THE telecom industry is currently in a state

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1 DISTRIBUTED PROCESSING ARCHITECTURES MAGAZINE, VOL. 1, NO. 1, JULY Virtual Distributed Servers: Flexible High Availability for Telecom Application Middleware Luis Pablo Prieto Student, DPA Abstract Telecom applications and application servers are the only common elements among the different next generation service delivery platforms proposed so far. JAIN SLEE is the most promising middleware for developing new telecom applications with the levels of availability and performance desired by operators. However, current commercial clustering methods for high availability can be too expensive for starting third party service providers. This document presents an alternative way of implementing high availability in JAIN SLEE, through the use of virtual nodes and distributed servers. This method should provide acceptable levels of availability under a variety of unexpensive hardware and network configurations. This would be an ideal choice for starting service providers which can foster the development and deployment of new telecom applications. Index Terms Telecom applications, middleware, high availability, JAIN SLEE 1 INTRODUCTION THE telecom industry is currently in a state of flux. The decreasing revenues of traditional telecom services and the rise of the Internet as a capable provider for almost any kind of multimedia service, is making network operators scramble to find new services and applications which help them regain the market dominance that they have been losing lately. These efforts are far from homogeneous, with operators (and network equipment vendors) throwing around network architectures under the blurry banners of Next Generation Networks (NGN), Service Delivery Platforms (SDPs) or IP Multimedia Subsystem (IMS) in a rather inconsistent fashion. However, if there is a common emerging aspect in all these initiatives (be them either the SIP-based, signaling-oriented IMS [1], a plain IT-based SDP [2] or a combination of both), it is the central role that advanced telecom applications will play in the delivery of services to the end user, independently of the network architecture used to deliver them. Alongside these telecom applications, the concept Student in Distributed Processing Architectures (towards Ph.D. in ICT at ETSIT, UVa) see Manuscript submitted July 9th, of the application server (AS) that hosts those applications is also a recurring item in any architectural proposition for delivery of revenue-generating telecom applications, like videoconference, gaming, multimedia content delivery, etc [3], [4]. Another common pattern in the evolution of telecom networks, no matter the concrete architecture of the network, is the possibility for third parties to provide these telecom services, in an attempt to mimick the success of the Internet in creating its own open services market, resulting in the development of many innovative services [5]. Even if on a first instance the application servers were implemented using Internet / web service middlewares like CGI or Java Servlets (or slightly modified variants of them), the peculiar needs of telecom services with regard to their performance and availability, gave rise to the concept of Service Logic Execution Environments (SLEEs). These SLEEs are event-driven, high-throughput, low-latency environments designed specifically for communication applications, and their most representative example, the Java-based JAIN SLEE [6] is used for implementing most of the commercial NGN entities, including application servers. Telecom services have a distinct set of availability and performance requirements, which are often represented as Service Level Agreements (SLAs).

