Enterprise distributed service platform – network ...

Pre-print:

I. Demydov, M. Klymash, N. Kryvinska, C. Strauss, “Enterprise Distributed Service Platform – Network Architecture and Topology Optimization”, Inderscience Publishers, International Journal of Space-Based and Situated Computing (IJSSC), Special Issue on “Middleware and Architectures for Seamless and Ubiquitous Space-based Computing in Distributed Systems”, Vol. 2, Iss. 1, 2012, pp. 23 - 30.

Enterprise distributed service platform – network architecture and topology optimisation Ivan Demydov* and Mychailo Klymash Telecommunications Department, Lviv Polytechnic National University, 12, S.Bandery Str., Lviv, 79013, Ukraine E-mail: [email protected] E-mail: [email protected] *Corresponding author

Natalia Kryvinska and Christine Strauss Department of e-Business, School of Business, Economics and Statistics, University of Vienna, Bruenner Str. 72, A – 1210 Vienna, Austria E-mail: [email protected] E-mail: [email protected] Abstract: Modern enterprises are global, associative e-business infrastructures involving employee, supplier, partner and customer networks. These dynamic, distributed organisations must have a flexible structure designed to move quickly in the face of global competitive pressures. Highly structured, vertically integrated, hierarchical organisations cannot respond to increasingly shorter periods of opportunity. Thus, we develop in this paper a method that allows considering the architecture of any kind of networked systems, which could be described by the formalised graphs and its adjacency matrix. This approach encompasses a categorisation and utilisation of the networked system topological properties. Namely, it involves an a-priory approximate determination of the basic network design performance features, e.g., information transfer capacity and the reliability assessment including configuration changes in running systems. Keywords: distributed service management platform; graph theory; optimisation; reliability; enterprise network. Reference to this paper should be made as follows: Demydov, I., Klymash, M., Kryvinska, N. and Strauss, C. (2012) ‘Enterprise distributed service platform – network architecture and topology optimisation’, Int. J. Space-Based and Situated Computing, Vol. 2, No. 1, pp.23–30. Biographical notes: Ivan Demydov is a Senior Lecturer at the Telecommunications Department, National University ‘Lviv Polytechnics’, Lviv, Ukraine. He received his Master and PhD in Telecommunication Systems and Networks from National University ‘Lviv Polytechnics’, Lviv, Ukraine. His research interests include optical networks, and distributed systems. Mychailo Klymash received his PhD in Telecommunications from the St. Petersburg State University of Telecommunications, named after Bonch-Brujevich, in 1993; and Habilitation in Telecommunication Systems and Networks from the Odessa National Academy of Telecommunications, named after O.S. Popov, in 2007. He is a Professor and the Head of the Telecommunications Department at the National University ‘Lviv Polytechnics’, Lviv, Ukraine since 2010. His research interests are transport networks, mobile networks and services, and distributed networked architectures modelling. Natalia Kryvinska is a Postdoctoral Fellow at the e-Business Research Group, Faculty of Business, Economics and Statistics, University of Vienna. She received her Diploma Engineer degree in Telecommunications from National University ‘Lviv Polytechnics’, Lviv, Ukraine, and PhD in Electrical Engineering from the Vienna University of Technology, Vienna, Austria. Her research interests include distributed systems management, service-oriented architectures in telecom domain, service delivery platforms, and e-services. Christine Strauss is an Associate Professor at the Faculty of Business, Economics and Statistics, University of Vienna. She holds a Masters in Business Informatics from the University of Vienna and Doctoral in Economics from the University of Zurich. She is the Head of the research group on Electronic Business at the University of Vienna. Her current research focuses on the field of electronic business, with a particular emphasis on e-services.

1

Introduction

The majority of enterprises now are global, networked infrastructures involving employees, suppliers, partners and customers. These dynamic, distributed organisations must have a flexible structure designed to move quickly in the face of global competitive pressures. Highly structured, vertically integrated, hierarchical organisations cannot respond to increasingly shorter periods of opportunity. To allow users inside of the distributed and interconnected enterprise to communicate and collaborate, companies have deployed a variety of communications tools (Figure 1). But, so far, companies have not realised their potential. To do so, it is critical that these communications tools be managed within a holistic strategy and integrated into the business processes of the organisation. Figure 1

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Management of communications technologies: The collaborative communications technologies such as voice, video and web conferencing have historically run on separate platforms and networks. And, therefore, instead of increasing productivity, legacy collaborative tools are cumbersome.

