Investigating the performance and resilience of mesh networks versus their traditional star-topology counterparts

Abstract:
There are at least a few existing mesh-topology network technologies. These include the IEEE 802.15.4 / Zigbee specifications, as well as recent IEEE 802.11 drafts. Mesh networks promise to increase packet throughput [2] through smarter routing protocols [3], and most of all improve network resilience to router failures [4] [5].

This project proposes to investigate these claims. To quantify the delta between mesh- and traditional star-topology (or "cluster tree") networks. Specifically, a partially connected mesh (as opposed to a fully connected graph) of nodes like that seen in a typical industrial control and automation setting, compared against the more traditional network topology of star networks with minimal connection redundancy.

The metrics considered by this project include:
Packet loss vs. number of failed
Packet throughput vs. hops. [6]
Average latency vs. hops. [6]

References:
[1] J. Nielsen, Official AAU Beamer Themes, Poster Theme and Report Templates, Jun. 2018. [Online]. Available: http : / / sqrt - 1 . dk / latex / latex . php (visited on 07/09/2018).
[2] Yuan Sun, Irfan Sheriff, Elizabeth M. Belding-Royer, and Kevin C. Almeroth, International Workshop on Wireless Traffic Measurements and Modeling Technical Paper, Jun. 2005. [Online]. Available: https://www.usenix.org/legacy/event/mobisys05/witmemo05/tech/full_papers/sun_yuan/sun_yuan_html/ (visited on 02/06/2020).
[3] Y. Yang, J. Wang, and R. Kravets, "Designing Routing Metrics for Mesh Netowkrs," en, p. 9.
[4] Ryu Miura, Masugi Inoue, Yasunori Owada, Kenichi Takizawa, Fumie Ono, Mikio Suzuki, Hiroyuki Tsuji, and Kiyoshi Hamaguchi, Disaster-resilient wireless mesh network - Experimental test-bed and demonstration - IEEE Conference Publication, Oct. 2013. [Online]. Available: https://ieeexplore-ieee-org.proxy.lib.sfu.ca/document/6618635 (visited on 02/09/2020).
[5] Nick Jones, Mesh Topologies Promise Resilient Wireless Networks, Jul. 2003. [Online]. Available: https : / / www . bus . umich . edu / kresgepublic / journals / gartner /research/116000/116077/116077.html (visited on 02/09/2020).
[6] Silicon AN1142: Mesh Network Performance , en, p. 11

The performance of mobile gaming using LTE and Wi-Fi

Abstract:
Gaming has become a major part of all internet traffic and mobile gaming is an emerging sector that has been neglected for a long time due to the limited performance of LTE. This report will explore how the advancements in LTE and Wi-Fi technologies have helped shape the future of mobile gaming.

References:
[1] W. Alf Inge, J. Martin, and S. Eivind, "Experiences from Implementing a Mobile Multiplayer Real-Time Game for Wireless Networks with High Latency," 2010 January 2010. [Online]. Available: https://www.hindawi.com/journals/ijcgt/2009/530367/. [Accessed 8 February 2020].
[2] G. M, D. Maggiorini, P. C and B. A, "A survey on interactive games over mobile networks," 10 February 2012. [Online]. Available: https://onlinelibrary.wiley.com/doi/epdf/10.1002/wcm.2197. [Accessed 8 February 2020].
[3] I. Fogg, "The State of Wifi vs Mobile Network Experience as 5G Arrives," November 2018. [Online]. Available: https://www.opensignal.com/sites/opensignal-com/files/data/reports/global/data-2018-11/state_of_wifi_vs_mobile_opensignal_201811.pdf. [Accessed 8 February 2020].
[4] T. L.-N. Quang-Dung Ho, "Smart Grid Communications Networks: Wireless Technologies, Protocols, Issues, and Standards," in Handbook of Green Information and Communication Systems, Orlando, Academic Press, 2013, pp. 115-146.
[5] F. A. Yongwan Park, "Overview Of Mobile Communications," in Enhanced Radio Access Technologies for Next Generation Mobile Communications, Springer, Dordrecht, 2007, pp. 1-37.
[6] V. Thrimurthulu and M. S. N.S, "Device-to-device communications in long term evaluation-advanced network," 11 January 2018. [Online]. Available: https://ieeexplore-ieee-org.proxy.lib.sfu.ca/document/8250577/citations. [Accessed 8 February 2020].
[7] H. Lei, Y. Wang, M. Lu and D. Yang, "Analysis and Simulation for Radio Access Network Architecture of 3GPP Long Term Evaluation," 4 December 2007. [Online]. Available: https://ieeexplore-ieee-org.proxy.lib.sfu.ca/document/4394254. [Accessed 8 February 2020].