2 DISTRIBUTED PROCESSING ARCHITECTURES MAGAZINE, VOL. 1, NO. 1, JULY JAIN SLEE was already designed with this kind of performance in mind; however, software middleware can only take us so far in terms of high availability. In order to provide for these requirements, current JAIN SLEE implementations rely on e.g. fault-tolerant clusters, normally implemented using low-level techniques [7] and specialized hardware based on the ATCA architecture [8]. However, this kind of clustering solutions can be too costly (in terms of equipment and network infrastructure) for implementing a single telecom application server, specially in the case of starting third party service providers. In this paper, we present an alternative implementation method for high availability in JAIN SLEE, which can be used over common hardware and network infrastructures, to give acceptable levels of fault tolerance. This method is based on virtual nodes [9] and distributed servers [9], two technologies which are part of the XtreemOS grid application toolkit [10]. Grid computing [11] technologies themselves are not used, although the extension of this method to a multi-domain telecom service market could make good use of them. The document is structured as follows: first, the current situation and characteristics of telecom applications are detailed, including current implementation approaches and middlewares, and paying special attention to the problem of high availability. Afterwards, the objectives and methodology of the proposal are detailed, alongside the main contributions of the proposal. Finally, an evaluation scheme is suggested, and conclusions and potential further research are discussed. 2 HIGH AVAILABILITY IN TELECOM APPLICA- TIONS The concept of telecom applications or telecom services has evolved dramatically from the days of the PSTN-based plain voice communication (a.k.a. telephone) and the first Intelligent Networks (IN). In this evolution, it has been merged with many other concepts coming from the Internet and the Web universes, to include any kind of multimedia and data communication that takes place through a telecom network [5]. Today, these multimeda/telecom services include applications as diverse as videoconference, instant messaging or IP-TV broadcasting. However, the most important sources of revenue among these are the ones related to gaming, music and, in general, multimedia content delivery [4]. 2.1 Service providers and SLAs in telecom applications In this cross-breeding process among Internet and telecom industries, the figure of the third party service provider has emerged as a successful driver in the design, development and exploitation of innovative Internet services in an open services market, which was made possible by the adoption of Service-Oriented Architectures (SOA) [12]. In its search for new, revenue-generating applications, the telecom industry is also turning to this open services market model, and thus today virtually every telecom service delivery platform and architecture supports the idea of third party service providers [5]. In the context of the telecom industry, the relationship between end users (specially corporations) and telecom service providers is often represented by service-level agreements (SLAs). These SLAs describe the conditions under which the aforementioned services must be provided, and the compensations to be given to the customers should these conditions fail. These conditions are mostly related to the availability (e.g. allowed downtime per month) and the performance (e.g. round-trip delay in milliseconds) of the service. In fact, similar mechanisms are also placed between network operators and the network equipment providers (NEPs) that manufacture the links and machines that conform telecom networks [13]. In the same way, the relationship between network operators and third party service providers is normally governed by SLAs. The most common parameters in this case are availability, reliability, troubleshooting delay, service provisioning, response time, latency and throughput [14]. The values guaranteed for this kind of services vary wildly, depending on the concrete nature of the service, from very loose for e.g. a messaging application, to very strict, for real-time multimedia communications like videoconference. However, the number of third party telecom service providers has been up to now, surprisingly low, indicating that probably the barriers of entry to market for telecom applications is not as low as their Internet counterparts. This also could be due to the lack of a clear, open telecom services market that can match the open services market of the Internet.

