Pre-print:
N. Kryvinska, C. Strauss, L. Auer, P. Zinterhof, “Conceptual Framework for Services Creation/Development Environment in Telecom Domain”, 10th International Conference on Information Integration and Web-based Applications & Services (iiWAS2008), in cooperation with ACM SIGWEB, 24-26 November, 2008, Linz, Austria, pp. 324-331.
Conceptual Framework for Services Creation/Development Environment in Telecom Domain Natalia Kryvinska, Christine Strauss, Lukas Auer,
Peter Zinterhof
Department of e-Business, Faculty of Business, Economics and Statistics, University of Vienna Bruenner Str. 72, A – 1210, Vienna, Austria
Department of Computer Sciences, University of Salzburg Jakob-Haringer-Str. 2, 5020 Salzburg, Austria
[email protected],
[email protected],
[email protected] ABSTRACT The telecom service providers (fixed and mobile) understand that they must bring in new smart services in order to attract new customers, retain existing ones and increase revenue. The challenges and goals for doing so are as follows: determining which services are needed; introducing more services in a faster manner and at lower costs; delivering innovative services in a way that allows existing users to migrate smoothly to new ones. These goals could not be achieved with traditional closed and proprietary network infrastructure, as the vendor lock-in involved in that infrastructure results in limited scope of services, and dependency on old business models. New services require a much greater degree of system flexibility, performance and scalability, as well as open standards. Next Generation Network (NGN) provide the means for enabling agile service creation capabilities that facilitate better user experiences by integrating both new and legacy services across any access. However, NGNs involve complex structures even for simple services as they consist of a large number of building blocks and necessitate hierarchical models with a lot of parallel subsystems. Thus, particular attention has to be paid to understanding and modelling the performance of these systems. The rationale of this paper lies in developing a design and engineering methodology (based on a mathematical foundation) that addresses the service creation aspects for those fields in which traditional approaches will not work for NGNs.
Categories and Subject Descriptors C.2.1 [Computer-Communication Networks]: Network Architecture and Design - distributed networks, network communications, network topology. G.3 [Probability and Statistics]: - Markov processes, Queueing theory.
General Terms Management, Performance, Design, Theory
[email protected]
Keywords Hierarchical modeling, Next Generation Network (NGN), Parallel queues, Queuing theory, Service Creation Environment (SCE), Service Delivery Platform (SDP).
1. INTRODUCTION The service providers nowadays are looking for the new strategies to attract new customers, hold on to existing ones, and increase the revenue. In view of the fact that it is not easy to predict which service will be widely accepted and generate profit, the strategy can not be based on single application. As an alternative, the environment that enables rapid creation, deployment, and delivery of multiple attractive services with low cost is highly desired. The smart services also require rich content which is provided with third-party content providers, so architecture has to be open to external providers as well. Conventional telecom architectures, based on proprietary hardware and software, are not ready for such demanding business requirements because traditional service building method requires complete vertical stacks for each new service, which means that services could not be shared between users of different networks (e.g., fixed, mobile, IP). Such an approach results in slow delivery of new services at high costs. The advanced services require much greater degree of system flexibility, performance and scalability, as well as open standards for both internal applications and external service providers, which calls for implementation of service network layer that separates services and applications from underlying network elements. Facing such demands service providers as well as network operators need to find a solution that protects their investment by re-using existing infrastructure and resources [1, 4, 25]. Next Generation Network (NGN), in this context, can be seen by service providers as a new revenue stream from their potential to increase service offerings. Therefore, it is very important to understand how proposed solutions in NGN can enable flexible and easy service creation both to service providers and third party application developers [2, 3].
1.1 What the Next Generation Network is?
−
In modern business environment customer services are the key to the success. At the center of these novel services is the Next Generation Network. So, the next-generation network is the next step in world communications, traditionally enabled by three separate networks: the PSTN voice network, the wireless network and the data network (the Internet). NGNs converge all three of these networks into a common packet infrastructure. This intelligent, highly efficient infrastructure delivers universal access and a host of new technologies, applications, and service opportunities. And, the real-time and non real-time communication services, content services, and transaction services are the three types of services that force NGNs.