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Making collaboration and communications real-time: The rise of IP-based technologies led to dramatic improvements in user productivity, but a real-time person-to-person communications medium still struggles with constraints. This has changed with the near ubiquity of instant messaging and the increased adoption of IP telephony. To realise the full value, end users must be able to find other people in the extended enterprise and invoke services in real-time (Kerravala, 2007; Kryvinska et al., 2008; Kim et al., 2006; Kryvinska and van As, 2001).

2

Challenges and requirements to the effective management of distributed service platforms

Communication tools inside of distributed and interconnected enterprise to communicate and collaborate (see online version for colours)

Source: Kerravala (2007)

Besides, the competitive advantage is no longer about a single core capability; it is a collective knowledge of the competitors; it is the effectiveness of the competitors’ supply chain. The quality of the entire extended organisation and how well each component collaborates and communicates with others in real-time is now the basis for competitive advantage. Collaboration and communications are much more difficult today with the distributed, global nature of the enterprise. The intelligent communications can improve the overall manageability and effectiveness of real-time communications, which in turn can make a company more agile and responsive and enable global problem solving and new product deployment. Thus, having simply better communication and collaboration tools does not guarantee that corporate productivity will rise. There are many obstacles with the way organisations deploy communications tools. The most significant challenges include:

We study in this section some important challenges and requirements for the enterprise network-managing systems. The enterprise networks typically consist of network devices such as routers, bridges, switches, hubs and so on. These devices are interconnected to form the various topological configurations of enterprise networks. The management system has to be able to detect automatically all network devices in an enterprise network, and discover the topology of the backbone. Although the topologies of enterprise networks do not change frequently, they do change occasionally. When the topology changes, the management system must detect the change and modify necessary information for proper monitoring and control (Hong et al., 2001; Bloomers, 1996). Next open issue is as follows: whereas organisations introduce the next generation of online applications, they inevitably reach a common standoff. They discover that the tools, skills and processes they have used to manage applications for years suddenly seem completely ineffective. Next-generation web systems are inherently complex and difficult to manage. They are comprised of many interconnected, heterogeneous parts: web servers, Java and .NET applications, application servers, packaged applications such as Siebel, Oracle and SAP as well as back-end systems such as IBM MQ, CICS, Tuxedo, and various kinds of databases. Compounding this complexity are initiatives around web services and service-oriented architectures (SOAs), business process and integration technologies, and quality initiatives like ITIL and Six Sigma. This degree of complexity is becoming the

performance or availability of the applications that must complete these functions will translate into lower productivity, decreased customer satisfaction, and in many cases, lost revenue.

norm, and currently used tools cannot provide the transaction visibility or management power to optimise them (CA, 2008; Leng et al., 2008; Yohanan and HahnSteichen, 2006; Kumar, 1995).

2.1 Approaching services delivery model The amount of innovative service offerings aimed at maintaining or growing average revenue per user (ARPU) continues to increase. These offerings include converged services, televoting, micro-payments, and sophisticated customer self-service and provisioning, and so on. In the next-generation environments, operators are rolling out OSS/BSS applications and services that are driven by standards-based software solutions utilising commercial off the shelf (COTS) components. Services are software transactions flowing through IP-based, standards-based applications and infrastructure. Technologies like J2EE, .NET, SIP, JSLEE, SOA, and web services are increasingly being used to implement new rich services and customer-facing applications (Figure 2). Figure 2

Guaranteeing – NGN platforms and applications are carrier grade – with the shift towards software-based service delivery platforms (SDPs) and IP multimedia subsystem (IMS) as part of NGNs, operators and service providers need new tools to manage the complex software platforms within the network while IT professionals need to ensure that supporting OSS/BSS can scale to meet new real-time demands.

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Optimising OSS/BSS – OSS and BSS systems need to be ready for the real-time demands of next generation networks, but they must also be ready to handle other immediate IT challenges. The rapid roll-out of new billing models and provisioning requirements combined with continued growth of subscribers puts extra pressure on existing systems.

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Ensuring availability of information hubs and busses – increasingly, network operators are using integration platforms, SOA and web services to support growing transaction volumes and provide greater and deeper integration. These systems require proactive management capabilities that enable proactive detection, isolation, and elimination of transaction performance issues.

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Meeting service level agreements (SLAs) – commercial relationships and regulatory demands place very strict SLAs on network operators. Failure to meet SLAs results in fines and loss of commercial opportunities. Without detailed systems monitoring and alerting, SLAs may be breached before proactive action can be taken to fix the issue (CA, 2007a; Hong et al., 1997; Kang et al., 2006).

Network architecture for new generation of service delivery model

Source: CA (2007a)

2.2 Requirements to the performance and quality of services managing Traditional systems or network management solutions do not meet the needs of today’s telecommunications applications and platforms. Managing performance and quality of service becomes a significant challenge as telecom service providers move into the next generation, software-based era. Some important converged, requirements to the effective management of next generation telecommunications environments are classified in the Table 1. And, the principal performance management issues/requirements are: •

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Optimising user-support applications – the goal for customer inquiries, and support is ‘first contact resolution’ – be it at the call centre or in a self-service portal. Completing transactions efficiently requires gathering information in real-time from multiple sources to create a single view of the customer, and then delivering it without delay. Any degradation in the

Table 1

Requirements to the service management environment

Comprehensive visibility End-user experience

Process integration and best practices

Historical reporting and capacity planning

Real-time monitoring

Expert services

Web applications

In production 24 × 7

Enterprise portals

Low overhead

Professional services Education services

Application servers Integration middleware Service-oriented architectures (SOAs) Supporting systems Individual transactions

Event notification System management framework integration Customisable, intuitive dashboards

An example of application performance management system, one that provides comprehensive visibility into customer transactions across the entire application environment, is presented in Figure 3. Figure 3

An example of performance management system

respectively as: || c ||(k) = •k, and || c ||(k+1) = •k+1. A function D(•k), the differential function of topological changes, and correspondingly a reliability parameter R(•k, •k+1) (Klymash and Demydov, 2007; Klymash et al., 2008b) are expressed as follows [equations (1) and (2)]: D ( •k ) =

R ( •R ,

Source: CA (2007b)

3

Analysis and optimisation the performance parameters of distributed service platform

On the basis of the research performed in our previous work (Klymash and Demydov, 2007; Klymash et al., 2008a, 2008b, 2009), we have developed a method for the synthesis of logical-channel topological structure of networked systems (see Figure 4) in order to optimise workflow reliability parameters and core routing algorithms that are resistant to the overloads. This method was obtained from an ‘a priori’ consideration of the topological properties of networked structure. Figure 4

N −1 N −1 ⎛ i +1

∑∑ ⎜⎜ ∑ • i = 2 j = 2 ⎝ r = i −1

k +1

)

=

N −1 rkj

N −1 − •ijk +

D ( •k +1 ) − D ( •k ) N N −1

⎞ N −1 N −1 ⎟ •isk − •ijk (1) ⎟ s = j −1 ⎠ j +1

∑ (

)

⋅ max •kN −1 − •kN −1

(2)

During the synthesis process, the function D [equation (1)] provides the workflows distribution balancing into the networked structure, while the function R [equation (2)] is responsible for the workflow organisation with predefined reliability parameters, considering a physical network configuration (low levels of the network architectural platform). The performance of the numerical calculations by means of equations (1) and (2) can be fairly effective because of linearity of matrix processing algorithms. Figure 5

An algorithm of the logical-channel topology synthesis in the workflow management system (see online version for colours)

Algorithm of the distributed networked service platform analysis (see online version for colours) Graf

Network

Table

a1,1 A=

a1,2 . . a1,m

a2,1 .

. .

. . . .

. .

.

.

. .

.

an ,1

.

. . an ,m

Matrix

In Figure 5, we present an algorithm that depicts the process of the logical-channel topology synthesis in workflow management systems (Klymash et al., 2009). As an initiating event we can consider: an incipient design of network systems, emergency situations related to the gross physical interfering as well as continuous overloading/congestions caused by incorrect network management associated with unprofessional personnel actions. Let us define adjacency matrixes for the previous and current states of the information workflow in the network

Source: Klymash et al. (2009)

In order to provide: resistance to the overloads, operations simplification, and utilising current routing as well as workflow management algorithms, without modifying the L2–L3 networking protocols, exists a special option in the management software platforms. With this option, we can evaluate route-costs function for the certain defined metrics. It can be also estimated a priory specified workflow loading || L || ≅ β ⋅ •N–1 with a priory topological properties (Klymash and Demydov, 2007; Klymash et al., 2008b), calculated using adjacency matrix || • || of actual network area (where β – the coefficient of the structural proportionality).

Let us define the lower and upper borders of the critical loading for the networked structure. The existing transport network operating values are varying from 85% till 95%. This is a very small range of changes that has been recognised and accepted by almost of experts on network analysis. If to consider routing processes in the network as an a priori provided or more correct anticipated loading of the networked structure the probability of the information flow passing has non-linear pattern when reaches the specified limit (from the simulation results). Hence, it is logical that the routing strategies must change with changing of the total loading values of networked structure. In general, it should be distinguished three cases that involve their own strategies in the concept of routing schemes: 1

acceptable loading of networked structure

2

critical loading of networked structure

3

critically high loading of networked structures.

Here below, we describe in details the routing strategy algorithms for each of three cases, considering the results from (Klymash et al., 2009). Strategy 1 Loading of networked structure is low (ST1) •

Step 1 – Introducing of an adjacency matrix of the networked structure. It can reflect, in the simplest case, physical or channel associations in the transport structure, as well as throughput capacity of a network links. We compute here the estimated values of topological structural loading, and normalise the obtained field topology matrix (Klymash and Demydov, 2007; Klymash et al., 2008b) to the maximum.

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Step 2 – The argument for the routing process, which is setup by the coordinates (e.g., node numbers), is the virtual link element (VLE). It forms route destination points by its nodes. Its value also corresponds to the relative number of possible virtual routes in the obtained matrix.

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Step 3 – We divide the matrix on this step onto the VLE values gradually. As result, we get a ‘track’ of the desired route based onto certain elements of the matrix coordinates or, in other words, a subset of inter-node relations/connections. This ‘track’ or the subset of inter-node relations can provide further an opportunity to setup the optimal routes with minimal loading of connecting paths, which, in turn, can be achieved through the appropriate balancing of traffic in the networked system. The elements of the normalised matrix with pre-defined loading requirements, which after division will have the greatest possible values, can characterise the transport network structure capability to establish information workflows without considering an a priori specified virtual link. Since, the network loading is relatively low so, for the conventional no priority workflows, it is necessary to perform the

routing by the maximum matrix values of the ‘track’. Besides, the signalling high-priority workflows, which require a low delay, will be also routed with the next (upper) priority level. The signalling workflows and the peak traffic that do not require the low network delay or require high reliability should be routed over the ‘track’ matrix elements that are equal or at least lower than 1, a priori included with their topological configuration into the VLE network workflows. Strategy 2 Critical loading of networked structure (ST2) •

Steps 1 and 2 are similar.

•

Step 3 – Again, we divide the matrix on this step onto the VLE values gradually. By the analogy with the previous case, we get a ‘track’ of the desired route based onto the certain elements of the matrix coordinates.

After dividing, the ‘track’ matrix elements with values approximately equal to 1 will reflect the best route, obtained from the topological properties for the specified virtual link formed by end nodes. For more reliable workflows, several intermediate transport links (if possible) should be used with ‘less than 1’ values of the ‘track’ matrix elements. Strategy 3 The loading of networked structure is higher than the critical level (ST3) •

Steps 1 and 2, and dividing onto the Step 3 are the same as with previous strategy.

•

Step 3 – Routing must be performed only at the lowest, in particular cases at least according to the specified requirements, e.g., with equal to 1 values of the ‘track’ matrix elements.

So, summing up, we get a basic set of routes B using one of essential routing algorithms, for example, Dijkstra. Each routing strategy provides a reduction of possible route-set variants. Besides, the set of routes formed by all three strategies forms a basis set –B ⊆ ST1 ∪ ST2 ∪ ST3. The first strategy gives preference to the set ST1, the second to –ST3 ∪ ST2, and the third – ST3. Let us describe the kernel routing algorithms for three routing strategies identified by us. To do this, we need to determine the symbol-operator that characterises the strategies: STu ≡ {max, 0, min}, where u – is a number of each of the routing strategies (ST1, ST2, ST3). Thus, we get a general function that determines the routing mechanism providing a prioritisation to the routes when the basic set of possible routes is reduced: ⎛ ⎜ ∀i, j : ⎜ ⎜ ⎜ ⎝

⎧⎪ •ijN −1 ⎫⎪ ⎨ N −1 ⎬ ⎪⎩ •{EVL} ⎪⎭ i =1, ..., N ,

j =1, ..., N ij

⎞ ⎟ Δλ ij − 1⎟ → STu ⎟ max || λ || ⎟ ⎠

(3)

In the equation (3): Δλij – a new workflow to be setup, || λ || – a matrix of launched network workflows, and when

−1 substituted into equation (3) || λ || ⊇ Δλij.. Also, •{NEVL } – is

the VLE forming route destination points by its nodes. Figure 6

Simulation results for the well-known routing algorithms from reference sources and the proposed (5 lower legends) ones for various configurations of diverse networked systems

topological properties of the physical structure of the networked system (e.g., ‘grid [4 × 4]’). Figure 7

Optimal route ‘track’ {6, 7, 11, 10} for the relatively low loading, normalisation of •ijN −1 to the VLE = {2, 14} is reverse (to unify the algorithms structure) (see online version for colours)

Source: Klymash et al. (2008b) Figure 8 Source: Klymash et al. (2008a, 2008b), Ilyas and Mouftah (2003)

It is necessary to stress that the consideration of equation (3) and related to it calculations make sense only when exist: a correctly calculated basis set of possible routes B, and correctly defined requirements for the information workflows values that must be setup. However, it does not guarantee 100% the workflow establishment, only increases the chances for the success. The function equation (3) can be realised relatively easily. In this paper, we present the results of the modelling and simulation (Figure 6) based on algorithms that consider the function-criterion equation (3). These simulation results are given for the well-known routing algorithms from reference sources and the proposed ones (e.g., 5 lower legends) for various configurations of diverse networked system (Klymash et al., 2008a, 2008b; Ilyas and Mouftah, 2003). The experimental studies of the routing processes, performed on the data transmission networked topology, are conformed to the simulation results (curves A, B, Figure 6) for the structure class – ‘grid [4 ×4]’. The mean deviation of the experiment dependencies has to be less than 5%. The coefficient of the workflow proportionality has to be also considered when reducing nine rings of networked models into the three rings of real networked structure. The examples of the established routes, on the loading matrix background, are given in Figure 7, and Figure 8, respectively. The matrix is normalised to the optimal and non-optimal VLE values by the traffic balancing consistency criteria. It is also taken into consideration the

Non-optimal route ‘track’ {3, 2, 1, 5, 9, 13} for the relatively high loading, gradual normalisation of •ijN −1 to the VLE = {2, 14} is direct (see online version for colours)

Source: Klymash et al. (2008b)

Described algorithms and mechanisms constitute a synthesised adaptive foundation for the routing processes optimisation. They are built and implemented using known algorithmic solutions. These mechanisms allow reducing the set of solutions to the desired. With them the best workflow management option can be selected, for instance: with minimum possible delay; or maximal possible probability/reliability of the workflow establishment; with the network resistance to the overloads (Figure 6, curves A, B) and, consequently, network traffic alignment. To summarise, during our theoretical as well as experimental studies of the routing processes there was

synthesised a novel framework for the workflow control algorithms of networked structure, resistant to overloads. The framework considers the topological properties of networked structures. We have also analysed, developed, and verified appropriate simulation models. The result of our research is 20% to 30% increase of the system output as well as workflow/connection establishment probability.

4

Conclusions

The combination of mobile technology, IP networks and application innovation has created a world where time and distance no longer matter. The enterprise users get the opportunity to communicate with each other, as well as with partners and clients, at any point of time, over any device, anywhere they are with the right information. This enables organisations to not only improve existing business processes, but also create new, more streamlined processes that could not have existed with older technology. Many years ago, the thought of deploying IP communications was risky to many organisations. Today, not deploying it has an even bigger risk; companies that do not deploy will not have the necessary business agility to keep up with the competition. The unified communications by means of SDPs help transform companies by acting as the glue that joins end users, networks, communication technology and business applications. This creates the business agility that organisations require to achieve the next level of employee productivity and customer service. The enterprises that adopt SDPs find the following benefits:

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Faster decision-making: Enterprises are able to reach the right person wherever he or she is and retrieve the information required to make critical business decisions. The human latency that so often plagues organisations is no longer there.

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Better acceptance and use of collaborative applications: Historically, the adoption of many new collaborative applications has been slow. By tying the collaborative applications to business processes, users see an immediate workflow and productivity benefits. Over time, these tools are becoming mainstreams.

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Work-life balance improvements: Collaborative teams worldwide are able to interact as easily as if they were in the room next door. This minimises the amount of travel required for users to collaborate with one another. Additionally, users have the same access to information whether they’re in the office, at home or sitting on a beach.

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Improved customer satisfaction: By providing the right information to businesses over any medium, enterprises can respond to customers much more quickly and accurately (Kerravala, 2007).

Furthermore, businesses are reliant on IP for the majority of their communications. An efficient management of IP-based

networks is one of the most critical tasks assigned to IT and communications departments. However, there are still some considerable drivers behind the IP adoption, as the single protocol of choice by business is ease of management, robustness, and fact that it is the basis for the global communications network. As an argument – any network failure can mean a total communications failure; and business is vulnerable relying on a single technology. Selecting the right tools to manage IP networks is a key decision for IT managers if they are to ensure the network is available and secure, whilst delivering high performance and efficiency (Tarzey et al., 2007). These mentioned above challenges on the effective management of heterogeneous enterprise environment are the input of our further research work.

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