickremasinghe, R. Calheiros, and R. Buyya. CloudAnalyst: A CloudSim-based Visual Modeller for Analysing Cloud Computing Environments and Applications. Proceedings of the 24th IEEE International Conference on Advanced Information Networking and Applications (AINA 2010), Perth, Australia, April 20-23, VII. CONCLUSION In this paper, it shows you the IMS core network architecture and the improved model. Especially we change the HSS which

Status of IMS-Based Next Generation Networks for Fixed Mobile Convergence

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