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Artykuły w czasopismach na temat „Network planning”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 9 marca 2023

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1

Bollapragada, Ramesh, Thomas B. Morawski, Luz E. Pinzon, Steven H. Richman i Raymond Sackett. "Network Planning of Broadband Wireless Networks". Interfaces 37, nr 2 (kwiecień 2007): 143–62. http://dx.doi.org/10.1287/inte.1060.0284.

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PELLEGRINI, Lilla, Monica LEBA i Alexandru IOVANOVICI. "CHARACTERIZATION OF URBAN TRANSPORTATION NETWORKS USING NETWORK MOTIFS". Acta Electrotechnica et Informatica 20, nr 4 (21.01.2020): 3–9. http://dx.doi.org/10.15546/aeei-2020-0019.

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We use tools and techniques specific to the field of complex networks analysis for the identification and extraction of key parameters which define ”good” patterns and practices for designing public transportation networks. Using network motifs we analyze a set of 18 cities using public data sets regarding the topology of network and discuss each of the identified motifs using the concepts and tools of urban planning.

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3

Koutitas, George. "Green Network Planning of Single Frequency Networks". IEEE Transactions on Broadcasting 56, nr 4 (grudzień 2010): 541–50. http://dx.doi.org/10.1109/tbc.2010.2056252.

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4

Wombell, S. "Network capacity planning". IEE Review 45, nr 2 (1.03.1999): 79–80. http://dx.doi.org/10.1049/ir:19990211.

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5

Prof. Y. B. Gurav, Prof Y. B. Gurav, i Manjiri Deshmukh. "Query Planning of Continuous Aggregation Queries Over Network". Indian Journal of Applied Research 3, nr 5 (1.10.2011): 140–43. http://dx.doi.org/10.15373/2249555x/may2013/42.

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6

Lin, Shih-Chun, Pu Wang, Ian F. Akyildiz i Min Luo. "Towards Optimal Network Planning for Software-Defined Networks". IEEE Transactions on Mobile Computing 17, nr 12 (1.12.2018): 2953–67. http://dx.doi.org/10.1109/tmc.2018.2815691.

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7

Falconer, Warren E. "The Third International Network Planning Symposium, Networks '86". Computer Networks and ISDN Systems 12, nr 2 (styczeń 1986): 126–27. http://dx.doi.org/10.1016/0169-7552(86)90021-8.

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8

Chen, Chi-Yuan, Fan-Hsun Tseng, Chin-Feng Lai i Han-Chieh Chao. "Network planning for mobile multi-hop relay networks". Wireless Communications and Mobile Computing 15, nr 7 (10.07.2013): 1142–54. http://dx.doi.org/10.1002/wcm.2396.

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9

Quach, Hong-Nam, Hyeonjun Jo, Sungwoong Yeom i Kyungbaek Kim. "Link Stability aware Reinforcement Learning based Network Path Planning". Korean Institute of Smart Media 11, nr 5 (30.06.2022): 82–90. http://dx.doi.org/10.30693/smj.2022.11.5.82.

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Along with the growing popularity of 5G technology, providing flexible and personalized network services suitable for requirements of customers has also become a lucrative venture and business key for network service providers. Therefore, dynamic network provisioning is needed to help network service providers. Moreover, increasing user demand for network services meets specific requirements of users, including location, usage duration, and QoS. In this paper, a routing algorithm, which makes routing decisions using Reinforcement Learning (RL) based on the information about link stability, is proposed and called Link Stability aware Reinforcement Learning (LSRL) routing. To evaluate this algorithm, several mininet-based experiments with various network settings were conducted. As a result, it was observed that the proposed method accepts more requests through the evaluation than the past link annotated shorted path algorithm and it was demonstrated that the proposed approach is an appealing solution for dynamic network provisioning routing.

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10

Penchev, Georgi. "Planning and Implementing Change in Cyber Security Network Organisations". Information & Security: An International Journal 50 (2021): 89–101. http://dx.doi.org/10.11610/isij.5008.

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11

Shrestha, Chandra, H. Kammeier i Jayant Routray. "District road-network planning". Third World Planning Review 23, nr 4 (listopad 2001): 347–66. http://dx.doi.org/10.3828/twpr.23.4.m761827u336v3631.

