enerjİ -telekom- gaz- su Üretİm, İletİm ve daĞitim Şebekelerİnİn planlamasi

8/8/2019 ENERJ -TELEKOM- GAZ- SU RETM, LETM VE DAITIM EBEKELERNN PLANLAMASI

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iidir. Gerek yurt iinde gerekse uluslar aras piyasalarda SIEMENS,SHELL, LUCENT, HP, ORACLE, SAP gibi teknoloji reten firmalardaalrken edindiim bilgi ve tecrbelerden, nem makam ve mevkileriigal eden siyasetiler ve yneticiler hi faydalanmay dnmediler. llabirilerinin adam, ebeke iinde insan ebekelerinin, siyasi parti veMSAD, TSAD gibi menfaat ebekelerinin yesi olmak gerekiyordu.Kiisel bir tercih olarak, erken yalarda siyasi bir parti yesi olmaktaisabet grmedim. Yanlmm! Trkiye gibi lkelerde, daynn olmas,Demirel in zal n, Erdoan n yakn akrabas olmak, bilmem dahakimin ve kimlerin yeeni akrabas olmak, bilgi sahibi olmaktan ok dahanemli sayld iin ne kadar rpnsam da lkeme faydal olamadm.Gurbete kmak zorunda kaldm. Aslan kedilere bodurdular.

New Universal Evolution of TelecommunicationsNetwork Planning: Fixed-Mobile Convergence withApplication and Service Divergence

Abstract :The unification of both packet- and circuit switched worldleading to the convergence of fixed and mobile networkstogether with the database planning, necessitated theconcomitant introduction of new applications and services inorder to protect the previous telecommunications investmentsof operators or investors, who are urgently looking for theprotection of their investments. This paper gives an overviewof how to optimize the network planning problem by


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maximizing benefits while minimizing the risks of theinvestors-suppliers-and operators, under the light of latestdevelopments in the area of network planning like the self-

similarity of traffic, dynamic routing and topologicalconstraints , summarizing the scope and the methodology of network planning and network management. The next generation of access, switching, and transmissionnetworks, as well as the end-user IT-equipment will be muchmore faster and intelligent, much more self-contained-and

actively self-regulating, adapting themselves through their own iterative adjustment and decision making mechanisms totheir own conditions or adaptive goal-settings. .

The New Network Planning and Network Management Teamshas 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 acceleratedrate of change of the market demand (All-IP, IPsec, DiffServQoS),as the main driving force of the technologicalinnovation.The new stored program controlled complexprocedures with fully open interfaces will make the activenetworks soon a market reality leading to the convergence of the fixed-and mobile networks. The All-IP (Ipv4 replacedsoon by Ipv6) convergence of different protocol stacks are tobe achieved by the unification of circuit-and packet switchedtechnologies through queueing theory and stochastic discreteevent simulation.

The new unified network architectures enabling gigabits or terabits of throughput with underlying topologicalconfigurations and dynamic routing policies will inthemselves be offered as a totally new revenue generatingbusiness, service or product. The world of ISPs or ASPs will


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be too complicated facing the question of survival againstrapidly changing challenging market conditions. TheOperators Suppliers-and Investors of future

telecommunications products or services will definitely needthe network as an intelligent unique product in itself offeredby the Network Planners or Consultants, because ISPs /ASPsare just about to loose their own control, or having tooutsource , at least losing soon their degrees of freedom and/or competence in decision making to the network planners of theuniversally converged, but with services and applications

totally diverged next generation networks.