3 DISTRIBUTED PROCESSING ARCHITECTURES MAGAZINE, VOL. 1, NO. 1, JULY Telecom application middlewares and JAIN SLEE The middlewares used for developing telecom applications have also evolved along with the network architectures. With the advent of Internet technologies and protocols such as IETF s Session Initiation Protocol (SIP) [15], most network hardware has been transformed to software entities (i.e. softswitches) that use these protocols for signaling communication sessions and media flows. At first, the applications and application servers were implemented using middlewares inherited from the Web and Web Service backgrounds, slightly modified for use in telecom environments, such as SIP CGI [16] and SIP servlets [17]. In fact, much of the current research in this field is still implemented using them, since they are well-known and relatively easy to program (albeit requiring a somewhat deep knowledge of SIP protocols) [3]. However, the realization of production-stregth telecom platforms, with their very restrictive SLAs 1, called for more advanced middlewares that could take care of these requirements transparently. Thus, the concept of Service Logic Execution Environments (SLEE) appeared. SLEEs are often defined as high-throughput, lowlatency event processing application environments, which provide a framework and component model for event driven applications. The SLEE was specifically developed for telecommunications systems, although it is generic in design to provide application to other specialized event driven systems [18]. By far, the most famous and widely used SLEE in the telecom industry is its Java-based specification, JAIN SLEE [19]. This specification provides an object-based component model and API for telecom application programmers, and hides much of the complexity regarding the underlying signaling protocols and network architectures. Thus, this middleware allows for portability of telecom applications among different networks, provided that adequate network plug-ins (Resource Adaptors, in JSLEE speech) are available. There are currently a number of JAIN SLEE implementations, ranging from the official Reference Implementation (RI) [20] to open source and commercial implementations such as Mobicents [21], 1. For example, typical availability requirements for telecom components follow the five nines rule, that is, % availability, or 6 minutes downtime per month. OpenCloud [22] or jnetx [23]. 2.3 Fault tolerance in JAIN SLEE Apart from defining the (object-based) component model for structuring the logic of the communication applications and composing them into higher level applications, JAIN SLEE was designed for concurrency and fault-tolerance, by defining lightweight transactions for replication demarcation [24]. The concrete implementation of fault tolerant mechanisms is not tackled in the specification, and implementors are free to realize them as they see fit. Although concrete data is hard to come by, it seems that most commercial implementors are using clustering solutions, based on the ATCA architecture for telecom equipment [8] and Carrier- Grade operating systems [25]. For example, benchmarking studies such as [7] and the official documentation of one of the most popular implementations [22] point in this direction, providing software fault tolerance using a variant of the method outlined in [26], for high-performance computing (HPC) clusters. These solutions make use of specialized hardware and software mechanisms for obtaining maximum performance and very high levels of availability. But these impressive specs come at a price, and purchasing and setting up a high-performance cluster server [27] running Rhino [22] can be too much for an aspiring telecom service provider, who is not used to spending millions of dollars in hardware solutions. 3 GOAL: FLEXIBLE HIGH AVAILABILITY IN TELECOM MIDDLEWARE In order to provide an application server environment which is beneficial for starting third party service providers, it is our goal to provide an alternative implementation method for high availability in JAIN SLEE middlewares, which can achieve reasonable availability levels for most telecom applications. By reasonable levels we understand that, although % availability is always desirable, clients for telecom services in many cases consider that values as low as 99.9% or 99.7% are also acceptable [13]. We target high availability as the main feature of our efforts because other SLA requirements, mostly related to performance, are generally considered to

4 DISTRIBUTED PROCESSING ARCHITECTURES MAGAZINE, VOL. 1, NO. 1, JULY be covered by JAIN SLEE s software design. Availability is a different matter, since the middleware relies in this case on the underlying infrastructure to achieve it. Another desirable requirement of this method should be its flexibility in terms of network architecture and hardware platform, to the extreme that it should be able to achieve its objectives when running over common PC hardware across one or more server sites communicating through wide area networks (WAN). 