Service Creation Environment Service Creation Environment
The services-oriented NGN gives service providers greater control, security, and reliability while it reduces their operating costs. Service providers can quickly and cost-effectively build new revenue. Built on open, modular elements, standard protocols, and open interfaces, the NGN caters to the specific needs of all users - enterprises, remote offices, telecommuters, and small office/ home office (SOHO) customers. The new class of services it enables is more flexible, scalable, and cost-efficient than services that have been offered in the past [1, 4, 26].
Application Server Application Server
Call Call Server Server
Access Access Network Network 2NGN 2NGN
1.2 The Requirements to the Services Development NGN application development has many common features with Internet application development. And, NGN applications development is accessible to a broader community, because of: −
easiness - the need for knowledge that is specific to telecommunications is less than before and it demands for a quick learning curve;
−
productivity - relies on the fact that a specific SCE is not provided commonly, some systems provide several levels of APIs. This brings the flexibility of choosing the most appropriate level of abstraction for a given application;
−
the creativity - can increase because there is a move to the use high-level application environments that can be deployed across different vendors. The use of IT technologies makes the range of programmable features available quite wide, promoting the mix of IT and telecommunications functionalities [2, 5].
2. COMPARATIVE ANALYSIS OF DIFFERENT SERVICE CREATION/ DEVELOPMENT TECHNOLOGIES 2.1 Evaluation Criteria The evaluation criteria used for classification and comparison of different service creation technologies are, as follows: −
network capabilities - based on the abstraction of underlying network infrastructure that can be used to exploit network functionalities; they can represent both functional (e.g. call control) and non-functional (e.g., authentication, logging) aspects.
reference architecture - defines which place a technology covers in the categorization, depicted in Figure 1. This layered architecture defines a distinction among technologies, depending on their characteristics: application server layer includes technologies used to execute services, programmed with tools, represented by the application creation environment layer; call server layer includes technologies handling routing and delivery of voice calls; media server layer represents technologies involved in multimedia communications, and messaging server stands for entities handling messaging and asynchronous communications. Media gateway layer represents networks related technologies.
Media Gateway
Media Media Server Server Media resource
Packet‐ ‐based Packet Packet‐based Network Network
Messaging Messaging Server Server Message resource
Figure 1. Reference architecture. −
interface abstraction - the interface evaluation defines the level of abstraction, the kind of interface, and its type of interface definition language. Regarding the abstraction level of an interface, an abstract interface hides technical details of the underlying technology to the developer, in order to gain more portability, easiness of use, concise programming.
−
interfaces and description languages - The kind of interface (KOI) describes the communications method by which the technology is exposing network capability to external systems.
−
suitability for third party development – (e.g., programmability) - describes the qualification of the technology in support of application development by third party developers, and the suitability to third party service providers.
−
easiness to use - it can be measured depending on how much knowledge/experience is required of the underlying technology;
−
industry support and maturity - measures technology’s availability and maturity, showing how well this technology is supported in the industry and provide a general statement as to the level of its maturity in relation to approved standards [2 ÷ 6].
2.2 Open Service Access (OSA)/Parlay The OSA/Parlay identifies and specifies a programming network interface in order to easily create applications using the network services (Figure 2) provided by the telecommunication networks. The set of service capability features (SCFs) could be incrementally extended, because one of the aims of OSA/Parlay is to provide an extendible and scalable interface that allows for
inclusion of new functionality in the network in future releases with a minimum impact on the applications using the OSA/Parlay interface. The key features of OSA/Parlay are: −
hiding the complexity of the network, its protocols and specific implementation from the applications;
−
being suitable to third party application development;
−
providing a secure, controlled access to network capabilities for third party service providers. Discovery
Application server
Application
OSA interface
framework framework
User location
HLR HLR
CSE CSE
Service registration
Considering the reference architecture, services running on different application servers could communicate using SOAP messages; another scenario can be made by a call server exposing WSDL interfaces (Figure 3) that offers network connectivity to a 3rd party service running in an application server external to the call server domain; intra-domain connectivity among different components can be obtained migrating to web services, when different technologies must communicate [2, 9 ÷ 11].