Introduction:

Network Planning Problem means in the broadest sense howto meet the customer, business and infrastructure specificconflicting competitive objectives under efficient resource-andcapacity utilization constraints over time.The term network planning has a broad scope of coverage,implying fundamentally both the strategical -and theoperational network planning processes, which can besummarized as the radio network planning process tuned tothe fixed-and mobile network planning processes , short-medium-and long-term resource allocation problem , capacityassignment 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


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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 aunified future network described by ist network database. Thetreatment of telecommunications network economics againstthe network availibility,network redundancy (availibility of redundant paths meeting overload and burstiness in peak hours), network security and network database back-up andrecovery concepts should be the main emphasis of an

integrated network planning. Shortly defined, the integratednetwork planning process covers the orderly , time-dependentefficient deployment and management of computer-and datacommunications facilities. The new service product Network Planning is used in both the operational ( referring to existingtelecommunication networks) and the strategicalsense( identifying future technology trends driven by marketforces ).The evolutionary network planning aims at the overalltechnological-economical-and financial integration of newnetwork components features and technologies into existingnetworks.For the development of network planning and integrationtools, the well-known classical O.R. algorithms of advanced.dynamic integer.programming and graph theory,queueing theory and combinatorial optimization, branch andbound methods, penalty methods, and Discrete EventSimulation.are the most commonly used network planningand optimization algorithms..(1),(2),(3),.(14)

The Network planning problem has to be understood as anoptimization problem, stated under the optimization criteria of cost effectiveness, high reliability- availibility-flexibility,extendability of networks and network components to


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minimize the overall network costs (reduce equipment) with amodular subnetworks structure. The general planning factorsto be considered are mainly the technological factors,

economical factors, financial factors, business factors,organizational factors,and environmental factors. Dependingupon 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 specifiedaccording to the underlying network topology can be used.

Finally based on the assumed traffic load sharing and trafficchannelizing mode, quite different problem formulations of network planning problem can be presented.

The most important network features can be counted as thestatistical multiplexing of loads, the existence of a largenumber of heterogenous subnetworks, their modular interconnection, and value-added services, the future growthprospects of existing networks The end to end delay, cell or packet loss, blocking probabilities and the calculation of thelink budgets and protocol overheads which are to be taken intoaccount together with the quality of service parameters. TheBandwidth availibility on demand is another bottleneck, thathas to be considered in the formulation of network planning-and optimization problem.The economies of scale, finitenessof resources, standardisation and growth prospects of newtechnologies, modular extendability, hardware and softwarevariety and emergence of new solutions should alsoconsidered as objective variables or constraints in theformulation of heterogenous networks` planning problem.


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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, businesspriorities, reuse of existing infrastructure in migration areimportant to identify the network design strategy.The optimized routing, colocation of network elements are theother factors influencing the cost-revenue-profit picture.

Aggregation and/or Decomposition into smaller Problems:Methodologically,the network planning and optimizationproblem has to be divided into a number of smaller, easilymanageable subproblems. One set of subproblems might bedefined 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 equipmentdesign (intelligence of end-user equipment), accesstechnologies design, the assessment of switching technologiesand finally the transmission systems.(5) The Markov Chains,queueing theory, general birth-death processes and renewaltheory 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 queuescan be used efficiently to simulate the traffic load as Poissondistributed interarrival times and service times; defining their ratio as the utilization factor. (6),(8).(9)

Applications such as video and voice telephony are delaysensitive and will require differentiated services (QoS) withprioritization introduced into the queueing models.Analysis of


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the accuracy of bursty traffic models together with theresponse and recovery times and load sharing/load balancingin case of overload are an essential part of performance

analysis of telecommunication networks Traffic modelsshould match closely to real data in order to obtain reasonabletracking of the critical network performance bottlenecks..

