universiti putra malaysia performance evaluation of …psasir.upm.edu.my/id/eprint/69022/1/fsktm...

UNIVERSITI PUTRA MALAYSIA

PERFORMANCE EVALUATION OF ADAPTIVE FORWARDING STRATEGY USING STOCHASTIC ADAPTIVE FORWARDING (SAF) IN

NAMED DATA NETWORKING

NOR FAIZAH BT JEMANGIN

FSKTM 2018 51

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PERFORMANCE EVALUATION OF ADAPTIVE FORWARDING

STRATEGY USING STOCHASTIC ADAPTIVE FORWARDING (SAF) IN


By


Thesis Submitted to the School of Graduate Studies, Universiti Putra Malaysia,

in Fulfilment of the Requirements for the Master of Computer Science

June 2018

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All material contained within the thesis, including without limitation text, logos,

icons, photographs and all other artworks, is copyright material of Universiti Putra

Malaysia unless otherwise stated. Use may be made of any material contained within

the thesis for non-commercial purposes from the copyright holder. Commercial use

of material may only be made with the express, prior, written permission of

Universiti Putra Malaysia.

Copyright © Universiti Putra Malaysia

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DEDICATIONS

To my beloved husband, Abd. Rashid Ahmad.

Thank you for the support, encouragement and constant love.

Also, to my supervisor, YM Raja Azlina Raja Mahmood

Your encouragement, support, advice and guidance are outline to my achievement.

Finally, thank you to all my family and friends,

Thank you for the support and encouragement.

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Abstract of thesis presented to the Senate of Universiti Putra Malaysia in fulfilment

of the requirement for the Master of Computer Science

PERFORANCE EVALUATION OF ADAPTIVE FORWARDING

STRATEGY USING STOCHASTIC ADAPTIVE FORWARDING (SAF) IN


By


June 2018

Supervisor : YM Raja Azlina Raja Mahmood

Faculty : Computer Science and Information Technology

In current IP-based network, loop is avoided by routing which have an authority in

determining forwarding decision but it prevent efficiency of content dissemination.

As future Internet architecture, NDN gives forwarding plane more authority by using

forwarding strategy to improved Interest satisfaction ratio and cache hit ratio even in

unexpected network status such as link failures. However, there are increased delay

whenever simulation times, link failures or number of clients are increased. A

number of technologies have been deployed in the current Internet infrastructure to

accommodate the new demands for access to content such as Content Distribution

Networks (CDN), Load Balancers, and Cloud Services. Although a lot of effort has

been made to improved IP-based forwarding plane but it is confined to the data

transmission in client-to-server mode or end-to-end. Thus, limiting the adaptability

in the forwarding plane function. Unique characteristic of NDN over IP is the

adaptability of its forwarding plane on choosing the potential outgoing face or

forwarding link when it discovers link failure to achieve quick recovery and manage

congestion by load balancing in multiple links. SAF has been introduced by Posch,

Rainer & Hellwagner in 2017 as new forwarding strategy in NDN to increase the

throughput by using adaptive ability in it. Thus, it gains my interest to study different

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perspective of performance such as delay and Interest retransmission in SAF using

ndnSIM simulator. The result shows that Stochastic Adaptive Forwarding (SAF) is

better than BestRoute in Interest satisfaction ratio by 17.8%, cache hit ratio by 1.8%,

delay by 10.5 seconds and Interest retransmission by 22%. Result also shows

BestRoute outperforms SAF in hop count by 3.2 hops because its aim is to find the

shortest route to the cache or server without evaluating the link performance.