Cloud gaming: analysis and simulation

Abstract:
Cloud Gaming is an upcoming technology that has only recently entered the spotlight for many gamers. At its essence, cloud gaming is a system in which the client (gamer) sends the most complex computations required to play a game to a server for computation. The server then returns a video stream for the client to decode. This offloads the task of acquiring powerful hardware (GPU, CPU, RAM, etc.) from the client to the server. However, this comes with its own drawbacks, mainly being that both the client and server must be able to support high levels of network goodput with low delay to optimize the gaming experience. Although the details of the methods used to get around these issues may be proprietary, the general approaches are well-documented for those interested in such topics. This paper performs an analysis of some of these approaches along with a cloud gaming network simulation consisting of the best solutions we found.

References:
[1] Z. Li, H. Melvin, R. Bruzgiene, P. Pocta, L. Skorin-Kapov, and A. Zgank, "Lag Compensation for First-Person Shooter Games in Cloud Gaming", Autonomous Control for a Reliable Internet of Services, 2018. [Online]. Available: https://www.academia.edu/36806094/Lag_Compensation_for_First-Person_Shooter_Games_in_Cloud_Gaming. [Accessed: 08- Feb- 2020]
[2] R. E. Ewelle, Y. Francillette, G. Mahdi, and A. Gouaich, "Network Traffic Adaptation for Cloud Games," Journal on Cloud Computing: Services and Architecture, 2013. [Online]. Available: https://www.academia.edu/11682718/Network_Traffic_Adaptation_for_Cloud_Games. [Accessed: 08- Feb- 2020]
[3] M. Hemmati, A. Javadtalab, A. A. N. Shirehjini, S. Shirmohammadi, and T. Arici, "Game as Video: Bit Rate Reduction through Adaptive Object Encoding," Proceeding of the 23rd ACM Workshop on Network and Operating Systems Support for Digital Audio and Video - NOSSDAV '13, 2013. [Online]. Available: https://www.academia.edu/13123404/Game_as_video. [Accessed: 08- Feb- 2020]
[4] W. Cai, R. Shea, C. Y. Huang, K. T. Chen, J. Liu, V. C. M. Leung, and C. H. Hsu, "A Survey on Cloud Gaming: Future of Computer Games," IEEE Access (Volume: 4), 2016. [Online]. Available: https://www.researchgate.net/publication/306006176_A_Survey_on_Cloud_Gaming_Future_of_Computer_Games. [Accessed: 08- Feb- 2020]
[5] W. Cai, F. Chi, X. Wang, and V. C. M. Leung, "Toward Multiplayer Cooperative Cloud Gaming," IEEE Cloud Computing, 2018. [Online]. Available: https://mypage.cuhk.edu.cn/academics/caiwei/paper/CaiCL18.pdf. [Accessed: 08- Feb- 2020]

Performance analysis of video streaming over WiFi (802.11n) network

Abstract:
Driven by the advancement in data compression technology and increasing demand, video streaming has become one of the main services people use with the Internet. With the wide adoption of WiFi (802.11n), it is vital to analyze the performance of video streaming under different scenarios. The project will simulate video streaming with traced data on a target device in ns-3 and analyze the performance of the target device over WiFi connection under different scenarios.