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12

Umar, Amjad, i Ramesh Subbaraman. "Ontology-Based Network Planning". International Journal of Business Data Communications and Networking 4, nr 3 (lipiec 2008): 31–51. http://dx.doi.org/10.4018/jbdcn.2008070102.

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13

Niden, Howard. "FRAMEWORK FOR NETWORK PLANNING". Information Systems Management 9, nr 4 (styczeń 1992): 16–21. http://dx.doi.org/10.1080/10580539208906894.

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14

Gupta, V. "What is network planning?" IEEE Communications Magazine 23, nr 10 (październik 1985): 10–16. http://dx.doi.org/10.1109/mcom.1985.1092435.

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15

Velasco, Luis, Alberto Castro, Daniel King, Ori Gerstel, Ramon Casellas i Victor Lopez. "In-operation network planning". IEEE Communications Magazine 52, nr 1 (styczeń 2014): 52–60. http://dx.doi.org/10.1109/mcom.2014.6710064.

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16

Gamst, A., E. G. Zinn, R. Beck i R. Simon. "Cellular Radio Network Planning". IEEE Aerospace and Electronic Systems Magazine 1, nr 2 (luty 1986): 8–11. http://dx.doi.org/10.1109/maes.1986.5005038.

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17

Marín, Angel, i Esteve Codina. "Network design: taxi planning". Annals of Operations Research 157, nr 1 (7.07.2007): 135–51. http://dx.doi.org/10.1007/s10479-007-0194-0.

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18

Ross-Pinnock, David, Glen Mullineux i Patrick S. Keogh. "Temperature Sensor Position Planning". Journal of Integrated Design and Process Science 24, nr 3-4 (11.04.2022): 65–94. http://dx.doi.org/10.3233/jid-210025.

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One of the challenges in large volume metrology is that it is often difficult or impossible to control the ambient conditions in which the object is to be measured. Dimensional measurement results vary with those conditions and it becomes necessary to apply some form of compensation. Thermal compensation of dimensional measurement is primarily reliant on the ability to properly measure temperature across the volume, which can differ by several degrees, but conventionally a uniform scaling has been applied. This paper focuses upon temperature sensor network planning improvement to facilitate thermal compensation. Beyond assembly environments, data from sensor networks are increasingly used to make decisions, but appropriate design and testing of such networks can be limited. As the demand for production digital twins increase, appropriate methods to quantify and optimise uncertainty to improve confidence will be invaluable. A virtual test bed has been created for the design, test, and optimisation of temperature sensor networks supported by physical simulation. Sensor networks have been used to take virtual measurements from a known temperature distribution and used to reconstruct the temperature distribution. Random search optimisation on a subset of the sensor network was carried out to determine some initial rules for sensor network design. The positioning of the sensors within the measurement volume and the method of reconstructing the temperature field was found to be more important than the capability of the individual sensors. Two means of interpolating the ambient field have been investigated: polynomial fitting and kriging. Temperature sensor networks appeared more sensitive to changes at the spatial boundary and these positions seem to be most critical for accurate reconstruction. In the case of the barrel section assembly it was found that asymmetric sensor heights produced better results, for example. A polynomial interpolation model using a 16-sensor network with 0.1 °C (confidence interval, k = 2) uncertainty sensors could produce a consistent temperature reconstruction error of ~0.04 °C RMS, corresponding to a thermal expansion error of ~1.5 μm in aluminium over a 1.6 m-tall structure.

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19

Bermingham, Philip, Tony Hernandez i Ian Clarke. "Network Planning and Retail Store Segmentation". International Journal of Applied Geospatial Research 4, nr 1 (styczeń 2013): 67–79. http://dx.doi.org/10.4018/jagr.2013010105.

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Store segmentation aims to divide a network of stores into meaningful groups, typically based on a combination of operational, site and trading environment characteristics. It is an increasingly important component within network planning activities of major retail chains due to the significant capital investment that is physically grounded in their large store networks. The paper outlines findings from case study research that has focused on developing spatial decision support tools that enable decision makers to explore, construct and visualize store segments. An integrated spatial statistical approach to store segmentation is detailed and associated benefits and shortfalls discussed. The paper highlights the potential to develop customised geospatial tools to support network planning decision making activities. It is argued that geospatial decision support tools need to be designed to accommodate the varying GIS skill-levels of potential end-users and that fundamentally more emphasis needs to be placed on creating tools that can be used by decision-makers as opposed to analysts.

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20

Pan, Kan, Anrui Li, Zheng Yang, Yongjie Nie, Zhenwei Geng, Junjie Wen, Wentao Liu, Shichen Wang, Hui Chen i Zuyuan Huang. "Research on Green Energy Internet Planning Model". E3S Web of Conferences 293 (2021): 03031. http://dx.doi.org/10.1051/e3sconf/202129303031.

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This paper intends to take power system planning as the main module, while considering the requirements and constraints of natural gas network and transportation network construction and use the energy hub model to analyse the energy transmission and transformation relationship between different networks, to realize the power system, natural gas network, and transportation. Integrated energy system planning for the network. To verify the effectiveness of the proposed PMIES planning method, an improved Garver test system is used for simulation. The system includes a 7-node natural gas network system and a 6-node electric test system. We optimized and analysed the simulated system for model research.

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21

Herz, R. K., i A. T. Lipkow. "Strategic water network rehabilitation planning". Water Supply 3, nr 1-2 (1.03.2003): 35–42. http://dx.doi.org/10.2166/ws.2003.0083.

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This paper presents the approach taken and the tools developed and advanced within the European research project CARE-W (Computer Aided REhabilitation of Water networks) for strategic rehabilitation investment planning as a complement to short-term performance monitoring and annual rehabilitation (rehab) budget allocation planning. In a first step, future rehab needs are quantified with a cohort-survival model from the present stock of assets taking into account the specific service lives of its components. Utility managers may choose in the short and medium range from many rehab options: doing more or less, sooner or later, on particular network components and with specific rehab technologies at lower or higher cost. So, in a second step, alternative medium-term rehab programs are specified and tested for their effects. The annual costs and benefits of these alternative rehab programs are forecast with the cohort-survival model beyond the rehab program period to capture the long-term effects of rehabilitating these long-lived assets. Advantages and disadvantages of alternative rehab programs are systematically compared to find out which one is most appropriate under local constraints. However, whereas the survival of network components can be forecast over very long periods with sufficient accuracy, many other characteristics of the water supply system that must be considered for finding the best network rehab strategy may take unforeseeable paths into the far future. Therefore, a scenario writing tool was developed allowing consistent scenarios for particular water utilities to be created and to test whether the alternative rehab programs are robust enough to meet all eventualities of the future. This approach is illustrated by a case study from East Germany.

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22

Hurley, Stephen, i Leigh Hodge. "Compromise in CDMA Network Planning". Communications and Network 02, nr 03 (2010): 152–61. http://dx.doi.org/10.4236/cn.2010.23023.

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23

Ewing, Reid. "Sketch Planning a Street Network". Transportation Research Record: Journal of the Transportation Research Board 1722, nr 1 (styczeń 2000): 75–79. http://dx.doi.org/10.3141/1722-09.

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A sketch planning methodology is used to determine the optimal spacing of through streets as a function of residential density. Unlike earlier efforts to relate street spacing to residential density, this methodology accounts for changes in mode share, trip length, time of travel, and intersection capacity as residential density increases. The methodology is transferable to other areas by modifying assumptions relating to travel demand and street network characteristics. Planners can derive their own spacing requirements for purposes of community master planning, site-plan review and approval, access management, or zoning and subdivision regulation.

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24

Kalafatas, Georgios, i Srinivas peeta. "NETWORK DESIGN FOR EVACUATION PLANNING". IFAC Proceedings Volumes 39, nr 12 (styczeń 2006): 199–203. http://dx.doi.org/10.3182/20060829-3-nl-2908.00035.

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25

Soumplis, Polyzois, Konstantinos Christodoulopoulos, Marco Quagliotti, Annachiara Pagano i Emmanouel Varvarigos. "Network Planning With Actual Margins". Journal of Lightwave Technology 35, nr 23 (1.12.2017): 5105–20. http://dx.doi.org/10.1109/jlt.2017.2743461.

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26

Usbeck, Kyle, Jeffrey Cleveland i William Regli. "Network-centric IED detection planning". International Journal of Intelligent Defence Support Systems 5, nr 1 (2012): 44. http://dx.doi.org/10.1504/ijidss.2012.053665.

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27

Pierangeli, Laurel Pflecki, i Gale A. Spencer. "Social Network Discharge Planning Tool". Home Healthcare Nurse: The Journal for the Home Care and Hospice Professional 5, nr 6 (listopad 1987): 38–40. http://dx.doi.org/10.1097/00004045-198711000-00008.

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28

Booher, David E., i Judith E. Innes. "Network Power in Collaborative Planning". Journal of Planning Education and Research 21, nr 3 (marzec 2002): 221–36. http://dx.doi.org/10.1177/0739456x0202100301.

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29

Kleiner, Y., B. J. Adams i J. S. Rogers. "Water Distribution Network Renewal Planning". Journal of Computing in Civil Engineering 15, nr 1 (styczeń 2001): 15–26. http://dx.doi.org/10.1061/(asce)0887-3801(2001)15:1(15).

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30

Davies, Martin, i Ian Clarke. "A Framework for Network Planning". International Journal of Retail & Distribution Management 22, nr 6 (wrzesień 1994): 6–10. http://dx.doi.org/10.1108/09590559410070259.

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31

Desmond, C. L., i R. S. Templeton. "Planning a business communications network". IEEE Network 3, nr 6 (listopad 1989): 8–10. http://dx.doi.org/10.1109/65.39130.

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32

Tang, Xiaoping, i D. F. Wong. "Network flow based buffer planning". Integration 30, nr 2 (październik 2001): 143–55. http://dx.doi.org/10.1016/s0167-9260(01)00015-3.

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33

Sen, Suvrajeet, Robert D. Doverspike i Steve Cosares. "Network planning with random demand". Telecommunication Systems 3, nr 1 (luty 1994): 11–30. http://dx.doi.org/10.1007/bf02110042.

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34

Hwang, I. M. "Festival and Travel Planning Network". International Journal of Tourism & Hospitality Reviews 2, nr 1 (1.11.2015): 67–69. http://dx.doi.org/10.18510/ijthr.2015.213.

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Travelers who interested in often use the internet (World Wide Web) as research medium because many websites post festival and traveling information such as festival, scenic spots, resorts, and local restaurants. However, without an organized research medium, many people who interested in culture discover the difficulty of focusing on research or making a choice from the massive festival and travel-related categories and sites. This paper describes and integrates a website with many festival and travel-related functions into one platform called Festival and Travel Planning Network. This platform allows easy access for users to obtain various festival information, city travel, restaurant, and hotel guidelines in Taiwan. This network automatically helps travelers to plan their tours and find accommodations by simply selecting by their interests of festival visits and hotel types on the website.The Festival and Travel Planning Network also provides online traveling suitcases allowing members to bookmark their favorite travel spots. The Festival and Travel Planning Network website is http://140.131.84.199/holiday/index/index_e.htm. For maximum quality, display resolution should be set at 1024×768. As for technical support, the website uses Internet Information Services as the web server and ASP.NET 3.5 as the web application framework. The database server is performed by SQL Server 2008 to organize and manage data. The webpage graphic and animation designer used Ulead PhotoImpact X3 and Adobe Photoshop CS5 and Flash CS5 as design tools

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35

Božić, Z., i E. Hobson. "Urban underground network expansion planning". IEE Proceedings - Generation, Transmission and Distribution 144, nr 2 (1997): 118. http://dx.doi.org/10.1049/ip-gtd:19970850.

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36

Blum, Johannes, i Sabine Storandt. "Scalability of Route Planning Techniques". Proceedings of the International Conference on Automated Planning and Scheduling 28 (15.06.2018): 20–28. http://dx.doi.org/10.1609/icaps.v28i1.13888.

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In this paper, we thoroughly analyze the scaling behavior of several state-of-the-art route planning techniques for road networks, all of which rely on preprocessing. One goal is to determine which technique is most suitable to be used on huge networks. To be able to conduct scalability studies in a clean way, we first describe a new kind of road network generator that allows to produce road networks even larger than that of our planet with similar properties as real networks. We then carefully implement several preprocessing-based route planning techniques, as contraction hierarchies, hub labels and transit nodes, to study their space consumption as well as their search spaces in different sized networks. This allows to derive functions that describe their empirical scaling behavior for the first time. We also compare our functions to existing theoretical bounds. We show that several of our results can not be sufficiently explained by the theoretical investigations conducted so far. Hence our results encourage a further look for road network models that allow for better predictions.