2.4 SIP servlets The SIP servlet API is a Java API based on the previously existing servlet API. SIP servlets are also a programming model where the servlets (the applications) are hosted by an infrastructure known as a servlet container (Figure 4).
Call control
Service capability server Service capability server Open Services Access
messages that rely on existing internet protocols like HTTP. Web services implementations need that the language-dependent API must be translated in WSDL and the application server where web-services are deployed must translate incoming SOAP messages to the underlying interfaces (e.g., Java, CORBA).
WAP WAP
Servers Servers
Gateway, Push‐‐ Gateway, Push proxy
Location server, MExE Location server, MExE server, SAT server
Interface class
SIP Servlet container Servlet Servlet SIP SIP
Figure 2. OSA architecture. A Parlay/OSA APIs provide a medium level of abstraction of the network capabilities. They provide an abstraction from different specific protocols [2, 7, 8].
SIP Servlet API Protocol unrelated container function
2.3 Interoperable Services Network Based on Web Services The web services architecture realizes an interoperable network of services focused on service reuse and it is suitable both to interact with third party applications and to export services by a network operator or a service provider. Service Creation Environment Web services toolkit
SOAP Application Server
Application Server
Servlet Servlet SIP SIP
Servlet Servlet SIP SIP
UA UA function function
Proxy Proxy function function
SIP SIP stack stack
Figure 4. SIP servlet and SIP servlet container. The SIP servlet API allows application to initiate and to answer SIP requests. Therefore it simply exposes SIP capabilities, both user agent and proxy capabilities, to the application while hiding a few protocol details handled transparently by the SIP Servlet container. SIP Servlet API is suitable for third party service development. It could be noted that third party service development is rather simple since they are seen as Java libraries [2, 12].
SOAP
2.5 Voice Extensible Markup Language (VoiceXML)
SOAP Call Server (Parlay--X gateway) (Parlay Terminal
Access Network 2NGN
Media Gateway
Packet--based Packet Network
Media Gateway
Access Network 2NGN
Figure 3. Web services in reference architecture. The web services can be used to export network services by exposing its WSDL (web services definition language) interfaces; these services communicate using SOAP (simple object access protocol), a protocol used to transport data between web services; service discovery and service registration are implemented accessing to the UDDI (universal discovery, description and integration) registry; XML is used as data format for SOAP
VoiceXML is a technology that allows a user to interact with a web server through voice-recognition technology, which exploits media server capabilities. VoiceXML can also be described as a phone markup language that can be used for voice applications that provide phone access to content and information, so it supports the network capability previously defined as generic user interaction (GUI). The VoiceXML interpreter can be seen as an enhanced feature of a media server, but its internal architecture is made of different parts (Figure 5): −
voice browser - software that renders the VoiceXML as a sequence of two dialogs between the system and the user.
−
web server - where the application pages reside. The application pages can be VoiceXML files, ASP, JSP, or PHP to dynamically create VoiceXML pages.
The user dials in to a particular phone number or SIP URI corresponding to the voice browser. The voice browser sends an HTTP request for the VoiceXML document to a server determined from the dialed number. Regular Web Server
Voice browser Voice XML interpreter
HTTP request
DTMF
Telephony
TTS
Audio
ASR
middleware XML voice Document
−
open source software - open source applications can play an important role in NGN systems. However operators of NGN services have to recognize this as a valid deployment model especially given the effective extensibility and tailor made adaptations that this approach offers.
The support of service selection, QoS, billing and security are four important areas of required attention and further investigation. An important step forward achieved with SIP application servers is the integration between communication and Internet technologies. This has major implications for enabling the creation of many new innovative services for NGN networks. Also, media servers are a core component of NGN architecture XML technologies, for example VoiceXML. Regarding service creation, development of NGN services is accessible in many ways. And, it is close to the web and IT developer community approach [2, 14].
4. AN ANALYTICAL FOUNDATION FOR SERVICE CREATION/DEVELOPMENT Figure 5. Basic Architecture for a Voice XML Service. VoiceXML makes it easy to rapidly create new applications and shields developers from low level programming issues. VoiceXML also executes logic: main components of a VoiceXML-based speech service include tags, forms and rules that define the content and a speech browser for interpreting and presenting audio content [2, 13, 14].