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Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia

sebagai memenuhi keperluan untuk Sarjana Sains Komputer

PENILAIAN PRESTASI STRATEGI MUDAH SUAI PENGHANTARAN

MENGGUNAKAN PENGHANTARAN MUDAH SUAI STOKASTIK (SAF)

DALAM RANGKAIAN DATA YANG DINAMAKAN

Oleh


Jun 2018

Penyelia : YM Raja Azlina Raja Mahmood

Fakulti : Sains Komputer dan Teknologi Maklumat

Dalam rangkaian semasa yang berasaskan IP, putaran berulang dielakkan oleh

penghalaan yang mempunyai kuasa dalam menentukan keputusan penghantaran

tetapi ia menghalang kecekapan penyebaran kandungan. Sebagai seni bina Internet

untuk masa akan datang, NDN memberi pemproses penghantaran lebih kuasa dengan

menggunakan strategi penghantaran bagi mencapai nisbah kepuasan Minat dengan

lebih baik dan nisbah jumpa simpanan walau dalam keadaan rangkaian yang tidak

diduga seperti kegagalan tautan. Walau bagaimanapun, terdapat kenaikan kelewatan

apabila masa simulasi, kegagalan tautan atau bilangan pelanggan dinaikkan.

Sebilangan teknologi telah dilaksanakan di dalam infrastruktur Internet semasa untuk

menampung permintaan yang baru bagi capaian kepada kandungan di rangkaian

pengedaran kandungan (CDN), pengimbang beban dan perkhidmatan awan.

Walaupun banyak usaha telah dibuat untuk menambahbaik penghantaran berasaskan

IP tetapi ia terhad kepada penghantaran data pelanggan-pelayan atau hujung-ke-

hujung. Oleh itu, menghadkan keupayaan penyesuaian diri di dalam fungsi tersebut.

Ciri-ciri unik NDN berbanding IP adalah keupayaan menyesuaikan diri dengan

menggunakan pemproses penghantaran untuk memilih antaramuka keluar atau laluan

penghantaran yang berpotensi apabila ia bertemu laluan yang gagal bagi mencapai

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pemulihan yang cepat dan menguruskan kesesakan dengan mengimbangi beban di

beberapa laluan keluar. SAF telah diperkenalkan oleh Posch, Rainer & Hellwagner

pada 2017 sebagai strategi penghantaran yang baru dalam NDN untuk meningkatkan

daya pemprosesan dengan menggunakan keupayaan adaptif di dalamnya. Justeru,

saya berminat untuk belajar berkenaan prestasi dari sudut perspektif lain seperti

kelewatan dan penghantaran semula Minat dalam SAF menggunakan pensimulasi

ndnSIM. Keputusan menunjukkan yang Penghantaran Adaptif Stokastik (SAF) lebih

baik daripada LaluanTerbaik dalam nisbah kepuasan Minat sebanyak 17.8%, nisbah

jumpa simpanan sebanyak 1.8%, kelewatan sebanyak 10.5 saat dan penghantaran

semula Minat sebanyak 22%. Keputusan juga menunjukkan LaluanTerbaik

mengatasi SAF dalam bilangan lompatan sebanyak 3.2 lompatan kerana kaedahnya

hanya memilih jalan terpendek kepada tempat simpanan atau pelayan tanpa menilai

prestasi talian.

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ACKNOWLEDGEMENTS

I would like to thank the author of SAF, Mr. Daniel Posch who had provided the

simulation program in https://github.com/danposch/ for me to explore and completed

this project. He also responses my email even though we never know each other

before.

Again, I need to acknowledge for the second time in this report to my supervisor YM

Raja Azlina for her guidance. She guided me a lot and also allow me to participate

in her Python class for Bachelor Degree class. She deserves to be one of the best

postgraduate supervisors in UPM.

Also, thank you for my assessor, Encik Mohd. Noor Derahman for his constructive

comments during project proposal and project report presentation.

Lastly to all my lecturers during my master studies who always encourage research

effort among students and share their experience and knowledge to inspired us.

May Allah blessed all of you. Ameen.

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APPROVAL

This thesis submitted to the Faculty of Computer Science and Information

Technology of Universiti Putra Malaysia and has been accepted as fulfilment of the

requirements for the degree of Master of Computer Science (Distributed Computing).