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37

Rastgou, Abdollah, i Saman Hosseini-Hemati. "Simultaneous Planning of the Medium and Low Voltage Distribution Networks under Uncertainty: A Bi-Level Optimization Approach". International Transactions on Electrical Energy Systems 2022 (28.09.2022): 1–19. http://dx.doi.org/10.1155/2022/2267926.

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Distribution network expansion planning (DNEP) is one of the important matters in the field of planning and operation of electrical power systems. Since many costs and losses have occurred in the distribution networks, it has increased attention towards this network. The electrical energy distribution network is divided into two parts: the medium voltage (MV) network and the low voltage (LV) network. The main problem in this field is that planning is done either only on the MV network or only on the LV network. While planning in each of these networks has a significant effect on the other networks, this important case has not been considered in most research studies. Therefore, this study has tried to do integrated planning in the form of a bi-level model in the presence of different types of distributed generations (DGs) and consider the uncertainties of renewable sources and load demand in both MV and LV networks so that the planning and operation costs are minimized. In the proposed bi-level model, the upper-level section aims to minimize the investment and the operation cost of the MV network, and the lower-level problem minimizes the investment and the operation cost of the LV network considering the DGs and pollution emission. The obtained results show the effectiveness of the proposed model.

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38

Lu, Jiangang, Wenjie Zheng, Ruifeng Zhao, Kaiwen Zeng, Shuwen Qiu i Ting Yang. "Heterogeneous communication network planning based on ant colony algorithm in smart grid". Journal of Physics: Conference Series 2384, nr 1 (1.12.2022): 012051. http://dx.doi.org/10.1088/1742-6596/2384/1/012051.

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Abstract With the development of smart grids, highly automated power systems increasingly rely on communication networks, and research on the reliability, safety, and economy of heterogeneous communication networks is particularly important. Traditional network planning methods do not take into account network load problems, resulting in serious network congestion and long delays. Aiming at the above problems, this paper proposes a heterogeneous communication network planning method for a smart grid based on an improved ant colony algorithm. This method improves the original ant colony algorithm by updating the pheromone concentration of the network node in real time and realizes the planning of heterogeneous communication networks in the smart grid. Simulation results show that the proposed method has the advantages of avoiding local network congestion, reducing the average delay, and improving network stability.

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39

Dobricic, Milica, Nenad Sekulic i Bosko Josimovic. "Spatial planning and ecological networks in Serbia". Spatium, nr 38 (2017): 18–26. http://dx.doi.org/10.2298/spat1738018d.

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The paper explains the importance and role of spatial planning in the context of the preservation and sustainable use of ecological networks. The concept of ecological networks is presented in terms of its main goals, structure, functions and approaches to biodiversity conservation. The paper gives an overview of ecological network development in Serbia, but also an overview of the activities carried out in establishing the NATURA 2000 European ecological network. Possibilities for improving the spatial planning process in light of the functional development of ecological networks in Serbia are indicated through an analysis of the requirements arising from the policies relevant for spatial planning and the development of ecological networks using the example of drawn up spatial plans.

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40

Wang, Junhai, Leijin Shan, Yongxia Dai, Lingling Ming i Dayang Yu. "A Systematic Planning Method for the Electric Vehicles Charging Service Network". Journal of Clean Energy Technologies 3, nr 2 (2015): 155–58. http://dx.doi.org/10.7763/jocet.2015.v3.187.

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41

Plets, David, Wout Joseph, Kris Vanhecke i Luc Martens. "EXPOSURE OPTIMIZATION IN INDOOR WIRELESS NETWORKS BY HEURISTIC NETWORK PLANNING". Progress In Electromagnetics Research 139 (2013): 445–78. http://dx.doi.org/10.2528/pier13013003.

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42

Pastorelli, Rosanna, Gabriella Bosco, Stefano Piciaccia i Fabrizio Forghieri. "Network Planning Strategies for Next-Generation Flexible Optical Networks [Invited]". Journal of Optical Communications and Networking 7, nr 3 (16.02.2015): A511. http://dx.doi.org/10.1364/jocn.7.00a511.

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43

Pagadrai, Sasikanth, Muhittin Yilmaz i Pratyush Valluri. "A Delay based MILP for Network Planning in Optical Networks". Procedia Computer Science 20 (2013): 427–32. http://dx.doi.org/10.1016/j.procs.2013.09.298.

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44

Millar, Robert John, Eero Saarijärvi i Matti Lehtonen. "An Improved Initial Network for Distribution Network Planning Algorithms". International Review of Electrical Engineering (IREE) 9, nr 3 (30.06.2014): 538. http://dx.doi.org/10.15866/iree.v9i3.792.

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45

Xu, Banghai, Ruofeng Wang i Wanli Su. "Smart generic cabling and network planning in office network". International Journal of High Performance Systems Architecture 7, nr 4 (2017): 204. http://dx.doi.org/10.1504/ijhpsa.2017.092387.

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46

Su, Wanli, Ruofeng Wang i Banghai Xu. "Smart generic cabling and network planning in office network". International Journal of High Performance Systems Architecture 7, nr 4 (2017): 204. http://dx.doi.org/10.1504/ijhpsa.2017.10013592.

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47

Mezhoudi, Mohcene, Mohamed L. El-Sayed i Paul F. Gagen. "Network service providers: Practical considerations for optical network planning". Bell Labs Technical Journal 11, nr 2 (4.08.2006): 145–55. http://dx.doi.org/10.1002/bltj.20166.

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48

Moysen, Jessica, Lorenza Giupponi i Josep Mangues-Bafalluy. "A Mobile Network Planning Tool Based on Data Analytics". Mobile Information Systems 2017 (2017): 1–16. http://dx.doi.org/10.1155/2017/6740585.

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Planning future mobile networks entails multiple challenges due to the high complexity of the network to be managed. Beyond 4G and 5G networks are expected to be characterized by a high densification of nodes and heterogeneity of layers, applications, and Radio Access Technologies (RAT). In this context, a network planning tool capable of dealing with this complexity is highly convenient. The objective is to exploit the information produced by and already available in the network to properly deploy, configure, and optimise network nodes. This work presents such a smart network planning tool that exploits Machine Learning (ML) techniques. The proposed approach is able to predict the Quality of Service (QoS) experienced by the users based on the measurement history of the network. We select Physical Resource Block (PRB) per Megabit (Mb) as our main QoS indicator to optimise, since minimizing this metric allows offering the same service to users by consuming less resources, so, being more cost-effective. Two cases of study are considered in order to evaluate the performance of the proposed scheme, one to smartly plan the small cell deployment in a dense indoor scenario and a second one to timely face a detected fault in a macrocell network.

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49

Paramonov, Alexander, Evgeny Tonkikh, Ammar Muthanna, Ibrahim A. Elgendy i Andrey Koucheryavy. "Fractals for Internet of Things Network Structure Planning". International Journal of Information Security and Privacy 16, nr 1 (1.01.2022): 1–12. http://dx.doi.org/10.4018/ijisp.305223.

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Wireless communication networks and technologies are witnessed a huge improvement which gain a large number of users. In addition, the choice and using methods of the network are depending on the environment in which it is created. Although the network in each case is unique, many of them share a lot of common. To this end, we propose a new approach for planning the structure of the Internet of Things (IoT) network based on fractals, where fractal figures are utilized to describe the structure of the target environment. Moreover, fractal dimension’s estimation, fraction area occupied by the target environment, and network model are used in the planning process. This approach allows you to choose a model that accurately describes the properties of the environment. Finally, the results proved the suitability of this approach for the IoT network structure planning in an urban or other environment based on the target environment’s data.

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HACKBARTH, KLAUS D., i J. ANTONIO PORTILLA. "DIDERO 3G A STRATEGIC NETWORK PLANNING TOOL FOR 3G MOBILE NETWORKS". International Journal of Information Technology & Decision Making 02, nr 04 (grudzień 2003): 531–55. http://dx.doi.org/10.1142/s0219622003000859.

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Strategic Planning for mobile networks has to consider the evolution from the existing 2nd Generation GSM architecture to a long term 3rd Generation UMTS architecture over various intermediate steps in the form of hybrid networks. The study of this evolution requires a corresponding Strategic Planning tool. This article deals with Strategic Network Planning and develops the corresponding models considering aspects like radio propagation, multi-service traffic and user mobility. The article presents a corresponding strategic planning tool which allows to study the evolution of a mobile network under the corresponding input data in the form of a service and topographic scenarios. The application of the tool to a specific network region is shown and costing perspectives for the different services are discussed.

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