4 METHODOLOGY The methodology to be followed to design this method can be divided into several phases: First, a method for reliable evaluation of the architecture and prototype must be proposed. To the best of our knowledge, no reliable method for modelling and translating from machine specs and software design to SLA parameters (e.g. 99.9% reliability) has been found. A deeper analysis of this problem should be performed, since it will be a crucial point in evaluating the proposed solution, and without it our results would hardly be provable. Afterwards, a deeper analysis of current high availability implementations in JAIN SLEE should be performed, to estimate accurately its reliance on the concrete clustering mechanisms such as ATCA. If at all possible, these implementations will be deployed over different hardware and network architectures such as the ones proposed above, to evaluate their impact in the level of availability that can be obtained. Then, our proposed solution must be more concretely described and a prototype implementation shall be developed. As a starting point for this implementation, we propose to integrate virtual nodes and distributed servers into a JAIN SLEE implementation (such as the open source Mobicents implementation). The usage of these two technologies obeys to the fact that, to achieve high availability through replication of resources, two aspects must be kept in mind: To replicate the resources and to establish adequate failover mechanisms among them so that entities accessing them do not notice the potential failures. Virtual nodes [28] is a middleware that helps developers to replicate services, both for performance and fault tolerance reasons. To provide methods for accessing those replicated elements as if they were a single resource (what is called a single system image). Distributed servers [9] use IPv6 versatile anycast methods to present a group of server processes as a single entity, with no modifications to the client side software. Finally, the prototype implementation will be evaluated, applying the aformentioned translation methods to see if the desired levels of availability have been achieved. Please refer to section 6 for more information. 5 CONTRIBUTIONS The main expected contributions of this proposal should be: The development of methods for modelling network, hardware and software designs and evaluating them to ascertain their expected availability in SLA-friendly terms, if no adequate one is found in the literature. The integration of flexible high availability mechanisms into the JAIN SLEE architecture and, more specifically, into a concrete implementation of it, while maintaining compatibility for JAIN SLEE applications. This resulting implementation will probably be released as open source, and/or merged within the original one, to enhance its functionality. 6 EVALUATION After the integration of the new availability mechanisms into a JAIN SLEE implementation, the resulting middleware will be evaluated to ascertain the adequacy of the solution in terms of availability. In order to perform this evaluation, the system prototype should be deployed over a pre-defined hardware and network system that consists, as we have already pointed out, of various PC-based application servers communicating across a (real or simulated) wide area network. Once this testbed system is set up, a battery of tests will be performed, including random server failures, network partitions and re-entrance of nodes etc. Parameters such as the elapsed time until the other nodes detect the failure or the failover behavior of the applications should be measured,

5 DISTRIBUTED PROCESSING ARCHITECTURES MAGAZINE, VOL. 1, NO. 1, JULY and translated into a SLA-friendly reliability factor using the methods developed to that effect. These tests should also be performed several times, using different kinds of telecom applications. In order to provide a representative sampling of the telecom application spectrum, at least one of each of these kinds of applications should be tested: Real-time communication applications (e.g. videoconference) Multiplayer gaming applications Multimedia content delivery (e.g. music delivery or IP-TV) Non real-time communication applications (e.g. messaging) Furthermore, the original clustering availability mechanisms should also be evaluated (if at all possible) under this very same configurations, to assess the gain that has been achieved with the new system. 7 CONCLUSIONS AND FUTURE WORK As the telecom industry strives to find revenuegenerating applications, a number of initiatives and network architectures have been proposed. On top of every one of them, telecom application servers provide the signaling and service logics necessary for those services to happen, regardless of the real network underneath. JAIN SLEE is the most promising middleware for implementing telecom applications and application servers, since it takes into account the high requirements of these applications in terms of availability and performance. However, the implementation of high availability mechanisms currently rely on lowlevel clustering methods designed for HPC equipment, where performance is considered much more important than price. We have presented a proposal for designing an alternative method for achieving (reasonable levels of) high availability without resorting to HPC clustering methods, even across wide area networks. Also, a prototype