_______________________________

YM RAJA AZLINA RAJA

MAHMOOD

Senior Lecturer

Department of Network and

Communication Technology Department

Faculty of Computer Science and

Information Technology

Universiti Putra Malaysia

Date:

___________________________

Accepted and approved by,

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DECLARATION BY GRADUATE STUDENT

I hereby confirm that:

• this thesis is my original work;

• quotations, illustrations and citations have been duly referenced;

• this thesis has not been submitted previously or concurrently for any other degree at any other institutions;

• intellectual property from the thesis and copyright of thesis are fully-owned by Universiti Putra Malaysia, as according to the Universiti Putra Malaysia

(Research) Rules 2012;

• written permission must be obtained from supervisor and the office of Deputy Vice-Chancellor (Research and Innovation) before thesis is published (in the

form of written, printed or in electronic form) including books, journals,

modules, proceedings, popular writings, seminar papers, manuscripts, posters,

reports, lecture notes, learning modules or any other materials as stated in the

Universiti Putra Malaysia (Research) Rules 2012;

• there is no plagiarism or data falsification/fabrication in the thesis, and scholarly integrity is upheld as according to the Universiti Putra Malaysia (Graduate

Studies) Rules 2003 (Revision 2012-2013) and the Universiti Putra Malaysia

(Research) Rules 2012. The thesis has undergone plagiarism detection software.

Signature: ________________________ Date: __________________

Name and Matric No.: Nor Faizah bt Jemangin (GS48106)

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TABLE OF CONTENTS

Page DEDICATIONS ................................................................................................................... iii

ACKNOWLEDGEMENTS ............................................................................................... viii

APPROVAL ........................................................................................................................ ix

TABLE OF CONTENTS ..................................................................................................... xi

LIST OF TABLES ............................................................................................................. xiv

LIST OF FIGURES ............................................................................................................ xv

LIST OF ABBREVIATIONS ........................................................................................... xvii

CHAPTER 1 ............................................................................................................. 1

INTRODUCTION ..................................................................................................... 1

1.1 Background .............................................................................................................. 1

1.2 Problem Statement ................................................................................................... 5

1.3 Research Objectives ................................................................................................. 5

1.4 Research Scope ........................................................................................................ 6

CHAPTER 2 ............................................................................................................. 7

LITERATURE REVIEW .......................................................................................... 7

2.1 Introduction .............................................................................................................. 7

2.2 Related Works ........................................................................................................ 10

2.3 SAF Detail Review ................................................................................................ 18

CHAPTER 3 ........................................................................................................... 20

METHODOLOGY .................................................................................................. 20

3.1 Literature Review ................................................................................................... 20

3.2 Simulation .............................................................................................................. 20

3.2.1 Hardware and Software Requirement .................................................................... 20

3.2.2 A Brief of ndnSIM Simulator ................................................................................ 22

3.2.3 Simulation Parameter ............................................................................................. 23

3.2.4 Project Limitation and Challenges ......................................................................... 25

3.2.5 ndnSIM Simulator Installation to Prepare Project Environment ........................... 26

3.3 Performance Metrics .............................................................................................. 30

3.3.1 Interest Satisfaction Ratio ...................................................................................... 30

3.3.2 Cache Hit Ratio ...................................................................................................... 30

3.3.3 Average Hop count ................................................................................................ 31

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3.3.4 Average Delay ....................................................................................................... 31

3.3.5 Average Interest Retransmission ........................................................................... 31

CHAPTER 4 ........................................................................................................... 32

DESIGN AND IMPLEMENTATION ....................................................................... 32

4.1 Topology Model ..................................................................................................... 32

4.2 Topology Architecture ........................................................................................... 34

4.3 Scenario.................................................................................................................. 35

4.4 Process Flow .......................................................................................................... 36

4.5 Testing Commands ................................................................................................ 39

4.6 Generating the Results ........................................................................................... 40

CHAPTER 5 ........................................................................................................... 42

RESULT AND DISCUSSION .................................................................................. 42

5.1 Introduction ............................................................................................................ 42

5.2 Scenario 1: Different Number of Simulation Time (In Minutes)........................... 42

5.2.1 Average Interest Satisfaction Ratio ........................................................................ 42

5.2.2 Average Cache Hit Ratio ....................................................................................... 43

5.2.3 Average Hop Count ............................................................................................... 44

5.2.4 Average Delay ....................................................................................................... 44

5.2.5 Average Retransmission ........................................................................................ 45

5.3 Scenario 2: Different Number of Link Failures ..................................................... 46




5.3.4 Average Delay ....................................................................................................... 50


5.4 Comparison Between Scenario 3: Different Number of Clients And 10 Servers and

Scenario 4: Different Number of Clients and Servers ........................................... 51




5.4.4 Average Delay ....................................................................................................... 55


CHAPTER 6 ........................................................................................................... 57

CONCLUSION AND FUTURE WORK ................................................................... 57

6.1 Conclusion ............................................................................................................. 57

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6.2 Future Works ......................................................................................................... 58

REFERENCES ....................................................................................................... 59

BIODATA OF STUDENT ....................................................................................... 62

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LIST OF TABLES

Page

Table 1: Differences of IP, Path Slicing and NDN 7

Table 2: Summary of Different Research Areas Covered in NDN Forwarding

Strategy 11

Table 3: The Actual Parameter from Posch et. al (2017) 23

Table 4: The Project Parameter 24

Table 5: Bandwidth and Connectivity Parameter Setting 34

Table 6: Scenarios of This Project 35

Table 7: Detail of Trace Files and Related Metrics 40

Table 8: Python Program to Run the Simulation and Generate Performance Metrics

41

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LIST OF FIGURES

Page

Figure 1: IP vs NDN ......................................................................................... 1

Figure 2: How Data Gets Distributed Over IP-CDN Architectures ......................... 2

Figure 3: How Data Gets Distributed Over NDN Architectures. ............................ 2

Figure 4: Interest and Data Processing In NDN .................................................... 9

Figure 5: The NDN Model Using SAF .............................................................. 18

Figure 6: Algorithm 1 in SAF. ......................................................................... 19

Figure 7: Algorithm 2 in SAF .......................................................................... 19

Figure 8: Structure of Hardware And Software Requirement ............................... 21

Figure 9: My Current Computer Specification Model Lenovo Ideapad MIIX 510 .. 21

Figure 10: Oracle VM VirtualBox setting.......................................................... 22

Figure 11: ndnSIM Component ........................................................................ 23

Figure 12: Pre-compile Library for ndnSIM ...................................................... 26

Figure 13: BRITE Installation .......................................................................... 27

Figure 14: Fetch the Code Repositories for ndn-cxx, ndnSIM, itec-ndn ................ 28

Figure 15: Build and Install ndn-cxx ................................................................. 28

Figure 16: Build and Install Ns-3 With The ndnSIM and the BRITE plugin .......... 29

Figure 17: Build SAF Scenarios In itec-ndn Folder ............................................ 29

Figure 18: Cache Hit vs Cache Miss ................................................................. 31

Figure 19: Random Network vs Scale-Free Network .......................................... 32

Figure 20: Different of Poisson Distribution and Power Law Distribution............. 33

Figure 21 : SAF Topology of Medium Connectivity ........................................... 33

Figure 22 : Topology Architecture .................................................................... 34

Figure 23 : Process Flow for Select Outgoing Face for An Interest ...................... 37

Figure 24 : Process Flow for Forwarding Table In SAF ...................................... 38

Figure 25 : Interest Satisfaction Ratio for Different Simulation Time ................... 43

Figure 26 : Cache Hit Ratio for Different Simulation Time ................................. 43

Figure 27 : Hop Count for Different Simulation Time ........................................ 44

Figure 28 : Delay for Different Simulation Time ................................................ 45

Figure 29 : Interest Retransmission for Different Simulation Time ....................... 45

Figure 30 : Interest Satisfaction Ratio for Different Link Failures ........................ 46

Figure 31 : Interest Satisfaction Ratio for Different Link Failures ........................ 47

Figure 32: Cache Hit Ratio for Different Link Failure ........................................ 47

Figure 33: Cache Hit Ratio For 0 Link Failure ................................................... 48

Figure 34: Hop Count for Different Link Failure ................................................ 49

Figure 35: Hop Count for 0 Link Failure ........................................................... 49

Figure 36: Delay for Different Link Failure ....................................................... 50

Figure 37: Interest Retransmission for Different Link Failures ............................ 50

Figure 38: Average Interest Satisfaction Ratio for Different Number of Clients And

10 Servers ............................................................................................... 52

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Figure 39: Average Interest Satisfaction Ratio for Different Number of Clients and

Servers.................................................................................................... 52

Figure 40: Average Cache Hit Ratio for Different Number of Clients And 10 Servers

.............................................................................................................. 53

Figure 41: Average Cache Hit Ratio for Different Number of Clients and Servers . 53

Figure 42: Average Hop Count for Different Number of Clients and 10 Servers .... 54

Figure 43: Average Hop Count for Different Number of Clients and Servers ........ 54

Figure 44: Average Delay for Different Number of Clients and 10 Servers ........... 55

Figure 45: Average Delay for Different Number of Clients and Servers ............... 55

Figure 46: Average Retransmission for Different Number of Clients And 10 Servers

.............................................................................................................. 56

Figure 47: Average Retransmission for Different Number of Clients And Servers . 56

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LIST OF ABBREVIATIONS

Abbreviations Meaning

AS Autonomous System

CDN Content Delivery Network

CS Content Store

FIB Forwarding Information Base

ICN Information Centric Network

IP Internet Protocol

ISP Internet Service Provider

LAN Local Area Network

LFU Least Frequently Used

FIFO First In First Out

LRU Least Recently Used

NDN Named Data Networking

PIT Pending Interest Table

RAM Random-Access Memory

TCP/IP Transmission Control Protocol/Internet Protocol

WAN Wide Area Network

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1

CHAPTER 1

INTRODUCTION

1.1 Background

It is all started when Van Jacobson presenting “A New Way to look at Networking”

in Google Tech Talk in 2006. This talk introduce a new paradigm of moving the

Internet toward a content distribution architecture (“NDN Frequently Asked

Questions (FAQ) - Named Data Networking (NDN),” n.d.). In this event, Jacobson

had defined ICN as to remove IP address which currently used in Internet

communication.

In short, IP is end to end host communication and centred around host

address while NDN is focusing on data content names instead of end to end host.

This requirement has translated from “where is the server hosting my data?” to

“where is my data?” (Aloulou, Ayari, Zhani, Saidane, & Pujolle, 2017) as in Figure 1

taken from http://comnet.ieee.tn/wp-content/uploads/2017/05/Comnet2017_Final.pdf

Figure 1: IP vs NDN

Retrieved from http://comnet.ieee.tn/wp-

content/uploads/2017/05/Comnet2017_Final.pdf

(Source: Aloulou, Ayari, Zhani, Saidane, & Pujolle, 2017)

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2

In the same reference as above, a lot of effort has been made to improve the

content delivery performance in current IP infrastructure such as using Content

Delivery Network (CDN). Although CDN is an effective solution to date but it is not

able to optimized the bandwidth usage in local area network (LAN) or in wide area

network (WAN), as the data is located in the region data centre. Thus, it has the

potential to increase the risk of bottleneck in the network gateways. That is all nodes

need to go to the endpoint of the CDN if they want to access the same content.

Figure 2 and Figure 3 illustrate how data gets distributed over the IP-based (CDN)

and NDN architectures respectively.

Figure 2: How Data Gets Distributed Over IP-CDN Architectures

Retrieved from http://mustafacanturk.com/named-data-networking/

(Source: Mustafacanturk, 2015)

Figure 3: How Data Gets Distributed Over NDN Architectures.

Retrieved from http://mustafacanturk.com/named-data-networking/

(Source: Mustafacanturk, 2015)

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3

Further, the role of Internet is increasing with the demand of Internet of

Things (IoT). According to Shang, Yu, Droms and Zhang (2016) the TCP/IP is not

suitable to handle IoT environment because it is not effective and efficient as

compared to NDN architecture. Cisco forecasted that global IP traffic in 2021 will

be equivalent to 127 times the volume of the entire global IP traffic in 2005 (“Cisco

Visual Networking Index: Forecast and Methodology, 2016–2021 - Cisco,” 2017).

Content Delivery Network (CDN) traffic will carry 71 percent of all Internet traffic

by 2021 in the same forecast report. Named data networking (NDN) is a promising

approach to address the needs of improving content delivery, handling IoT

environment and increasing volume of Internet traffic as it is expected to be future of

Internet architecture. Instead of sending packets between client and server devices

identified by numeric IP addresses in IP network, in NDN the network will send

Interest in the form of desired data name without specifying where the data may be

located. Routers may satisfy the Interests from router caches, other nodes or original

data producer. This will increase user experience in using Internet and lowering cost

of service provider who owned the original data producer by reducing number of

servers and the amount of bandwidth needed at their datacentre.

According to Yi, Abraham, Afanasyev, Wang, Zhang & Zhang (2014), IP

networks make routing as a brain of activity, such as spreads policy information and

topology, discovers and recovers from network failures, calculate route meanwhile

the data plane only forwards packets based on the Forward Information Based (FIB).

However, NDN forwarding react differently which it has adaptive forwarding to

handle further changes in network once the above activities have been implemented

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4

without the need to refer back to the routing information. Routing information in

NDN only used during first time and for any long-term network changes.

Although a lot of effort has been made to improved IP-based forwarding

plane but it is confined to the data transmission in end-to-end or client-to-server

mode. Thus, limiting the adaptability in the forwarding plane (Cao et al., 2016).

The forwarding strategy is crucial to the robustness and effectiveness of

Named Data Networking (NDN) (Lei, Wang, & Yuan, 2015) and (Cao et al., 2016).

The spread of NDN’s local caching is an advantage in decreasing duplication of

content transmission. However, the behaviour of cached items which can volatile in

certain condition calls for an effective and efficient forwarding strategy to

significantly improved the performance of data delivery (Yao, Yin, Tan, & Jiang,

2017).

There are two types of forwarding strategies. An adaptive forwarding

strategy learns current network status through it face(s) or interfaces to improve

future decisions. A static forwarding strategy only relies on the decisions made by

the routing protocol and unable to adapt with network changes unless it removes the

unperformed face in forwarding information base (FIB) (Ben Abraham, Crowley, &

Abraham, 2016).

I have chosen an anchor paper wrote by Posch, Rainer & Hellwagner (2017)

about Stochastic Adaptive Forwarding (SAF) in Named Data Networking. It has

been published in IEEE Transaction on Networking in April 2017. SAF is focuses to

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5

improved throughput or Interest satisfaction ratio by evaluating the interface

performance and diverting Interest to another reliable interface if the current

interface become unreliable.

1.2 Problem Statement

In current IP-based network, loop-free can be achieved by routing which have an

authority in determining forwarding decision but it prevent efficiency of content

dissemination. As future Internet architecture, there have been several researches

effort pertaining forwarding strategies in NDN to increase any relevant performance.

These include SAF that studied such as Interest satisfaction ratio, cache hit ratio and

hop count (Posch, Rainer, & Hellwagner, 2017). However, their work does not

evaluate delay and Interest retransmission in different simulation time, different link

failures, different number of clients and different number of servers.

1.3 Research Objectives

The aim of this project is to evaluate the performance of stochastic adaptive

forwarding (SAF) and comparing it with the BestRoute algorithm in terms of delay

and Interest retransmission in different simulation time, different link failures,

different number of clients and different number of servers. The project will also

evaluate and verify the performance of the two algorithms in terms of Interest

satisfaction ratio, cache hit ratio and hop count in the said scenarios.

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6

1.4 Research Scope

This project focuses on evaluating the performance of SAF approach as compared to

the current forwarding strategy available in ndnSIM such as BestRoute in NDN. The

studied performance parameters are delay, Interest retransmission, Interest

satisfaction ratio, cache hit ratio and hop count.

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59

REFERENCES

Mustafacanturk. (2015). Named Data Networking. Retrieved from

http://mustafacanturk.com/named-data-networking/, January 2015.

Afanasyev, A., Mastorakis, S., Moiseenko, I., & Zhang, L., (2017)

http://ndnsim.net/current/intro.html.

Shang, W., Yu, Y., Droms, R., & Zhang, L. (2016). Challenges in IoT Networking

via TCP/IP Architecture. NDN. Retrieved from http://named-

data.net/techreports.html

Yi, C., Afanasyev, A., Moiseenko, I., Wang, L., Zhang, B. & Zhang, L. (2013). A

case for stateful forwarding plane, Comput. Commun., vol. 36, no. 7, pp.

779–791.

Posch, D., Rainer, B. & Hellwagner, H. (2017). SAF: Stochastic Adaptive

Forwarding in Named Data Networking. IEEE/ACM Transactions on

Networking, Vol. 25, No. 2.

D. Nguyen, M. Fukushima, K. Sugiyama, and A. Tagami, ‘Efficient multipath

forwarding and congestion control without route-labeling in CCN’, in

Communication Workshop (ICCW), 2015 IEEE International Conference

on, 2015, pp. 1533–1538.

K. Schneider, C. Yi, B. Zhang, and L. Zhang, ‘A Practical Congestion Control

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Conference on Information-Centric Networking, New York, NY, USA,

2016, pp. 21–30.

Ilya Moiseenko Alexander Afanasyev and Lixia Zhang. ndnsim: Ndn simulator for

ns-3. In NDN, Technical Report NDN-0005, 2012.Revision 2: October 5,

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Yi, C. (2014). Adaptive Forwarding in Named Data Networking (Doctoral thesis,

University of Arizona). Retrieved from

https://www2.cs.arizona.edu/~yic/paper/dissertation.pdf

Posch, D. (2016). Towards Effective Multimedia Dissemination in Information-

Centric Networks (Doctoral thesis, Alpen Adria University at Klagenfurt,

Austria). Retrieved from http://www-itec.uni-

klu.ac.at/bib/files/posch_thesis.pdf

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portal.org/smash/get/diva2:1039090/FULLTEXT01.pdf

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Yi, C., Abraham, J., Afanasyev, A., Wang, L., Zhang, B. & Zhang, L. (2014). On

the role of routing in named data networking,” in Proc. 1st Int. Conf. Inf.

Centric Netw., pp. 27–36.

Shi, J. & Liang, T (2018). NFD forwarding pipelines. Retrieved April 2018 from

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from http://book.varnish-software.com/4.0/chapters/HTTP.html.

Afanasyev, A. (2017). [ndnSIM] error while loading shared libraries: libns3-dev-

brite-optimized.so. Retrieved July 6, 2018, from

http://www.lists.cs.ucla.edu/pipermail/ndnsim/2017-October/004256.html

Alexander Afanasyev, Spyridon Mastorakis, Ilya Moiseenko, and L. Z. (2017).

ndnSIM Documentation — ndnSIM documentation. Retrieved July 17, 2018,

from http://ndnsim.net/2.5/

Aloulou, N., Ayari, M., Zhani, M. F., Saidane, L., & Pujolle, G. (2017). Taxonomy

and comparative study of NDN forwarding strategies. In 2017 Sixth

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