1 / 86

Network Optimization 網路最佳化

Network Optimization 網路最佳化. Chih-Hao Lin ( 林志浩 ) Department of Information Management Chung Yuan Christian University December 20, 2019. 林志浩 ( Chih-Hao Lin ). 學歷：國立台灣大學 資訊管理學 博士 現職：中原大學 資管系 助理教授 專長：系統最佳化、演化式計算、效能評估、無線通訊網路、網路規劃與容量管理 課程：系統最佳化、資源規劃與管理、網路規劃與管理、資源管理實務、企業資料通訊、管理數學 聯絡方式：

partain
Download Presentation

Network Optimization 網路最佳化

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Network Optimization網路最佳化 Chih-Hao Lin (林志浩) Department of Information Management Chung Yuan Christian University December 20, 2019

  2. 林志浩 (Chih-Hao Lin) • 學歷：國立台灣大學 資訊管理學 博士 • 現職：中原大學 資管系 助理教授 • 專長：系統最佳化、演化式計算、效能評估、無線通訊網路、網路規劃與容量管理 • 課程：系統最佳化、資源規劃與管理、網路規劃與管理、資源管理實務、企業資料通訊、管理數學 • 聯絡方式： • Tel: (03) 265-5410 • E-mail: linch@cycu.edu.tw Chih-Hao Lin

  3. Outline • Introduction • Motivation: the bridges of Koenigsberg • Network flow applications • Possible problems in developing decision models • Shortest path problem • Maximum flow problem • Minimum cost flow problem • Network optimization issues • Two research examples • Conclusion Chih-Hao Lin

  4. Introduction • Deterministic mathematical model • All parameter values are assumed to be certainty • Mathematical programs which decide how to plan or “program” activities. • “Netform” • Network flow-based formulation • Network-related formulation. • Deterministic network optimization • Solve deterministic network-related formulation by optimization technique Chih-Hao Lin

  5. Outline • Introduction • Motivation: the bridges of Koenigsberg • Network flow applications • Possible problems in developing decision models • Shortest path problem • Maximum flow problem • Minimum cost flow problem • Network optimization issues • Two research examples • Conclusion Chih-Hao Lin

  6. The Bridges of Koenigsberg: Eüler 1736 (from J.B. Orlin in MIT) • “Graph Theory” began in 1736 • Leonard Eüler • Visited Koenigsberg • People wondered whether it is possible to take a walk, end up where you started from, and cross each bridge in Koenigsberg exactly once • Generally it was believed to be impossible Chih-Hao Lin

  7. The Bridges of Koenigsberg: Eüler 1736(cont’d)(from J.B. Orlin in MIT) Chih-Hao Lin

  8. The Bridges of Koenigsberg: Eüler 1736 (cont’d)(from J.B. Orlin in MIT) Chih-Hao Lin

  9. The Bridges of Koenigsberg: Eüler 1736 (cont’d)(from J.B. Orlin in MIT) Chih-Hao Lin

  10. The Bridges of Koenigsberg: Eüler 1736 (cont’d)(from J.B. Orlin in MIT) Chih-Hao Lin

  11. The Bridges of Koenigsberg: Eüler 1736(cont’d)(from J.B. Orlin in MIT) Chih-Hao Lin

  12. Outline • Introduction • Motivation: The Bridges of Koenigsberg • Network flow applications • Possible problems in developing decision models • Shortest path problem • Maximum flow problem • Minimum cost flow problem • Network optimization issues • Two research examples • Conclusion Chih-Hao Lin

  13. Network Flow Applications • Communications • Design and expansion of communication systems • Flow of information across networks • Transportation • Transportation of goods over transportation networks • Scheduling of fleets of airplanes: time/space networks • Manufacturing • Scheduling of goods for manufacturing • Flow of manufactured items within inventory systems • Personnel assignment • Assignment of crews to airline schedules • Assignment of drivers to vehicles Chih-Hao Lin

  14. Outline • Introduction • Motivation: The Bridges of Koenigsberg • Network flow applications • Possible problems in developing decision models • Shortest path problem • Maximum flow problem • Minimum cost flow problem • Network optimization issues • Two research examples • Conclusion Chih-Hao Lin

  15. Chih-Hao Lin

  16. Defining the Problem • Conflicting viewpoints • Analysts may often have to consider conflicting viewpoints in defining the problem • Impact on correlative part of system • Problems do not exist in isolation and are not owned • Assumptions • To state problems in terms of solutions • State of the art • Problem can change during the development Chih-Hao Lin

  17. Chih-Hao Lin

  18. Developing a Model • Fitting and modifying the textbooks models • Not always match the textbook approach • Understanding the models • Most readers will not use the results of a model they do not understand Chih-Hao Lin

  19. Chih-Hao Lin

  20. Acquiring Input Data • Using trustworthy data • For example, most data generated in a firm come from basic accounting reports • Validity of data Chih-Hao Lin

  21. Chih-Hao Lin

  22. Developing a Solution • Illustrating the mathematical models with pictures • Hard-to-understand mathematics • Considering multi-objective problems • The limitation of only one answer Chih-Hao Lin

  23. Chih-Hao Lin

  24. Testing the Solution • Convince the reader of the validity of the results • Review every assumption Chih-Hao Lin

  25. Chih-Hao Lin

  26. Analyzing the Results • The results must be analyzed in terms of how they will affect the total organization Chih-Hao Lin

  27. Chih-Hao Lin

  28. Outline • Introduction • Motivation: the bridges of Koenigsberg • Network flow applications • Possible problems in developing decision models • Shortest path problem • Maximum flow problem • Minimum cost flow problem • Network optimization issues • Two research examples • Conclusion Chih-Hao Lin

  29. Shortest Path Problem • R.K. Ahuja, T.L. Magnanti and J.B. Orlin, Network Flows: Theory, Algorithms, and Applications, Prentice-Hall, 1993. • Consider a network G = (N, A) • There is an origin node 1 and a destination node 6. • What is the shortest path from 1 to 6? Chih-Hao Lin

  30. Shortest Path Problem (cont’d) • Label-setting algorithms: Non-negative arc lengths • Dijkstra’s Algorithm (1959)  O(n2) • Radix heap implementation (1990)  O(m+n log(nC)) • Label correcting algorithm: Negative costs permitted • Bellman–Ford algorithm (1956) O(min(n2mC, m2n)) • FIFO implementation (1958)  O(mn) • Dynamic lot sizing application • All-pairs shortest path problem • Repeated shortest path algorithm  O(nm+n2 log C) • Floyd–Warshall algorithm (sometimes known as the Roy–Floyd algorithm or WFI Algorithm) O(n3) Chih-Hao Lin

  31. Outline • Introduction • Motivation: the bridges of Koenigsberg • Network flow applications • Possible problems in developing decision models • Shortest path problem • Maximum flow problem • Minimum cost flow problem • Network optimization issues • Two research examples • Conclusion Chih-Hao Lin

  32. Maximum Flow Problem • Directed Graph G = (N, A) • A source node s and a sink node t • Capacities uij on arc (i, j) • Maximize the flow out of s • Subject to flow out of i= flow into i, for i≠s or t. Chih-Hao Lin

  33. Maximum Flow Problem (cont’d) • Labeling algorithm • Ford-Fulkerson algorithm (1956)  O(nmU) • Edmonds-Karp algorithm (1972) • The largest augmenting path algorithm  O(m2 log U) • The shortest augmenting path algorithm  O(nm2) • Generic preflow-push algorithm • Push-relabel algorithm (1970)  O(n2 m) • FIFO preflow-push algorithm (1982)  O(n3) • Applications • Network reliability and maximum flow Chih-Hao Lin

  34. Outline • Introduction • Motivation: the bridges of Koenigsberg • Network flow applications • Possible problems in developing decision models • Shortest path problem • Maximum flow problem • Minimum cost flow problem • Network optimization issues • Two research examples • Conclusion Chih-Hao Lin

  35. 0 10, $4 2 4 30, $7 25, $5 25 1 20, $2 20, $6 20, $1 3 5 25, $2 -25 0 Minimum Cost Flow Problem • Consider a network G = (N, A) • Flow out of i -Flow into i = b(i) • Each arc has a linear cost and a capacity 5 5 5 20 20 Chih-Hao Lin

  36. Minimum Cost Flow Problem (cont’d) • Basic algorithms • Cycle-canceling algorithm (1967)  O(nm2CU) • Successive shortest path algorithm (1961)  O(nU S(n, m, nC)) • Polynomial-time algorithm • Capacity scaling algorithm (1972)  O((m logU)  S(n, m, nC))) • Cost scaling algorithm (1980)  O(n3log(nC)) • Network simplex algorithms • Minimum cost flow applications Chih-Hao Lin

  37. Outline • Introduction • Motivation: the bridges of Koenigsberg • Network flow applications • Possible problems in developing decision models • Shortest path problem • Maximum flow problem • Minimum cost flow problem • Network optimization issues • Two research examples • Conclusion Chih-Hao Lin

  38. Network Planning Performance Optimization Network Monitoring Network Capacity Expansion Network Servicing Network Optimization Issues • Network planning & capacity management Chih-Hao Lin

  39. Network Optimization Issues (cont’d) • Network planning • To design a network with the minimum installation and operation cost subject to performance (QoS), survivability / reliability and other constraints • Communication networks • GSM (The 2G digital cellular system) • WCDMA (The 3G wideband cellular system) • Wireless LAN (i.e. IEEE 802.11, WiFi) • Wireless MAN (i.e. IEEE 802.16, WiMAX) Chih-Hao Lin

  40. A Wireless Cell Planning Algorithmfor Adaptive Beam and SDMA Systems Chih-Hao Lin

  41. Network Optimization Issues (cont’d) • Network performance optimization • For an in-service traffic network, to assure pre-specified QoS requirements and/or to optimize certain performance measures, e.g. to minimize the total system throughput/revenue or to minimize the average cross-network packet delay • Networking mechanisms • Channel assignment • Resource management • Admission control • Quality of service routing • Multipath and multicast routing Chih-Hao Lin

  42. User 2 4 3 1 2 1 2 1 1 2 2 2 4 4 1 1 2 3 2 4 3 1 4 4 3 3 2 3 2 An Adaptive Resource Allocation Algorithmin OFDMA Networks Sub-carrier Resource Allocation Algorithm OFDM time slot Chih-Hao Lin

  43. Network Optimization Issues (cont’d) • Network monitoring • For an in-service traffic network, by using traffic measurements or performance modeling techniques (or a combination of the two) to identify potential performance exceptions and to activate corrective actions • To collect traffic measurements for load forecasting purposes (to feed the servicing and the capacity expansion processes) Chih-Hao Lin

  44. An Optimal Monitoring Scheme • Three typical questions: • What engineering thresholds for network elements to use when end-to-end performance objectives are concerned? • When/How often to monitor the network? • What parts of network (or the whole network) to monitor? Chih-Hao Lin

  45. Network Optimization Issues (cont’d) • Network servicing • Using corrective actions to alleviate the performance exceptions identified by the monitoring process • Three typical approaches • Traffic rerouting/load balancing • Resource reallocation • Sizing (minimal-cost capacity augmentation to satisfy the current demand) Chih-Hao Lin

  46. A Bandwidth Reservation Algorithm for Wireless Cellular Networks Considering Mobility Characteristic and Service Level Agreement Chih-Hao Lin

  47. Network Optimization Issues (cont’d) • Network capacity expansion • For an in-service traffic network, to determine the capacity augmentation strategy at each decision stage over a pre-specified time horizon such that the total cost, considering the effect of economies of scale and composite cost of money, is minimized • Communication networks • Wireless LAN (i.e. IEEE 802.11, Wi-Fi) • Wireless MAN (i.e. IEEE 802.16, WiMAX) • WSN (Wireless sensor network) Chih-Hao Lin

  48. Network Capacity Expansion S.R. Saunders, Antennas and Propagation for Wireless Communication Systems, John Wiley & Sons, Ltd., 1999. Chih-Hao Lin

  49. Our Research Results • Communication networks • GSM (The 2G digital cellular system) • WCDMA (The 3G wideband cellular system) • Wireless LAN (i.e. IEEE 802.11, Wi-Fi) • Wireless MAN (i.e. IEEE 802.16, WiMAX) • OFDMA (Orthogonal frequency division multiple access) • WSN (Wireless sensor network) Chih-Hao Lin

  50. Our Research Results (cont’d) • Topics • Network design and expansion • Performance assurance and optimization • Resource allocation and management • Mobility management • Admission control • Quality of service routing • Network servicing • Reliability and survivability Chih-Hao Lin

More Related