References:
[1] L. Gao, M. Tang, H. Pang, J. Huang, and L. Sun, "Multi-User Cooperative Mobile Video Streaming: Performance Analysis and Online Mechanism Design," in IEEE Transactions on Mobile Computing, vol. 18, no. 2, pp. 376-389, 1 Feb. 2019. [Online]. Available: https://ieeexplore-ieee-org.proxy.lib.sfu.ca/document/8356092. [Accessed: 02-Mar-2020].
[2] X. Zhu and B. Girod, "Video streaming over wireless networks," 2007 15th European Signal Processing Conference, Poznan, 2007, pp. 1462-1466. [Online]. Available: https://ieeexplore-ieee-org.proxy.lib.sfu.ca/document/7099048. [Accessed: 02-Mar-2020].
[3] E. Ozfatura, O. Ercetin, and H. Inaltekin, "Optimal Network-Assisted Multiuser DASH Video Streaming," in IEEE Transactions on Broadcasting, vol. 64, no. 2, pp. 247-265, June 2018. [Online]. Available: https://ieeexplore-ieee-org.proxy.lib.sfu.ca/document/8345181. [Accessed: 02-Mar-2020].
[4] A. Ligata, E. Perenda, and H. Gacanin, "Quality of Experience Inference for Video Services in Home WiFi Networks," in IEEE Communications Magazine, vol. 56, no. 3, pp. 187-193, March 2018. [Online]. Available: https://ieeexplore-ieee-org.proxy.lib.sfu.ca/document/8316791. [Accessed: 02-Mar-2020].
[5] H. Zhang, Z. Lu, X. Wen and Z. Hu, "QoE-Based Reduction of Handover Delay for Multimedia Application in IEEE 802.11 Networks," in IEEE Communications Letters, vol. 19, no. 11, pp. 1873-1876, Nov. 2015. [Online]. Available: https://ieeexplore-ieee-org.proxy.lib.sfu.ca/document/7163515. [Accessed: 02-Mar-2020].

Simulation of DDoS attacks in 4G networks

Abstract: 4G is the fourth generation of mobile technology. 4G networks have a lower latency than the earlier network generations, 2G and 3G which is important for real-time interaction applications. These specifications allow 4G networks to connect to a myriad of smart devices in the same infrastructure. Consequently, due to the network's immense size there is room for DDoS attacks on devices with poor security. This project aims to simulate a small 4G network and observe the effects of a successful DDoS attack. Different scenarios will be simulated to see the effects of the attacks on the targeted devices in the network. Looking closely at the targeted device, this project will discuss any performance changes to the devices surrounding the affected device as well as the entire network.

References:
[1] K. Alieyan, M. M. Kadhum, M. Anbar, S. U. Rehman, and N. K. A. Alajmi, "An overview of DDoS attacks based on DNS," 2016 International Conference on Information and Communication Technology Convergence (ICTC), Jeju, 2016, pp. 276-280.
[2] J. Henrydoss and T. Boult, "Critical security review and study of DDoS attacks on LTE mobile network," 2014 IEEE Asia Pacific Conference on Wireless and Mobile, Bali, 2014, pp. 194-200.
[3] M. Khosroshahy, D. Qiu, and M. K. Mehmet Ali, "Botnets in 4G cellular networks: Platforms to launch DDoS attacks against the air interface," 2013 International Conference on Selected Topics in Mobile and Wireless Networking (MoWNeT), Montreal, QC, 2013, pp. 30-35.
[4] Piro, Giuseppe & Baldo, Nicola & Miozzo, Marco. (2011). An LTE module for the ns-3 network simulator. Proceedings of the 4th International ICST Conference on Simulation Tools and Techniques: March 2011. 10.4108/icst.simutools.2011.245571.
[5] D, Y., M, S., Uvaze Ahamed, A., & S, N. (2019). Some Investigation on DDOS Attack Models in Mobile Networks. International Journal Of Interactive Mobile Technologies (IJIM), 13(10), pp. 71-88. doi:http://dx.doi.org/10.3991/ijim.v13i10.11304
[6] Balyk, A. & Karpinski, Mikolaj & Naglik, A. & Shangytbayeva, G. & Romanets, Ihor. (2017). Using graphic network simulator 3 for DDoS attacks simulation. International Journal of Computing. 16. 219-225.
[7] A. H. Khan, M. A. Qadeer, J. A. Ansari and S. Waheed, "4G as a Next Generation Wireless Network," 2009 International Conference on Future Computer and Communication, Kuala Lumpar, 2009, pp. 334-338.

Simulation of a smart meter neighborhood

Abstract:
With the big shift towards environmental conservation in recent years, "smart grid" systems are becoming more widely implemented around the world [1]. Using smart power meters, smart grid systems can selectively send power to customers based on real-time data, allowing for efficient power transfer and cost savings [2]. As of 2014, over 99 % of BC Hydro customers have had their traditional power meter replaced with an Itron CENTRON smart meter as part of the Itron OpenWay smart grid solution employed [3, 4], making the topic of local interest. The smart meters collect and send customer power data to BC Hydro over an IPv6 mesh network [4, 5]. A typical Lower Mainland neighborhood equipped with smart meters is modelled and simulated in Riverbed Modeler Academic Edition 17.5. This report analyzes the simulation results and explores the communication networks used in BC Hydro's smart grid.