implementation of this method has been proposed, using virtual nodes and distributed servers, two components of the XtreemOS grid application toolkit. Moreover, an scheme for the evaluation of the method has been outlined. The research work described in this document is just a brief summary of a work that could span several years. Nevertheless, we can already spot a few lines that could be worth investigating once this work is finished. One of them would be to investigate how service level agreements (SLAs) themselves could be integrated with the presented model, so that the high availability features could be auto-configured directly with that kind of input. Another one would be the extension of this scheme (and, in fact, the general JAIN SLEE high availability structure) to span several administrative domains which provide resources in an open JSLEE application hosting market. In this effort, the application of grid computing technologies and mechanisms could undoubtedly prove very useful. REFERENCES [1] G. Camarillo and M. A. Garcia-Martin, The 3GPP IP Multimedia Subsystem, 2nd Edition. Wiley and Sons, [2] C. J. Pavlovski and Q. Staes-Polet, Digital media and entertainment service delivery platform, in Proc. 1st ACM Intl Wksp. Multimedia Service Composition, Singapore, 2005, p [3] H. Khlifi and J.-C. Grégoire, Ims application servers: Roles, requirements, and implementation technologies, Internet Computing, IEEE, vol. 12, no. 3, pp , May- June [4] C. J. Pavlovski, Service delivery platforms in practice, IEEE Communications Magazine, Mar [5] T. Magedanz, N. Blum, and S. Dutkowski, Evolution of SOA Concepts in Telecommunications, IEEE Computer Magazine, Nov [6] University of Otago. JAIN SLEE official web. Web site, Last visit: May 29, [7] Benchmarking the OpenCloud SIP Application Server on Intel-Based Modular Communications Platforms, White Paper, Last visit: July 8, 2008, Intel Corp. and OpenCloud Ltd., [8] PCI Industrial Computer Manufacturers Group. Advanced telecom computing architecture specifications page. Web site, Last visit: May 29, [9] XtreemOS Consortium, First Prototype Version of Ad Hoc Distributed Servers, Integrated Project, Nov [10] X. Consortium. (2008) Xtreemos: A linux-based operating system to support virtual organizations for next generation grids. Web site, Last visit: May 29, [11] I. Foster and C. Kesselman, The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann Publishers, [12] M.P. Papazoglou and D. Georgakopoulos, Service Oriented Computing, Communications of the ACM, Oct [13] J. H. Lee, Enterprise customer s needs for sla on telecom services in korea, Management of Engineering and Technology, Portland International Center for, pp , Aug [14] Jong-Tae Park and Jong-Wook Baek and James Won-Ki Hong, Management of Service Level Agreements for Multimedia Internet Service Using a Utility Model, IEEE Communications Magazine, May 2001.

6 DISTRIBUTED PROCESSING ARCHITECTURES MAGAZINE, VOL. 1, NO. 1, JULY [15] J. Rosenberg, H. Schulzrinne, G. Camarillo, A. Johnston, J. Peterson, R. Sparks, M. Handley, and E. Schooler, SIP: Session Initiation Protocol, RFC 3261 (Proposed Standard), Jun. 2002, updated by RFCs 3265, 3853, 4320, [Online]. Available: [16] J. Lennox, H. Schulzrinne, and J. Rosenberg, Common gateway interface for SIP, IETF, RFC 3050, Jan [17] JSR Expert Group, SIP Servlet API Specification Version 1.0, JSR 116, Feb [18] Phelim O Doherty. (2003, May) JAIN SLEE Principles. Web site, slee principles.html. Last visit: July 8, [19] JSR Expert Group, JAIN SLEE API Specification Version 1.0, JSR 22, Mar [20] OpenCloud Ltd. JAIN SLEE Reference Implementation. Web site, Last visit: July 8, [21] Red Hat Middleware, LLC. (2008) Mobicents official page. Web site, Last visit: July 8, [22] OpenCloud Ltd. (2008) OpenCloud and Rhino Application Server official page. Web site, Last visit: July 8, [23] jnetx. (2008) jnetx official page. Web site, Last visit: July 8, [24] David Ferry and Swee Lim. (2006) An Introduction to JAIN SLEE. Web site, Last visit: July 8, [25] The Linux Foundation. Carrier Grade Linux official page. Web site, Grade Linux. Last visit: May 29, [26] K. Uhlemann, C. Engelmann, and S. Scott, Joshua: Symmetric active/active replication for highly available hpc job and resource management, Cluster Computing, 2006 IEEE International Conference on, pp. 1 10, Sept [27] OpenCloud Ltd. (2008) Rhino Scalability and Performance on Blade hardware. Web site, Last visit: July 8, [28] XtreemOS Consortium, Design and Specification of a Virtual Node System, Integrated Project, Dec Luis Pablo Prieto graduated in 2001 as Telecom Engineer at Valladolid University (UVa). That very same year he was hired at Telefónica R&D, where he is currently working in the XTREEMOS EU research project. Apart from mobile and grid computing, his research interests focus on computer supported collaborative work (CSCW), and its applications to the fields of arts and creativity. He combines research with a musical career, and he obtained the Middle Degree in Piano in 1995 in Valladolid Conservatory.