Generically, one could optimize the cost-revenue-profit tripleby minimizing the cost of expenditures for equipment andoperations, and maximize revenues by introducing value-

added intelligent services through intelligent networking (adda separate control layer to achieve service,network and end-user equipment independence) and doing all this over time astechnology, user requirements and the economic factorschange. The decomposition of network planning problem intosmaller 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 radionetwork planning, administrative planning, fundamentaltechnical planning to develop plans for network management,switching and routing, addressing, signalling, operations,provisioning and maintenance. Engineering plans are detailedand immediate plans. Another type of planning can beaccomplished on the basis of network components selection,like the number of base stations, local exchanges, tollexchanges, interexchange transmission, loop plant, signallingnetwork and customer premises equipment, LAN,WAN,MAN, Routers, Bridges, Gateways etc. For GSM/GPRS/EDGE/UMTS network planning, the mainclassification is usually the radio network planning and fixednetwork planning besides of course the packet switching and


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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-termplans(5-20 years), medium-term plans (2-5 years), and short-term plans (1-2 years) could be done using iterative dynamicprogramming or simulation scenario techniques by changingthe planning assumptions. ( 7)

Performance Evaluation of High Speed Packet SwitchingNetworks

The Packet-switching network was developed during the1960s.The idea behind a packet-switching network was tocreate a network of dedicated leased lines whose sole functionwould be to transport digital data traffic. At the source, datawould be divided into groups of bits called packets. An actualpacket has two parts: Header and the actual information fieldor payload. The System Performance measures in a packetswitched 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. Thepayload is the group of information bits that has to betransported over the network.algorithms running in theswitching nodes read a packet`s destination address andforward the packet over the next successive link on its way toits destination.


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The great advantage of statistical multiplexing in packet switching technology , that is sharing of transmission lines bythe bursty data traffic between many users,lowered the cost of

transmitting data over leased lines and combined the inherentbursty data traffic into aggregate flows that could beaccommodated economically by long lasting leased-lineconnections. Today packet-switching is used overall in generaluser networks such as Internet as well as in specializedapplications such as in establishing the connections intelephone 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 worldcommunications bandwith increased drastically. ATMcombined broadband(high-speed) communications andservices of voice- data-and video traffic in an integratedmanner (ISDN). Some important advantages of ATMtechnology against STM(Synchronous Transfer Mode):No rigidly structured hierarchy anymore neededNo time slot assignment (Mapping) problem anymoreNo need for separate switches at each data rate by multirateswitching as a combination of 64kbps switching buildingblocks.Bursty data traffic and services instead of fixed-demand services possible

During Network Planning the individual network componentsare to be planned and integrated into the existing GSMnetwork 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 trafficsimulations.


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The scope of overall end-to-end network planning problemshould 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 dependingupon the relative market choices of companies; even within asingle market the architecture and technology are to beconsidered as moving targets, under which we should look for optimum network solutions(maximizing benefits whileminimizing risks). Mobile operators are building networksonly for their own use, without any real traffic simulations.The large variety of subnetworks and services necessitates adedicated and specialized planning. The diversity of hardwareand software complicates network management and planning.Therefore the choice of HW and SW and the rapid growth innetworks makes it compulsory to install higher capacitysystems accompanied by proper network planning.

Mathematical Programming for Network Planning

An objective function and associated set of constraints iscalled a mathematical program, consisting of decisionvariables and surplus or slack variables to convert theconstraint inequalities into equations which are then to be


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solved by matrix operations of inversion and multiplication.The set of all constraints determines the feasible solutionspace. The Objective function might be cost, performance or

reliability metrics. Network planning problem formulated as amathematical programming, might have a single uniqueglobally optimal solution or many locally optimal solutions.A locally optimal solution is only optimal for a limited portionof the feasible solution space. Sometimes heuristicalgorithms, which use intuitive procedures to find outoptimal solutions, might be useful to achieve global optimal

solutions starting with local optimal solutions. The canonicalproblem formulation for network planning and queueingtheory 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 shiftsin subscriber-and application distribution and their trafficbehaviour, changes in the subscriber mobility profile,subscriber growth, unbalanced market-driven regionalnetwork 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 trafficand wide fluctuations of the traffic patterns. The dynamicrouting should be used to prevent congestions and applicationperformance as a valuable traffic engineering tool. Thedeployment of load-sensitive routing is however difficult dueto overheads imposed by link-state update propagation, pathselection and signalling. Through simulation experiments of


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one week or one-month duration, packet flows could be tracedto differentiate between long-lived and short-lived flows toimprove 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 pathsunderutilized.