References:
[1] X. Lu, W. Wang, and J. Ma, "An empirical study of communication infrastructures towards the smart grid: design, implementation, and evaluation," IEEE Trans. Smart Grid, vol. 4, no. 1, pp. 170-183, Mar. 2013, doi: 10.1109/TSG.2012.2225453. Accessed: Feb. 9, 2020. [Online]. Available: https://ieeexplore.ieee.org/document/6461498
[2] "Advanced metering infrastructure and customer systems: results from the smart grid investment grant program," U.S Department of Energy Office of Electricity Delivery and Energy Reliability, Washington, DC, USA. Accessed: Feb. 9, 2020. [Online]. Available: https://www.energy.gov/sites/prod/files/2016/12/f34/AMI%20Summary%20Report_09-26-16.pdf
[3] BC Hydro. "Smart meters help customers save via MyHydro." BCHydro.com. https://www.bchydro.com/news/conservation/2014/smart-meters-help-customers-save-via-myhydro.html (accessed Feb. 9, 2020).
[4] "RF safety compliance of OpenWay Smart Meters and the CG-Mesh IPv6 network". Itron Inc., Liberty Lake, WA, USA. Accessed: Feb. 9, 2020. [Online]. Available: https://app.bchydro.com/content/dam/BCHydro/customer-portal/documents/accounts-billing/customer-care/smart-metering/itron-open-way-rf-white-paper.pdf
[5] P. Granger. "BC Hydro, Cisco and Itron - a Powerhouse in Canada". Blogs.Cisco.com. https://blogs.cisco.com/energy/bc-hydro-cisco-and-itron-a-powerhouse-in-canada (accessed Feb. 9, 2020).

QoE analysis of video streaming services on public and private Wi-Fi

Abstract:
Introduced to the public in 1999, the wireless network has broadly changed human activities, and for many years we have seen the shift to a wireless world. Thanks to the simple installation and the evolution of laptops and cellphones having built-in Wi-Fi, more companies are seeing the market to provide services through the wireless networks. With the increase in demand, we have seen the emergence of online video streaming services which appear in various discipline fields such as healthcare and entertainment. In order to obtain a high performance and security network service, the customers would hesitate between ethernet and public & private Wi-Fi. Therefore, this project will analyze, and compare the quality of experience in video streaming services on different network environments such as Public Wifi, Home 5G Wifi, and Ethernet.

References:
[1] Predicting quality of experience for online video service , Bulkan U. & Dagiuklas, T. Multimed Tools Appl (2019) 78: 18787.https://doi.org/10.1007/s11042-019-7164-9
[2] Video Streaming Over Wireless [Online]. Available: https://web.stanford.edu/~bgirod/pdfs/Zhu_Girod_EUSIPCO_07.pdf. [Accessed: 09-Feb-2020].
[3] S. Khorsandroo, R. Md Noor and S. Khorsandroo, "A generic quantitative relationship between quality of experience and packet loss in video streaming services," 2012 Fourth International Conference on Ubiquitous and Future Networks (ICUFN), Phuket, 2012, pp. 352-356.http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6261727&isnumber=6261644
[4] J. of C. S. IJCSIS. "A Close Assessment And Analysis Of Public WIFI," Academia.edu - Share research. [Online]. Available:https://www.academia.edu/30634995/A_CLOSE_ASSESSMENT_AND_ANALYSIS_OF_PUBLIC_WIFI. [Accessed: 10-Feb-2020]
[5] "Video streaming framework for lte in ns-3" [Online]. Available: https://github.com/c-steindl/lteNS3/blob/master/lte-source/lte-ue-phy.cc [Accessed: 07-Feb-2020].
[6] A. Jame, "Wi-Fi vs. Ethernet: Which Connection to Use?," Ubidots Blog, 11-Dec-2019. [Online]. Available: https://ubidots.com/blog/wi-fi-vs-ethernet-which-connection-to-use/. [Accessed: 09-Feb-2020].
[7] "Whitepaper-Reliable-Video-Streaming-over-Wi-Fi," Ittiam. [Online]. Available: https://www.ittiam.com/resource/reliable-video-streaming-over-wifi-part1/whitepaper-reliable-video-streaming-over-wi-fi/. [Accessed: 10-Feb-2020].
[8] "History"[Online]. Available: https://www.wi-fi.org/who-we-are/history. [Accessed: 09-Feb-2020].

