Challenge 3 Self Organized Networks proposed by Fon Presentation May - PowerPoint PPT Presentation

See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/321483748 Challenge 3 Self Organized Networks proposed by Fon Presentation · May 2017 CITATIONS 0 9 authors , including: Aleksandra Stojanova Dusan Bikov Goce Delcev University of Š tip Goce Delcev University of Š tip 17 PUBLICATIONS 0 CITATIONS 10 PUBLICATIONS 2 CITATIONS SEE PROFILE SEE PROFILE Some of the authors of this publication are also working on these related projects: VitoshaTrade ( github.com/TodorBalabanov/VitoshaTrade ) View project https://github.com/TodorBalabanov/EllipsesImageApproximator View project All content following this page was uploaded by Todor Balabanov on 03 December 2017. The user has requested enhancement of the downloaded file.

Challenge 3 Self Organized Networks proposed by Fon Aleksandra Stojanova, Dusan Bikov, Gorka Kobeaga, Javier Del Ser Lorente, Mirjana Kocaleva, Thimjo Koca, Thomas Ashley, Todor Balabanov

Agenda ● P r o b l e m d e s c r i p t i o n ● Study group goals and structure ● Solution proposed ● Experiments and results ● Conclusions 2 15-19 May 2017 Self Organized Networks

Wi-Fi in the Real World ● It is possible to have large number of WiFi hotspots within the same coverage area – T h i s n u m b e r i s o n l y g o i n g t o i n c r e a s e i n t h e n e x t d e c a d e ● Hotspots may operate in interfering frequencies with different power levels – User performance is afgected due to the medium access mechanism imposed by the 802.11 standard 3 15-19 May 2017 Self Organized Networks

The 2.4 GHz band [1] 4 15-19 May 2017 Self Organized Networks

The 5 GHz band [1] 5 15-19 May 2017 Self Organized Networks

Shared Medium Transmissions ● CoChannel Interference (CCI) - p r e f e r r e d – Transmissions occur in the same frequency channel ● Adjacent Channel Interference (ACI) – Transmissions are sent on adjacent or partially overlapping channels ● D e f e r o n g o i n g t r a n s m i s s i o n s ● Corrupt transmitted frames – I n c r e a s e n u m b e r o f r e t r a n s m i s s i o n s 6 15-19 May 2017 Self Organized Networks

Study Group Goals ● Propose improved algorithms for frequency selection – Unmanaged partially cooperative urban environment – Some of the hotspots are not accessible for configuration (owned by other companies/people) 7 15-19 May 2017 Self Organized Networks

Group Team Work ● Two teams – Team A ● Algorithms (research, description, presentation) – Team P ● Python (implementation, simulations, validation) 8 15-19 May 2017 Self Organized Networks

Working Methodology ● Short Sprints – Small tasks – Clear deadlines – Teams synchronization twice a day ● Morning ● Afuernoon 9 15-19 May 2017 Self Organized Networks

Algorithm Input-Output ● Input – List of neighboring hotspots ● Signal level ● Frequency of operation ● Location (only for own devices) ● Output – List of frequency channels selection 10 15-19 May 2017 Self Organized Networks

Optimization Target ● Interference mitigation – Leading to an optimized usage of hotspots ● Optimized spectrum usage ● Higher bandwidth for network accessing – Better customer satisfaction 11 15-19 May 2017 Self Organized Networks

First Proposal ● Iterated Local Search – Modification of local search or hill climbing – Modification consists of iterating calls to the local search routine ● Initial solution – Greedy start – Random start 12 15-19 May 2017 Self Organized Networks

First Algorithm [2] 13 15-19 May 2017 Self Organized Networks

Second Proposal ● Reinforcement Learning based Local Search – A combined reinforcement learning techniques with descent-based local search 14 15-19 May 2017 Self Organized Networks

Second Algorithm [3] 15 15-19 May 2017 Self Organized Networks

Solution Validation ● Genetic Algorithm based solution – Available in advance – Chromosomes encode Fon’s hotspots channels number selection – Fitness function is the total interfering calculated in Fon’s hotspots 16 15-19 May 2017 Self Organized Networks

Third Algorithm [4] 17 15-19 May 2017 Self Organized Networks

Real Data – Tokyo, Japan 18 15-19 May 2017 Self Organized Networks

Artificial Generated Data 19 15-19 May 2017 Self Organized Networks

ILS – Convergence 20 15-19 May 2017 Self Organized Networks

RLLS – Convergence 21 15-19 May 2017 Self Organized Networks

GA – Logarithmic Scale Convergence 22 15-19 May 2017 Self Organized Networks

GA – Linear Scale Convergence 23 15-19 May 2017 Self Organized Networks

Conclusions & Further Work ● Heuristic optimization is effective – But it is time consuming – Python is very useful for this kind of calculations ● As further work Genetic Algorithm can be combined with Iterated Local Search and Reinforcement Learning based Local Search 24 15-19 May 2017 Self Organized Networks

References 1. Problem Statement: Self Organized Networks, ESGI 131 Challenge Self Organized Networks (proposed by Fon), 15-19 May 2017, Bilbao, Spain 2. Thomas Stutzle, Iterated Local Search - Variable Neighborhood Search, Darmstadt University of Technology Department of Computer Science Intellectics Group, MN Summerschool, 2003, Tenerife, Spain 3. Yangming Zhoua, Jin-Kao Hao, Beatrice Duvala, Reinforcement learning based local search for grouping problems: A case study on graph coloring, Expert Systems with Applications Volume 64, 1 December 2016, pp. 412–422 4. Gualtiero Colombo, A genetic algorithm for frequency assignment with problem decomposition, Journal International Journal of Mobile Network Design and Innovation archive, Volume 1 Issue 2, September 2006, pp. 102-112 25 15-19 May 2017 Self Organized Networks

Questions & Answers Thank you! 26 15-19 May 2017 Self Organized Networks View publication stats View publication stats