A middle approach between physical experimentation andstatistical analysis which is often used, is simulationtechnique. Since simulations are performed with software , it

is easy to change or test the model assumptions, or changerequests. The usual type of simulation of a network is calleddiscrete event simulation. Thediscrete events areoccurrences such as packets being transmitted , a buffer receiving a packet, or a call being switched. Simulations canbe run to trace transient behaviour of networks,which occur over a very short period of time as a result of some event. Thebehaviour of networks over long time periods and the self-similarity of internet traffic, that means the steady-statebehaviour of networks could be observed and simulated toexamine various planning assumptions, whether they representthe reality.of traffic as it is. Discrete event simulation isstochastic in nature, because basic inputs like packet arrivalsand call placements are to be generated randomly by usingpseudorandom number generators.as software products.(3)

The self-similar traffic modelling is going to replace thepoisson modelling of network traffic, because of long-rangedependence in wide-area networks. The simplest models withlong-range dependence are self-similar processes, which arecharacterized by hyperbolically decaying autocorrelationfunctions. The long-range dependence of self-similar processes can be charactereized by a single parameter, called


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the Hurst parameter., which can be estimated using Whittle`sprocedure (11)

Transient queueing analysis is essential for network plannersto understand the temporal behaviour of their networks. Thesojourn time performance of a network node has to be studiedunder realistic traffic environment. For that purpose , anetwork node has to be modeled as a finite quasi-birth-deathprocess(instead of simplest M/M/1queueing model) with leveldependent transitions, which are used to model a controlled or

prioritized queueing system, where both the arrival and theservice processes are to be regulated based on the instantenousbuffer occupancy level, because the size of the buffer isalways finite in reality.and the arriving cells are lost when thebuffer is full. This approach allows the incorporation of moresophisticated and accurate traffic models than the previous 2/3State Markov Models.of network traffic. The impact of inputtraffic characteristics and the effect of various simplifyingassumptions like infinite buffer approximations, the effect of statistical multiplexing and the controlling effect of preemptive cell discarding (to assure the QoS) on the sojourntime behaviour of the system has to be studied further indepth.to explain the nodal congestion in networks planning.Realistic networks of today have large buffer size, butcomplex and bursty input traffic makes the infinite buffer assumption invalid. Buffering together with the statisticalmultiplexing can be used to increase the redundancy,reliability and availibility of networks to avoid congestionsand to provide the QoS parameters in case of overload or highly bursty traffic input with long duration.(12, 13)

Trends in Network Planning:


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For Transmission capacity services: TDM SONET/SDHWDM/DWDM-First step to the future optical switching at10-100 Terabits/sec.

For Access Networks services: TDMCATV,DSL,802.11,LMDS Wireless-Mobile-IP Convergenceof fixed-and mob.IP,100Mbit Ethernet is the right nextstep,but fiber optics is the future transmission medium intelecommunications.For Fixed Voice Networks services: CS VoIP using H.323Replace with SIP and MGCP Session Initiation and

Mediagateway ProtocolFor Mobile Voice and Data Networks :.VoGSM SMS WAPGPRS EDGE UMTS or 802.11 IP-based new Value-AddedServices, like IP-based Intelligent networking and newmiddleware applications development just by separating thecontrol plane and data plane.New IP-Services Best Effort DiffServQoS IPsec.for VPNSecurity WDM-Switching replacing ATM ; as a moving targetbetween assured delay and assured bandwith use MPLS for traffic engineering, just putting the bandwidth where thetraffic 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 bethe key to voice/data convergence; mobile phone operatorswill become wireless Internet access providers and last but notleast: Internet is able to provide QoS and Security withoutLayer2 VCs. With the realization of UMTS, the cellular networks of the future might well be dimensioned for thedominant 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 consolidatinglayers enabling cost savings in infrastructure.


