Many companies are offering products and services without a deep and precise customer perspective. Customer focus will be the core issue of big data analytics and customer experience management. IT Projects are to be based on open standards and viable reliable platforms processing both structured and unstructured data.
Re-marketing by Re-naming, learning by doing trial and error methodology was practiced by many big IT Companies in many clients. Customer satisfaction and investment protection suffered, confidence lowered.
Business ethics is the foundation of sustainable innovation. Companies like IBM SAP ORACLE ACCENTURE violated the very basic rules of service oriented open architectures, big data analytics incorporating both structured and unstructured data and focusing on customer satisfaction service level aggreements.
Real time reliable non-redundant non-dirty data is technically the basis for right decisions Second the proper data modeling ensuring the movement of minimum amount of just in time relevant clean data just in place is a necessity.
Third the simplicity of 3 level Architecture with Data Base Applications and User Interface, visulaization, miniaturizationlast but not least the customer acceptance of performance metrics.
Resource Management, the optimum use of time material and human resources organized on three pillars of finance sales and production business lines are the main carrying columns on the premise or IT Infrastructure database strategy Applications strategy and highly visulaized User interfaces. Integration of IT Strategy with Metadata and Business strategy is vital for long term survival.
The Residual value of systems is best describing the system behaviour At the end of the day all market players are trying to maximize their profit by letting the time resources and human resource work for them. How to implement the best practices in IT Industry especially in utility energy oil gas banks and telecommunications infrastructure by efficient data modeling and adapting or matching and synchronising data modeling, work flows and process flows.
I want to present my article on Telecomm Network Planning in 1999, which is still valid strategy as of today. We need to find out open standards, timeless or time independent simple big data solutions on linkedIn.
The pragmatic system integration solution from IT and Telecomm Perspective, efficient data modeling, data quality and big data analytics and mobility solutions will determine the future of IT and Telecom Industry:
New Universal Evolution of Telecommunications Network Planning:
Fixed-Mobile Convergence with Application and Service Divergence
SIEMENS PSE TN MNS SA
The unification of both packet- and circuit switched world leading to the convergence of fixed and mobile networks together with the database planning, necessitated the concomitant introduction of new applications and services in order to protect the previous telecommunications investments of operators or investors, who are urgently looking for the protection of their investments. This paper gives an overview of how to optimize the network planning problem by maximizing benefits while minimizing the risks of the investors-suppliers-and operators, under the light of latest developments in the area of network planning like the self-similarity of traffic, dynamic routing and topological constraints , summarizing the scope and the methodology of network planning and network management.
The next generation of access, switching, and transmission networks, as well as the end-user IT-equipment will be much more faster and intelligent, much more self-contained-and actively self-regulating, adapting themselves through their own iterative adjustment and decision making mechanisms to their own conditions or adaptive goal-settings. .
The New Network Planning and Network Management Teams has to act at the speed of light or at least at the speed of thought, in order to be able to keep pace with the accelerated rate of change of the market demand (All-IP, IPsec, DiffServ QoS),as the main driving force of the technological innovation.The new stored program controlled complex procedures with fully open interfaces will make the active networks soon a market reality leading to the convergence of the fixed-and mobile networks. The All-IP (Ipv4 replaced soon by Ipv6) convergence of different protocol stacks are to be achieved by the unification of circuit-and packet switched technologies through queueing theory and stochastic discrete event simulation.
The new unified network architectures enabling gigabits or terabits of throughput with underlying topological configurations and dynamic routing policies will in themselves be offered as a totally new revenue generating business, service or product. The world of ISPs or ASPs will be too complicated facing the question of survival against rapidly changing challenging market conditions. The Operators –Suppliers-and Investors of future telecommunications products or services will definitely need the network as an intelligent unique product in itself offered by the Network Planners or Consultants, because ISPs /ASPs are just about to loose their own control, or having to outsource , at least losing soon their degrees of freedom and/or competence in decision making to the network planners of the universally converged, but with services and applications totally diverged next generation networks.
Network Planning Problem means in the broadest sense how to meet the customer, business and infrastructure specific conflicting competitive objectives under efficient resource-and capacity utilization constraints over time.