3. THE ASPECTS OF THE SERVICES PLATFORM DEPLOYING We highlight here some key aspects that have to be considered when deploying NGN service platforms: −
SIP tools - is a means to the communications needs of an NGN deployment. There are however, still several major issues that SIP must support before they may be considered mature enough for scalable, multi-service, managed communications networks. Functions in support of service selection, QoS, billing and security are four such areas of required attention.
−
dependency on telecommunication specialist expertise dependency on telecommunications specialist expertise for service development has to be certainly declined.
−
intelligence balance - location of intelligence is no longer restricted to the core-operating network. If compared to PSTN networks, NGNs are enriched by much more powerful terminals enabling the provision of new and innovative services. This means that massively used simple services with simple billing policies demand much less resources from the network/application providers than PSTN services.
−
APIs availability – a variety of APIs are emerging in NGN providing different levels of functional abstraction. It can be confusing to community when having to choose which API to use for a particular service. But, at the same time it means that the same service may be implemented in many different ways allowing service providers better chance to differentiate themselves from each other.
4.1 Open queuing network as a model for NGN SCE In an open network of queues service request enter the system from outside, follow a path through one or several service processing points, and then leave the system. The path that a service request follows may be fixed, or may vary in a probabilistic way. It seems obvious that the average rate at which service requests enter the service processing network must be the same as the average rate of departures from this network. The overall flow of service requests is therefore not affected by the state of the service processing network itself. The service processing network can be seen as a single service center with a complicated set of rules for serving requests (Figure 6, 7) [15, 16].
4.2 Hierarchical modeling, decomposition of the model into parallel subsystems In NGNs even simple service has complex structure. It consists from a lot of building blocks, which create hierarchical models with a lot of parallel subsystems. Thus, the NGN SCE is based on multiprocessing technology, parallel programming languages, and parallel programming environments. And, particular interest is in understanding and modeling the performance of parallel programs. The parallel programs have the fork-join structure and this type of parallel program paradigm arises in many NGN application areas (Figure 6) [17 ÷ 20]. The NGN SCE, in this case, can be modeled as follows. We assume that SCE multiprocessing computing system has K homogeneous servers, each with an infinite capacity queue. A service logic parallel program arrives to the multiprocessing computing environment with mean arrival rate λ. Upon the parallel program’s arrival, it splits into K independent tasks ti, 1 ≤ i ≤ K and task ti is assigned to the ith server. Each task’s service time is k-stage Erlang distributed with a mean service time of 1/μ. Each server uses the first-in-first-out (FIFO) scheduling discipline to service its tasks. When a task is finished and if there are any tasks belonging to the same parallel program still in service, the finished task will wait in the synchronization area. The parallel
program is considered complete and it departs from the computing system only when all its tasks have been completed. This type of work is closely related to fork-join queuing systems. The exact analysis is possible when the system is significantly simplified, for example, if it is assumed the job arrival process is Poisson with tasks having exponential service time distribution and the number of servers, K, is equal to two. For more than two servers, approximation and heuristic techniques are used to solve the problem [17, 20]. α1 α2
αR
λ11
λ21
λr 1
λ12
λ22
λr 2
λ1R
1
2
So, we take into consideration the system with K=2 queues to obtain the mean time in system of service request processing or response time. The response time of a task consists of two components: −
time spent in an M/M/1 queuing system, and
−
time spent in the system after service completion and before leaving the system. The latter is called synchronization delay; it is non-zero for the task that finishes its service first and zero for its sibling [21 ÷ 23].
The mean job response time equals the mean task response time because each job consists of exactly two tasks. Thus, the mean job response time in two-queue system is the sum of the mean response time in an M/M/1 queuing system:
λr
λ2R
The state of the system explained above can be presented by the number of tasks in each of the K queuing systems. This results in a K-dimensional Markov process whose analysis seems to be hard, if not impossible, for the general case.