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FMC: Fixed-Mobile Convergence:

The heterogenous networks evolution and the mobility of

Internet requires a unique OAMConcept for common billing, operation and maintenance of diversified network services.FMC can be realized by establishing a combined switchingcentre enabling the service andsupport of both the mobile and the fixed customers through

the same exchange. This might

be a hardware or software solution or a combination of bothdepending upon the existingnetwork infrastructure. Global access to personalized servicesare independent of accessmethodology, underlying network and delivery method. Itshould be mentioned that the accessnetwork is not so expensive to build out and to upgrade.Convergence will first happen in enterprise networks whenvoice is moved from traditional voice VPN (PABX networks)to data-VPN and thereafter into long distance IP-basedintelligent VPNs. In the medium-term, the emergingtechnologies and standards will facilitate service and network convergence to an IP based network with fixed and mobileaccess increasing complexity with ever growing datathroughput rates, bandwidth allocation and network configuration management problems. The optimization criteriafor 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 delaylevels with differentiated security allocations for differentapplications and the interoperability or compatibility of hardware and software units without posing any difficultiesfor combined implementation.


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Conclusion:

Modified overall network optimization problem formulationfor 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 totalline costs (call set up, volume-and time dependant charging

accounting for the cross-product of total connection time andvolume of data transferred end-to-end packet-and circuitswitched connections), subject to a given traffic load sharingmodel, given the chosen coding schemes for radio network coverage, given the specified node locations, inter-node andintra-node peak circuitswitched -and packetswitched trafficload sharing mechanisms, adjusted or matched by generalbirth-date stochastic queueing models delivering the requiredminimum link budgets and buffer sizes for smoothing out theburstiness of packet data traffic, over the decision variables of underlying network topology and routing policy, yielding thetotal channel or link capacities adapted by channel allocationchoices (channelized, unchannelized, fractional, setting DE for FR or CLP for ATM or labeling for ATM LSR ) relying on theDiffServ or prioritized QoS-using static,virtual, dynamicrouting mechanisms, without leaving any longer pathsunderutilized, if congestion in the shortest paths occurs),satisfying the allowed overall access-switching-transmissionend-user equipment delays, reliability-redundancy-andavailibility constraints, all being discrete(non-continuous) anditerated .over time covering the network planning period. Theoutputs of such a planning model will be measured or scaledin multiple functional HW-or SW units, bits -and seconds,


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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 themarket-players will be threatened in survival.This overall problem formulation for the optimization of combined radio-and fixed network planning process could beextended for incorporating the involved database planning,database security, back-up and recovery processes.

References:

1-Thomas G. Robertazzi:Planning TelecommunicationNetworks , 1999, IEEE Communications Society, Ch.1-2-3pp 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 Hallpp 92-96

4- J. Ioannidis, D. Duchamp and G.Q. Maguire Jr.: IP-basedProtocols 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


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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 IEEECommunications Magazine, Vol.23, Nr.10, Oct. 1985, pp 10-16

8-Kleinrock. L. Queueing Systems Vol 1-2, New York , 19759-Kleinrock, L; Queueing Systems-Problems and Solutions-,

New York, 198910- Heinanen, J.Futureproof network planning strategiesInternational Conference in London, 24-25 May, 2000,organized by Vision in Business.

11-Garrett.M and Willinger.W, : Analysis, Modelling andGeneration 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 th Annual Conference on InformationSciences and Systems, Princeton University Press, PrincetonNJ, March 1992

13-Kant K., Introduction to Computer System PerformanceEvaluation, McGraw-Hill, New York, 1992.

14-Kumar V.,Hsu M. Recovery Mechanisms in DatabaseSystems, Prentice-Hall, New jersey, 1998,pp. 56-68, 259-291, 661-697

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