Performance analysis of social media network service using MANET

Abstract: MANET is a type of ad hoc network that can change locations and configure itself on the fly. Because MANETS are mobile, they use wireless connections to connect to various . [7]. The vision for this project is to simulate social networking service using MANET (ad-hoc network) and to analyze it for its performance parameters. For this project, we aim to analyze mobile social networking using MANET wherein traditionally for social networking services utilize infrastructure networking [1]. Traffic data for the social media service will be generated using either Riverbed or ns-3 and additionally Wireshark will also be used.

References:
[1] Stieglitz, S., & Fuchs, C. (2011, August 17). Challenges of MANET for Mobile Social Networks. Retrieved from https://www.sciencedirect.com/science/article/pii/S1877050911004376?fbclid=IwAR1D2OknYazZtzhh_LluW3e9zn1sHT51-f-QyinVEXn9ggKIwr9Wgk59Eew
[2] Rao, Y. C., Kishore, P., & Prasad, S. R. (2019, March). Riverbed Modeler Simulation-Based Performance Analysis of Routing Protocols in Mobile Ad Hoc Networks. Blue Eyes Intelligence Engineering & Sciences Publication.
[3] Joy, J., Chung, E., Yuan, Z., Zou, L., Li, J., & Gerla, M. (2016, May 2). DiscoverFriends: Secure Social Network Communication in Mobile Ad Hoc Networks (pp. 1>
[4] Sanguankotchakorn, T., Shrestha, S., & Sugino, N. (2012, November 21). Effective Ad Hoc Social Networking on OLSR MANET Using Similarity of Interest Approach. Retrieved from https://link.springer.com/chapter/10.1007/978-3-642-34883-9_2?fbclid=IwAR2GIIPoPLNok06uCmGEhc_373mSRnAkzm8u_smZ_rNI0on_-2kyItHkNUw
[5] Sun, X. (2007). Simulation and Analysis of Packets Replication over Multi-Path Routing in MANET. Retrieved from https://community.riverbed.com/servlet/fileField?entityId=ka00b000000l6eqAAA&field=File_Attachment__Body__s&fbclid=IwAR2LEcuGDQl1RyuvqnFlFTfjaF6vSl5eDu9jFCm8Wy3vVA3AAofpti8jzdY
[6] Williams, H. T. P., McMurray, J. R., Kurz, T., & Lambert, F. H. (2015, April 11). Network analysis reveals open forums and echo chambers in social media discussions of climate change. Retrieved from https://www.sciencedirect.com/science/article/pii/S0959378015000369?fbclid=IwAR16xPRf8N8IIk5oED7EcQcqZ9B6nU6zQvqOse1cKR3BwI9MuWVorQRCnng
[7] MANET. Accessed on (2020, February 9). Retrieved from https://techterms.com/definition/manet

WI-FI network design for public transportation system

Abstract:
Nowadays, WIFI has become more and more important in our daily life and people can barely live without it. WIFI, as a great invention of modern society, is bringing a huge convenience to almost everywhere in Canada. However, people in Metro Vancouver are not able to enjoy the benefit from it on public transportation while other countries in Asia had developed it for decades. Hence, the purpose of this report is having a WIFI on public transportation in Metro Vancouver, and we will discuss it through the analysis on improving coverage and performance of wireless network on public transportation.

References:
[1] Usenix.org. (2020). 4th USENIX Symposium on Networked Systems Design & Implementation. [online] Available at: https://www.usenix.org/legacy/event/nsdi07/tech/full_papers/patra/patra_html/ [Accessed 8 Feb. 2020].
[2] P. Fraga-Lamas, T. M. Fernandez-Carames, and L. Castedo, "Towards the Internet of Smart Trains: A Review on Industrial IoT-Connected Railways" Sensors (Basel, Switzerland), 21-Jun-2017. [Online]. Available: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5492363/. [Accessed: 08-Feb-2020].
[3] "British Columbia Ferry Services Inc.," Wi-Fi at BC Ferries | BC Ferries - British Columbia Ferry Services Inc. [Online]. Available: https://www.bcferries.com/about/wireless/. [Accessed: 08-Feb-2020].
[4] "ns-3: src/wifi/examples/wifi-trans-example.cc File Reference," ns. [Online]. Available: https://www.nsnam.org/doxygen/wifi-trans-example_8cc.html. [Accessed: 08-Feb-2020].
[5] "ns-3 tutorial: 6.3 Building a Wireless Network Topology." ns. [Online]. Avail

Simulation of the Netflix video streaming

Abstract:
Netflix and chill tonight? No, but this project will be exploring the technology behind Netflix's video streaming services which bring users a smooth and consistent quality of visual enjoyment by using adaptive bitrate. Ns-3 will be used to simulate Netflix's famous CDN (content delivery network) as well as mimic the buffering and change of bitrate based on the users' network condition.