RR
Figure 6. Distribution of the interarrival time of service logic parallel program. Let t be the random variable of the interarrival time of a parallel program to the SCE multiprocessing system and A*(s) is Laplace transform. Then, a class of interarrival distribution is the seriesparallel phase type which has the form [17]: R
rj
j =1
i =1
A ∗ (s ) = ∑α j ∏
λij s + λij
(1)
for 0 < α j < 1, ∑α j = 1 and λij > 0
μ 1
tasks
λ Split
2
(2)
and the mean synchronization delay S, that is,
T2 = T1 + S .
(3)
Using Little’s formulae, we can present synchronization delay as follows:
N (4) , 2λ where N is the average number of tasks which have completed and are waiting for their siblings to complete. Let k be any integer and define qk to be the probability that the number of tasks in the first queuing system exceeds the number of tasks in the second queuing system by k. By symmetry, we have qk = q-k, k ≥ 1 and thus S=
R
j =1
T1 = 1 / (μ − λ ),
μ
∞
Synchronization area
arrival
N = 2∑ kqk ,
μ
which implies
K service area
Figure 7. The fork-join model for service logic parallel program.
4.3 Approximate analysis of parallel queues model We take into consideration a system which consists of K identical parallel queuing systems as shown in Figure 7. Service requests arrive in a time-invariant, state-independent Poisson fashion with rate λ. Upon arrival, a service request forks into K tasks. Task k, k = 1, 2, …, K, is assigned to the kth queuing system which consists of a single server and an infinite capacity queue. The service times of tasks are independent and exponentially distributed with mean 1/μ. The server utilization is denoted by ρ = λ/μ. A job (e.g., service request) leaves the system as soon as all its tasks complete their service. In other words, tasks of the same job joined before departing the system [21, 22].
(5)
k =1
departure
S=
1
∞
∑ kq . λ k =1
k
(6)
The balance equation for the system can show that qk = q+k + pk,0, k = 0, 1, …, where pk,0 is the probability that there are k tasks in the first queue and 0 tasks in the second queue. This implies that ∞
qk = ∑ pi ,0
k = 0,1,...
(7)
i=k
Substituting (7) into (6) and simplifying yields to [21 ÷ 23]:
S=
1
i (i + 1) pi ,0 . 2 i =1 ∞
∑ λ
(8)
The generating function for pi,0 is given by [23]:
(1 − ρ )2 . 3
P(z ,0) =
(9) 1 − pz Using this to determine the first two moments of pi,0 and substituting into (8) and (3) yields
T2 =
12 − ρ T1 . 8
(10)
Mean response time T, normalized
In Figure 8, we present results of calculations of eq.2 and 10.
A lower bound, on the other hand, is obtained by neglecting queuing effects. In this case, the response time is the maximum of K exponentially distributed service times each with mean 1/μ. Thus, we have
103
102
The harmonistic series HK calculation results are presented in Figure 9, from which we can see that HK has form of the negative exponential distribution. This meets requirements of theorem in eq. 14.
T2
TK ≥ H K
T1 10
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
.
(16)
From (11) and (16) we can see that both bounds grow at the same rate HK. In other words, for large K the bounds are of order O(ln K). From this observation, we conclude that TK itself is growing at the same rate. Consequently, knowing the value of T2:
1 0
1
μ
1
Mean arrival rate λ, normalized
TK ≅ S K (ρ )T2 ,
K ≥ 2,
(17)
Figure 8. The first two moments of time in system or response time in two-queue system.
where SK(ρ) is a scaling factor which grows at rate O(ln K). We seek an approximation of the following form is
The approach to solve the K >2 queue problem is an approximate one. The essence of the approximation method stems from an interesting observation of bounds on TK. An upper bound is obtained by assuming independent queuing systems and, since the response times in M/M/1 queues are exponentially distributed with mean T1, is given by
(18) S K (ρ ) = α (ρ ) + β (ρ )H K , K ≥ 2. By substituting S2(ρ) = 1, which is true by definition, in the above equation we have that β(ρ) = (1 - α(ρ))/H2, and thus,
TK ≤ H K T1 .
(11)
where HK is the harmonic series [22, 24]. Then the following upper bound holds:
μ −λ
.
(12)
The theorem for the expected response time of the queuing system is as follows: ∞
∞
0
0
(
)
TK = ∫ G (t )dt ≤ ∫ 1 − F K (t ) dt .
F (t ) = 1 − e
− ( μ −λ )t
(14)
and then [21, 22]: ∞
(
(
H K = ∫ 1 − 1 − e −t 0
) )dt . k
(15)
4,5
HK, harmonic series
4 3,5 3
HK
2,5 2 1,5
K ≥ 2.
(19)
The behavior of α(ρ) as ρ approaches zero is as follows. In an almost empty system where limρ→0 TK = HK/μ, which from eq.17 suggests that limρ→0 SK (ρ) = HK/H2, K ≥ 2. Consequently, by taking the limit of (19), we get limρ→0 α (ρ) = 0. Substituting this into (19) and (17) leads to the following approximate expression for TK.
⎛H 4⎛ H TK ≅ ⎜⎜ K + ⎜⎜1 − K H 11 H2 ⎝ ⎝ 2
(13)
The theorem follows from the fact that for the system
1 − α (ρ ) HK , H2
where α(ρ) is to be determined.
⎞ ⎞ ⎟⎟ ρ ⎟T2 , ⎟ ⎠ ⎠
K ≥ 2.
(20)
The scaling factor in this expression exhibits a logarithmic behavior in K and a linear behavior in ρ, which we can see from Figure 10.
Mean response time T K, normalized
1
TK ≤ H K
S K (ρ ) = α (ρ ) +
103
102
T50 10
T5 1
1
0
0,5
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1
Mean arrival rate λ, normalized
0 0
10
20
30
40
Number of queueing systems, K
Figure 9. The harmonistic series HK.
50
Figure 10. The mean response or time in system TK for K identical parallel queuing systems.
4.4 The non-split architecture with a set of K independent M/EK/1 queuing systems The parallel queues model with fork/join configuration achieves parallelism on a task level, i.e., jobs are split into K statistically identical tasks that can be executed simultaneously on all K processors. The “price” for this increased parallelism is the synchronization delay that occurs when tasks wait for their siblings to finish execution. An alternate architecture for the K processors is to not split jobs but rather distribute all K tasks of a job randomly to one of the K processors. Since each job is assumed to consist of K independent exponentially distributed tasks, the queuing system formed by the non-splitting architecture consists of a set of K independent M/EK/1 queuing systems having a job arrival rate of λ/K jobs per unit time where each job consists of K exponential segments. It can be shown that the mean response time for this system is given by (Figure 11) [21 ÷ 24]:
Mean response time T K, normalized
K −1 ⎞ ⎛ TM / EK / 1 = ⎜ K − ρ ⎟T1 . 2 ⎝ ⎠
(21)
103
102
T50 10
T5 1 0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1
Mean arrival rate λ, normalized
Figure 11. The mean time in M/EK/1 system for K parallel servers.
5. CONCLUSIONS The Next Generation Networks (NGNs) put forward many advantages, such as support of many application-rich new services, along with more traditional telephony applications, agnostic access, and improved economics. They also give service providers greater control, security, and reliability while reducing their operating costs. Thus, service providers can quickly and cost-effectively build new revenue. Built on open, modular elements, standard protocols, and open interfaces, the NGN caters to the specific needs of all users - enterprises, remote offices, telecommuters, and small office/ home office (SOHO) customers. The new class of services it enables is more flexible, scalable, and cost-efficient than services that have been offered in the past. Furthermore, Next Generation Networks provide the means for enabling agile service creation capabilities that ensure better user experiences by integrating both new and legacy services across any access. However, even simple service has complex structure in NGNs, as they consist of many building blocks, which in turn necessitate hierarchical models with a wide array of parallel subsystems. As a result, it was very important to understand how proposed solutions in NGNs can enable flexible and easy service creation both for service providers and third-party application
developers. For this reason, our work places particular stress on understanding and modeling the performance of NGN structures, as well as on developing a design and engineering methodology (based on a mathematical foundation) that addresses the service creation aspects for which traditional approaches will not work in NGNs.
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