The term „network planning“ has a broad scope of coverage, implying fundamentally both the strategical -and the operational network planning processes, which can be summarized as the radio network planning process tuned to the fixed-and mobile network planning processes , short-medium-and long-term resource allocation problem , capacity assignment and routing problem together with the integrated network data base planning,considering the network evolution, network compatibility and the integration of OEM-products into existing networks, network planning standardization, security and diffserv capability of a variety of middleware applications developed independently of underlying network structures, but as a feedback influence increasing the complexity of network traffic load, assuming a unified future network described by ist network database. The treatment of telecommunications network economics against the network availibility,network redundancy (availibility of redundant paths meeting overload and burstiness in peak hours ), network security and network database back-up and recovery concepts should be the main emphasis of an integrated network planning. Shortly defined, the integrated network planning process covers the orderly , time-dependent efficient deployment and management of computer-and data communications facilities. The new service product Network Planning is used in both the operational ( referring to existing telecommunication networks) and the strategical sense( identifying future technology trends driven by market forces ).The evolutionary network planning aims at the overall technological-economical-and financial integration of new network components features and technologies into existing networks.
For the development of network planning and integration tools, the well-known classical O.R. algorithms of advanced.dynamic integer.programming and graph theory, queueing theory and combinatorial optimization, branch and bound methods, penalty methods, and Discrete Event Simulation.are the most commonly used network planning and optimization algorithms..(1),(2),(3),.(14)
The Network planning problem has to be understood as an optimization problem, stated under the optimization criteria of cost effectiveness, high reliability- availibility-flexibility, extendability of networks and network components to minimize the overall network costs (reduce equipment) with a modular subnetworks structure. The general planning factors to be considered are mainly the technological factors, economical factors, financial factors, business factors, organizational factors,and environmental factors. Depending upon the level of planning detail required , for the definition of the network components, network modules (HW-and SW), various system and network architectures, network services, network topology ,different routing strategies specified according to the underlying network topology can be used. Finally based on the assumed traffic load sharing and traffic channelizing mode, quite different problem formulations of network planning problem can be presented.
The most important network features can be counted as the statistical multiplexing of loads, the existence of a large number of heterogenous subnetworks, their modular interconnection, and value-added services, the future growth prospects of existing networks The end –to –end delay, cell or packet loss, blocking probabilities and the calculation of the link budgets and protocol overheads which are to be taken into account together with the quality of service parameters. The Bandwidth availibility on demand is another bottleneck, that has to be considered in the formulation of network planning-and optimization problem.The economies of scale, finiteness of resources, standardisation and growth prospects of new technologies, modular extendability, hardware and software variety and emergence of new solutions should also considered as objective variables or constraints in the formulation of heterogenous networks` planning problem.
The evolution of networks over time is a key aspect of network planning and network optimization.The new network engineering requests may come due to a new product or technology or new customer (market-driven or technology-driven) expectations. The definition of new services, business priorities, reuse of existing infrastructure in migration are important to identify the network design strategy.
The optimized routing, colocation of network elements are the other factors influencing the cost-revenue-profit picture.
Aggregation and/or Decomposition into smaller Problems:
Methodologically,the network planning and optimization problem has to be divided into a number of smaller, easily manageable subproblems. One set of subproblems might be defined relying on the existing network structure, network topology, the priority rules for services in proportion to their shares in revenues, and the routing strategy. Another set of subproblems might be defined as end-user terminal equipment design (intelligence of end-user equipment), access technologies design, the assessment of switching technologies and finally the transmission systems.(5) The Markov Chains, queueing theory, general birth-death processes and renewal theory can be used to unify the totally different world of circuit switching and packet switching. The Erlang-k distribution and priority queueing models as M/G/m queues can be used efficiently to simulate the traffic load as Poisson distributed interarrival times and service times; defining their ratio as the utilization factor. (6),(8).(9)
Applications such as video and voice telephony are delay sensitive and will require differentiated services (QoS) with prioritization introduced into the queueing models.Analysis of the accuracy of bursty traffic models together with the response and recovery times and load sharing/load balancing in case of overload are an essential part of performance analysis of telecommunication networks Traffic models should match closely to real data in order to obtain reasonable tracking of the critical network performance bottlenecks..
Generically, one could optimize the cost-revenue-profit triple by minimizing the cost of expenditures for equipment and operations, and maximize revenues by introducing value-added intelligent services through intelligent networking (add a separate control layer to achieve service,network and end-user equipment independence) and doing all this over time as technology, user requirements and the economic factors change. The decomposition of network planning problem into smaller optimization problems has to be done for the sake of simplicity, consistence, uniqueness and solvability.
There are various types of classification approaches for different types of network planning, such as fixed and radio network planning, administrative planning, fundamental technical planning to develop plans for network management, switching and routing, addressing, signalling, operations, provisioning and maintenance. Engineering plans are detailed and immediate plans. Another type of planning can be accomplished on the basis of network components selection, like the number of base stations, local exchanges, toll exchanges, interexchange transmission, loop plant, signalling network and customer premises equipment, LAN, WAN,MAN, Routers, Bridges, Gateways etc. For GSM/GPRS/EDGE/UMTS network planning, the main classification is usually the radio network planning and fixed network planning besides of course the packet switching and the circuit switching. According to different services, another classification could be made as POTS, ISDN, SMDS or FR services, Packet, Video, Cellular Telephone, E-Mail, Remote Login, File Transfer, Image Transfer, Voice Connections, World Wide Web.
According to timing or time coverage of plans, the long-term plans(5-20 years), medium-term plans (2-5 years), and short-term plans (1-2 years) could be done using iterative dynamic programming or simulation scenario techniques by changing the planning assumptions. ( 7)
Performance Evaluation of High Speed Packet Switching Networks
The Packet-switching network was developed during the 1960s.The idea behind a packet-switching network was to create a network of dedicated leased lines whose sole function would be to transport digital data traffic. At the source, data would be divided into groups of bits called packets. An actual packet has two parts: Header and the actual information field or payload. The System Performance measures in a packet switched network are the interarrival times, service times, queue length, transit time, waiting time, and server idle time.(2)
The Header contains information about the originating point, packet`s destination, its priority and its error codes. The payload is the group of information bits that has to be transported over the network.algorithms running in the switching nodes read a packet`s destination address and forward the packet over the next successive link on its way to its destination.
The great advantage of statistical multiplexing in packet switching technology , that is sharing of transmission linesby the bursty data traffic between many users,lowered the cost of transmitting data over leased lines and combined the inherent bursty data traffic into aggregate flows that could be accommodated economically by long lasting leased-line connections. Today packet-switching is used overall in general user networks such as Internet as well as in specialized applications such as in establishing the connections in telephone networks through the Common Channel Signalling System 7.
With the introduction of ATM (Asynchronous Transfer Mode) technology, the share of packet-switching in the total world communications bandwith increased drastically. ATM combined broadband(high-speed) communications and services of voice- data-and video traffic in an integrated manner (ISDN). Some important advantages of ATM technology against STM(Synchronous Transfer Mode):
No rigidly structured hierarchy anymore needed
No time slot assignment (Mapping) problem anymore
No need for separate switches at each data rate by multirate switching as a combination of 64kbps switching building blocks.Bursty data traffic and services instead of fixed-demand services possible
During Network Planning the individual network components are to be planned and integrated into the existing GSM network and Internet. This covers the interconnecting of network equipment according to the network planning, configuration of system parameters for each network component, customer specific setup of the network management system tests with real applications and real traffic simulations.
The scope of overall end-to-end network planning problem should be divided into smaller subnetwork planning problems as the
-Radio Network Planning(RNP)
-Fixed network Planning ( PSTN,B- ISDN..)
-Mobile Network Planning (GSM/GPRS/EDGE/UMTS)
-Database Planning (Backup-and Recovery (14)
Planning a High Quality, High Performance Network Architecture
The right network architecture should be tailored depending upon the relative market choices of companies; even within a single market the architecture and technology are to be considered as moving targets, under which we should look for optimum network solutions(maximizing benefits while minimizing risks). Mobile operators are building networks only for their own use, without any real traffic simulations. The large variety of subnetworks and services necessitates a dedicated and specialized planning. The diversity of hardware and software complicates network management and planning. Therefore the choice of HW and SW and the rapid growth in networks makes it compulsory to install higher capacity systems accompanied by proper network planning.
Mathematical Programming for Network Planning
An objective function and associated set of constraints is called a mathematical program, consisting of decision variables and surplus or slack variables to convert the constraint inequalities into equations which are then to be solved by matrix operations of inversion and multiplication. The set of all constraints determines the feasible solution space. The Objective function might be cost, performance or reliability metrics. Network planning problem formulated as a mathematical programming, might have a single unique globally optimal solution or many locally optimal solutions. A locally optimal solution is only optimal for a limited portion of the feasible solution space. Sometimes heuristic algorithms, which use intuitive procedures to find out optimal solutions, might be useful to achieve global optimal solutions starting with local optimal solutions. The canonical problem formulation for network planning and queueing theory used to formulate the telecommunications network design and the solution technique , called simplex algorithm, can be found in Ref.(1).p.14-41.
The Network Optimization is indispensable because of shifts in subscriber-and application distribution and their traffic behaviour, changes in the subscriber mobility profile, subscriber growth, unbalanced market-driven regional network growth and limitations of frequency resources on air-interface.
Routing Problem and Discrete Event Simulation
ISPs or ASPs face a challenge in provisioning of network resources because of the rapid growth of bursty internet traffic and wide fluctuations of the traffic patterns. The dynamic routing should be used to prevent congestions and application performance as a valuable traffic engineering tool. The deployment of load-sensitive routing is however difficult due to overheads imposed by link-state update propagation, path selection and signalling. Through simulation experiments of one week or one-month duration, packet flows could be traced to differentiate between long-lived and short-lived flows to improve the performance of the links and to achieve the routing stability. The existing routing protocols OSPF, BGP, RIP etc. are optimizing in one way, leaving the longer paths underutilized.
A middle approach between physical experimentation and statistical analysis which is often used, is simulation technique. Since simulations are performed with software , it is easy to change or test the model assumptions, or change requests. The usual type of simulation of a network is called discrete event simulation. The”discrete events” are occurrences such as packets being transmitted , a buffer receiving a packet, or a call being switched. Simulations can be run to trace transient behaviour of networks,which occur over a very short period of time as a result of some event. The behaviour of networks over long time periods and the self-similarity of internet traffic, that means the steady-state behaviour of networks could be observed and simulated to examine various planning assumptions, whether they represent the reality.of traffic as it is. Discrete event simulation is stochastic in nature, because basic inputs like packet arrivals and call placements are to be generated randomly by using pseudorandom number generators.as software products.(3)
The self-similar traffic modelling is going to replace the poisson modelling of network traffic, because of long-range dependence in wide-area networks. The simplest models with long-range dependence are self-similar processes, which are characterized by hyperbolically –decaying autocorrelation functions. The long-range dependence of self-similar processes can be charactereized by a single parameter, called the Hurst parameter., which can be estimated using Whittle`s procedure (11)
Transient queueing analysis is essential for network planners to understand the temporal behaviour of their networks. The sojourn time performance of a network node has to be studied under realistic traffic environment. For that purpose , a network node has to be modeled as a finite quasi-birth-death process(instead of simplest M/M/1queueing model) with level dependent transitions, which are used to model a controlled or prioritized queueing system, where both the arrival and the service processes are to be regulated based on the instantenous buffer occupancy level, because the size of the buffer is always finite in reality.and the arriving cells are lost when the buffer is full. This approach allows the incorporation of more sophisticated and accurate traffic models than the previous 2/3 State Markov Models.of network traffic. The impact of input traffic characteristics and the effect of various simplifying assumptions like infinite buffer approximations, the effect of statistical multiplexing and the controlling effect of preemptive cell discarding (to assure the QoS) on the sojourn time behaviour of the system has to be studied further in depth.to explain the nodal congestion in networks planning. Realistic networks of today have large buffer size, but complex and bursty input traffic makes the infinite buffer assumption invalid. Buffering together with the statistical multiplexing can be used to increase the redundancy, reliability and availibility of networks to avoid congestions and to provide the QoS parameters in case of overload or highly bursty traffic input with long duration.(12, 13)
Trends in Network Planning:
For Transmission capacity services: TDM SONET/SDH WDM/DWDM-First step to the future –optical switching at 10-100 Terabits/sec.
For Access Networks services: TDM CATV,DSL,802.11,LMDS Wireless-Mobile-IP Convergence of fixed-and mob.IP,100Mbit Ethernet is the right next step,but fiber optics is the future transmission medium in telecommunications.
For Fixed Voice Networks services: CS VoIP using H.323 Replace with SIP and MGCP Session Initiation and Mediagateway Protocol
For Mobile Voice and Data Networks :.VoGSM SMS WAP GPRS EDGE UMTS or 802.11 IP-based new Value-Added Services, like IP-based Intelligent networking and new middleware applications development just by separating the control plane and data plane.
New IP-Services Best Effort DiffServQoS IPsec.for VPN Security WDM-Switching replacing ATM ; as a moving target between assured delay and assured bandwith use MPLS for traffic engineering, just putting the bandwidth where the traffic is or putting the traffic where bandwidth is.
Overall Trends and Conclusions: Fiber is the only future proof foundation for all network services; SIP and MGCP will be the key to voice/data convergence; mobile phone operators will become wireless Internet access providers and last but not least: Internet is able to provide QoS and Security without Layer2 VCs. With the realization of UMTS, the cellular networks of the future might well be dimensioned for the dominant type of traffic which is expected to be mobile data, rather than voice. This would lead to network consolidation of IP, ATM and Frame Relay.through network consolidating layers enabling cost savings in infrastructure.
FMC: Fixed-Mobile Convergence:
The heterogenous networks evolution and the mobility of Internet requires a unique OAM
Concept for common billing, operation and maintenance of diversified network services.
FMC can be realized by establishing a combined switching centre enabling the service and
support of both the mobile and the fixed customers through the same exchange. This might
be a hardware or software solution or a combination of both depending upon the existing
network infrastructure. Global access to personalized services are independent of access
methodology, underlying network and delivery method. It should be mentioned that the access
network is not so expensive to build out and to upgrade. Convergence will first happen in enterprise networks when voice is moved from traditional voice VPN (PABX networks) to data-VPN and thereafter into long distance IP-based intelligent VPNs. In the medium-term, the emerging technologies and standards will facilitate service and network convergence to an IP based network with fixed and mobile access increasing complexity with ever growing data throughput rates, bandwidth allocation and network configuration management problems. The optimization criteria for such a converged network can be counted as the end-to-end targeted quality of service levels, throughput rates, link capacity utilization, the minimized overall cost and delay levels with differentiated security allocations for different applications and the interoperability or compatibility of hardware and software units without posing any difficulties for combined implementation.
Modified overall network optimization problem formulation for a unified network planning process
The overall planning problem for such a converged network could be be formulated as the minimization of end-to-end total line costs (call set up, volume-and time dependant charging accounting for the cross-product of total connection time and volume of data transferred end-to-end packet-and circuit switched connections), subject to a given traffic load sharing model, given the chosen coding schemes for radio network coverage, given the specified node locations, inter-node and intra-node peak circuit- switched -and packet- switched traffic load sharing mechanisms, adjusted or matched by general birth-date stochastic queueing models delivering the required minimum link budgets and buffer sizes for smoothing out the burstiness of packet data traffic, over the decision variables of underlying network topology and routing policy, yielding the total channel or link capacities adapted by channel allocation choices (channelized, unchannelized, fractional, setting DE for FR or CLP for ATM or labeling for ATM LSR ) relying on the DiffServ or prioritized QoS-using static,virtual, dynamic routing mechanisms, without leaving any longer paths underutilized, if congestion in the shortest paths occurs), satisfying the allowed overall access-switching-transmission end-user equipment delays, reliability-redundancy-and availibility constraints, all being discrete(non-continuous) and iterated .over time covering the network planning period. The outputs of such a planning model will be measured or scaled in multiple functional HW-or SW units, bits -and seconds, which are to be converted into monetary units using a market-driven sales, qualified cost- and pricing strategy allowing for the investment protection of investors-suppliers-and operators triple defined as survival value chain, such that none of the market-players will be threatened in survival.
This overall problem formulation for the optimization of combined radio-and fixed network planning process could be extended for incorporating the involved database planning, database security, back-up and recovery processes.
1-Thomas G. Robertazzi:Planning Telecommunication Networks , 1999, IEEE Communications Society, Ch.1-2-3 pp 2-36
2-Susan L. Solomon Simulation of Waiting Line Systems, 1983 Prentice Hall, pp 11-16
3-Jerry Banks,John S.Carson II, Barry L.Nelson :Discrete-Event System Simulation, 1999 Prentice –Hall
4- J. Ioannidis, D. Duchamp and G.Q. Maguire Jr.: IP-based Protocols for Mobile Internetworking.In Proc. SIGCOMM 91, ACM, Zurich, Sept. 1991, pp. 235-245.
5- Pflug,G Stochastische Modelle in der Informatik, Stuttgart, 1986, p.85 and p.117
6-Daigle, J..N.: Queueing Theory for Telecommunications, Addison-Wesley, 1992 pp- 6-13, Ch.3-4
7-Gupta V.P., „What is Network Planning“ IEEE Communications Magazine, Vol.23, Nr.10, Oct. 1985, pp 10-16
8-Kleinrock. L. Queueing Systems Vol 1-2, New York , 1975
9-Kleinrock, L; Queueing Systems-Problems and Solutions-, New York, 1989
10- Heinanen, J.“Futureproof network planning strategies“ International Conference in London, 24-25 May, 2000, organized by Vision in Business.
11-Garrett.M and Willinger.W, : Analysis, Modelling and Generation of Self-Similar VBR Video Traffic, in: Proceedings of SIGCOMM`94 , pp. 269-280, 1994
12- Kobayashi, H., Ren Q.: Nonstationary behaviour of statistical multiplexing for multiple types of traffic, in : Proceedings of the 26 Annual Conference on Information Sciences and Systems, Princeton University Press, Princeton NJ, March 1992
13-Kant K., Introduction to Computer System Performance Evaluation, McGraw-Hill, New York, 1992.
14-Kumar V.,Hsu M. Recovery Mechanisms in Database Systems, Prentice-Hall, New jersey, 1998,
pp. 56-68, 259-291, 661-697