References:
[1] https://www.researchgate.net/publication/286468923_Buffer-Based_Adaptive_Bitrate_Algorithm_for_Streaming_over_HTTP
[2] http://www.tkn.tu-berlin.de/fileadmin/fg112/Papers/2017/ott17simulation.pdf
[3] http://ns3simulator.com/ns3-video-streaming-projects/
[4] https://www.preseem.com/2018/04/netflix-behavior-wireless-network/
[5] https://openconnect.zendesk.com/hc/en-us/articles/360035569491-Example-router-configurations

Creating a Simulation Model for LEO satellite networks

Abstract:
Low Earth Orbiting (LEO) satellite constellations are an emerging technology for providing global, low-latency broadband Internet services. Companies such as SpaceX, Amazon, OneWeb, and Telesat aim to launch thousands of LEO satellites into space to create mega-constellations to function as communication networks [1] . In our project, we will produce a simulation model for such a LEO satellite network, which will involve the development of a LEO satellite module in ns-3.

References:
[1] P. Gvozdjak, "Modeling communications in low-earth-orbit satellite networks," Ph.D. dissertation, School of Computing Science, Simon Fraser Univ., Burnaby, 2000. Accessed on: Mar. 7, 2020. [Online]. Available: https://www.collectionscanada.gc.ca/obj/s4/f2/dsk1/tape3/PQDD_0011/NQ61647.pdf
[2] J. Deutschmann, K. Hielscher, and R. German, "Satellite Internet performance measurements," in Proc. of the 2019 International Conference on Networked Systems, March, 2019, Garching, Germany [Online]. Available: IEEE Xplore, https://ieeexplore-ieee-org.proxy.lib.sfu.ca/document/8854494. [Accessed: 8 Feb. 2020].
[3] J. Puttonen, S. Rantanen, F. Laakso, J. Kurjenniemi, K. Aho, and G. Acar, "Satellite model for network simulator 3," in Proc. of the 7th International ICST Conference on Simulation Tools and Techniques, March, 2014, Lisbon, Portugal [Online]. Available: ACM Digital Library, https://dl.acm.org/doi/10.4108/icst.simutools.2014.254631. [Accessed: 8 Feb. 2020].
[4] M. Handley, "Delay is not an option: low latency routing in space," in Proc. of the 17th ACM Workshop on Hot Topics in Networks, November, 2018, Washington, USA [Online]. Available: ACM Digital Library, https://dl.acm.org/doi/10.1145/3286062.3286075. [Accessed: 8 Feb. 2020].
[5] Z. Wang, G. Cui, P. Li, W. Wang, and Y. Zhang, "Design and implementation of ns3-based simulation system of LEO satellite constellation for IoTs," in Proc. of 2018 IEEE 4th International Conference on Computer and Communications, December 2018, Chengdu, China [Online]. Available: IEEE Xplore, https://ieeexplore.ieee.org/abstract/document/8781066. [Accessed: 8 Feb. 2020].

Video streaming over LTE network

Abstract:
Nowadays, video streaming is one of the most populated service in mobile internet, accounting for about 50% of total mobile data traffic. This motivates us to perform simulation and analysis of video streaming performance over LTE network. Most popular video streaming services such as YouTube and Netflix use HTTP Adaptive Streaming (HAS). ns-3 is one of the most widely used new models of network simulators due to its rich network library and basic traffic generator models such as on-off traffic model. Thus it satisfies the need for HAS traffic generator framework for mobile networks.

References:
[1] "LTE_(telecommunication)" [Online], Available: https://en.wikipedia.org/wiki/LTE_(telecommunication) [Accessed: February 9, 2020]
[2] William David and Diego Maza, "A Framework for Generating HTTP Adaptive Streaming Traffic in ns-3" [Online], Available: https://hal.archives-ouvertes.fr/hal-01362445/document [Accessed: February 9, 2020]
[3] Mohsen Ansari, "Parallel HTTP for Video Streaming in Wireless Networks" [Online], Available: https://prism.ucalgary.ca/bitstream/handle/11023/3507/ucalgary_2016_ansari_mohsen.pdf;jsessionid=A2C527D36F9CB2CFEEDBB01C61CDCB9B?sequence=3 [Accessed: February 9, 2020]
[4] Wilmar Yesid Campo-Munoza a, Evelio Astaiza-Hoyos a and Luis Freddy Munoz-Sanabria b, "Traffic modelling of the video-on-demand service through NS-3" [Online], Available: http://www.scielo.org.co/pdf/dyna/v84n202/0012-7353-dyna-84-202-00055.pdf [Accessed: February 9, 2020]
[5] Abdurrahman Fouda, Ahmed N. Ragab, Ali Esswie, Mohamed Marzban, Amr Naser, Mohamed Rehan, and Ahmed S. Ibrahim, "Real-Time Video Streaming over NS3-based Emulated LTE Networks" [Online], Available: https://pdfs.semanticscholar.org/f673/97726b320dd6cd2ee7554822c1ce9baa20c2.pdf?_ga=2.217818975.898755008.1581217133-1822197051.1580512233 [Accessed: February 9, 2020]

Simulation of malware attacks in wireless and LAN networks

Abstract:
Malware poses a significant threat to the security of any computer network, and has become more advanced as network security becomes stronger. Using the ns-3 network simulator we will simulate the transmission of a malicious program through a s device to their entire network, both Wireless and LAN. This project will include the efficiency in which the malware can spread to devices sharing a network.victim

References:
[1] A. Ahmad, S. Woodhead, and D. Gan, "The V-network testbed for malware analysis," 2016 International Conference on Advanced Communication Control and Computing Technologies (ICACCCT), 2016.
[2] Bilar and E. Filiol, "On self-reproducing computer programs," Journal in Computer Virology, vol. 5, no. 1, pp.
[3] Eder-Neuhauser, T. Zseby, and J. Fabini, "Malware propagation in smart grid networks: metrics, simulation and comparison of three malware types," Journal of Computer Virology and Hacking Techniques, vol. 15, no. 2, pp. 109-125, 2018.
[4] Jia, J. Liu, Y. Fang, L. Liu, and L. Liu, "Modeling and analyzing malware propagation in social networks with heterogeneous infection rates," Physica A: Statistical Mechanics and its Applications, vol. 507, pp. 240-254, 2018.
[5] E. Karim, A. Walenstein, A. Lakhotia, and L. Parida, "Malware phylogeny generation using permutations of code," Journal in Computer Virology, vol. 1, no.1-2, pp. 13-23, 2005.
[6] Lee, H. Abe, T. Hirotsu, and K. Umemura, "Analysis of Anomalies on a Virtualized Network Testbed," 2010 10th IEEE International Conference on Computer and Information Technology, 2010.

Effects of IoT devices on local Wi-Fi and Ethernet networks' performance

Abstract:
The recent increase of the Internet of Things (IoT) devices and the variety of network requirements of each application has affected the Internet and the local networks such as institutions and houses where these devices are connected. In order to assess the effects of these devices on local networks, this project studies the performance variations on Wi-Fi and Ethernet networks due to the adherence of IoT devices. This is done by means of simulation to observe the possible effects that the amount and variety of IoT devices connected to the network could have on its performance.

References:
[1] P. Lech and P. Wlodarski, "IoT WiFi Home Network Stress Test.," in Image Processing and Communications Challenges 8. IP&C 2016. Advances in Intelligent Systems and Computing, 2016. [2] D. Kauling, M. AlTaei and Q. H. Mahmoud, "Impact of IoT device saturation on home WiFi networks," in Smart Cities Symposium 2018, Bahrain, 2018. [3] Y. Zhuang, T. S. Rappaport, R. McGeer, and J. Cappos, "Future Internet Bandwidth Trends: An Investigation on Current and Future Disruptive Technologies," 2013. [4] G. Armitage, J. Kennedy, S. Nguyen, J. Thomas, and S. Ewing, "Household internet and need for : evaluating the impact of increasingly online lifestyles and the internet of things.," 2017. [5] E. Gupta and P. Kaur, "Comparative Throughput of WiFi and Ethernet LANs using OPNET MODELER," International Journal of Computer Applications, vol. 8, no. 6, 2010.

Title

Abstract:

References: