An Efficient Routing Protocol for Energy Management in WSN-Assisted loT Sarah Ammar Rafea and Abdulkareem A. Kadhim.

Slides:



Advertisements
Similar presentations
Advanced Computer Networks Fall 2011
Advertisements

Low-Power Interoperability for the IPv6 Internet of Things Presenter - Bob Kinicki Low-Power Interoperability for the IPv6 Internet of Things Adam Dunkels,
6LoWPAN Extending IP to Low-Power WPAN 1 By: Shadi Janansefat CS441 Dr. Kemal Akkaya Fall 2011.
Multicast in Wireless Mesh Network Xuan (William) Zhang Xun Shi.
Kyung Tae Kim, Hee Yong Youn (Sungkyunkwan University)
PORT: A Price-Oriented Reliable Transport Protocol for Wireless Sensor Networks Yangfan Zhou, Michael. R. Lyu, Jiangchuan Liu † and Hui Wang The Chinese.
Leveraging IP for Sensor Network Deployment Simon Duquennoy, Niklas Wirstrom, Nicolas Tsiftes, Adam Dunkels Swedish Institute of Computer Science Presenter.
1-1 CMPE 259 Sensor Networks Katia Obraczka Winter 2005 Transport Protocols.
NCKU CSIE CIAL1 Principles and Protocols for Power Control in Wireless Ad Hoc Networks Authors: Vikas Kawadia and P. R. Kumar Publisher: IEEE JOURNAL ON.
Taming the Underlying Challenges of Reliable Multihop Routing in Sensor Networks.
Adaptive Self-Configuring Sensor Network Topologies ns-2 simulation & performance analysis Zhenghua Fu Ben Greenstein Petros Zerfos.
DAC: Distributed Asynchronous Cooperation for Wireless Relay Networks 1 Xinyu Zhang, Kang G. Shin University of Michigan.
Empirical Analysis of Transmission Power Control Algorithms for Wireless Sensor Networks CENTS Retreat – May 26, 2005 Jaein Jeong (1), David Culler (1),
FBRT: A Feedback-Based Reliable Transport Protocol for Wireless Sensor Networks Yangfan Zhou November, 2004 Supervisors: Dr. Michael Lyu and Dr. Jiangchuan.
1 Minimizing End-to-End Delay: A Novel Routing Metric for Multi- Radio Wireless Mesh Networks Hongkun Li, Yu Cheng, Chi Zhou Department of Electrical and.
Yanyan Yang, Yunhuai Liu, and Lionel M. Ni Department of Computer Science and Engineering, Hong Kong University of Science and Technology IEEE MASS 2009.
IETF-76, Hiroshima, Nov 2009 ROLL Working Group Meeting IETF-76, Nov 2009, Hiroshima Routing Metrics used for Path Calculation in Low Power and Lossy Networks.
Impact of the Internet of Things on Computer Networks James Byars December 12, 2013 IT422 – Computer Networks Professor Tim Johnson.
Results Introduction Increased interest in real-word applications in industrial automation, smart home, smart building and smart-cities will result in.
A Simple and Effective Cross Layer Networking System for Mobile Ad Hoc Networks Wing Ho Yuen, Heung-no Lee and Timothy Andersen.
CSE 6590 Fall 2010 Routing Metrics for Wireless Mesh Networks 1 4 October, 2015.
Adaptive Tree-based Convergecast Protocol CS 234 Project - Anirudh Ramesh Iyer, Swaroop Kashyap Tiptur Srinivasa, Tameem Anwar Guide - Prof. Nalini Venkatasubramanian,
KTH Royal Institute of Technology.  Background  Problem  Goals  Communication Protocols  Proposed Solutions  Experiments  Data & Conclusions 
Advanced Computer Networks Fall 2013
Cross-layer Packet Size Optimization for Wireless Terrestrial, Underwater, and Underground Sensor Networks IEEE INFOCOM 2008 Mehmet C. Vuran and Ian F.
Energy-Efficient Shortest Path Self-Stabilizing Multicast Protocol for Mobile Ad Hoc Networks Ganesh Sridharan
CSE 6590 Fall 2009 Routing Metrics for Wireless Mesh Networks 1 12 November, 2015.
Bounded relay hop mobile data gathering in wireless sensor networks
SenProbe: Path Capacity Estimation in Wireless Sensor Networks Tony Sun, Ling-Jyh Chen, Guang Yang M. Y. Sanadidi, Mario Gerla.
RPL:IPv6 Routing Protocol for Low Power and Lossy Networks Speaker: Chung-Yi Chao Advisor: Dr. Kai-Wei Ke 2015/10/08 1.
Slide #1 Performance Evaluation of Routing Protocol for Low Power and Lossy Networks (RPL) draft-tripathi-roll-rpl-simulation-04 IETF Virtual Interim WG.
Speaker: Chia-Wen Lu (Sally) Adviser: Dr. Quincy Wu Date:02/23/2012
Speaker: Yi-Lei Chang Advisor: Dr. Kai-Wei Ke 2012/05/15 IPv6-based wireless sensor network 1.
Fast and Reliable Route Discovery Protocol Considering Mobility in Multihop Cellular Networks Hyun-Ho Choi and Dong-Ho Cho Wireless Pervasive Computing,
Tufts Wireless Laboratory School Of Engineering Tufts University Paper Review “An Energy Efficient Multipath Routing Protocol for Wireless Sensor Networks”,
Design of energy-efficient routing protocol in multicast ad-hoc mobile networks using directional antennas J. seetaram, Assoc.prof., Sree chaitanya college.
ICACT 2012 Performance Study on SNMP and SIP over SCTP in Wireless Sensor Networks Advisor: Quincy Wu Speaker: Chia-Wen Lu (Sally) National Chi Nan University.
TempLab : A Testbed to Study the Impact of Temperature on Wireless Sensor Networks C.A. Boanoy, M.A. Zúñiga, J. Brownz, U. Roedigz, C. Keppitiyagama§,
Internet of Things Fall 2015
Bing Wang, Wei Wei, Hieu Dinh, Wei Zeng, Krishna R. Pattipati (Fellow IEEE) IEEE Transactions on Mobile Computing, March 2012.
Toward Reliable and Efficient Reporting in Wireless Sensor Networks Authors: Fatma Bouabdallah Nizar Bouabdallah Raouf Boutaba.
Abstract 1/2 Wireless Sensor Networks (WSNs) having limited power resource report sensed data to the Base Station (BS) that requires high energy usage.
On Mobile Sink Node for Target Tracking in Wireless Sensor Networks Thanh Hai Trinh and Hee Yong Youn Pervasive Computing and Communications Workshops(PerComW'07)
Efficient Geographic Routing in Multihop Wireless Networks Seungjoon Lee*, Bobby Bhattacharjee*, and Suman Banerjee** *Department of Computer Science University.
-1/16- Maximum Battery Life Routing to Support Ubiquitous Mobile Computing in Wireless Ad Hoc Networks C.-K. Toh, Georgia Institute of Technology IEEE.
Low-Power Interoperability for the IPv6 Internet of Things Presenter - Bob Kinicki Low-Power Interoperability for the IPv6 Internet of Things Adam Dunkels,
Reporter: Hung-Wei Liu Advisor: Tsung-Hung Lin 1.
Authors: Christos Stergiou Andreas P. Plageras Kostas E. Psannis
ABSTRACT Problem Statement: The main aim of this thesis work is to investigate the performance of real-time voice traffic in IP networks and MPLS networks.
Routing Metrics for Wireless Mesh Networks
Internet of Things Amr El Mougy Alaa Gohar.
Enabling QoS Multipath Routing Protocol for Wireless Sensor Networks
Wireless Sensor Networks 6. WSN Routing
Routing Metrics for Wireless Mesh Networks
Performance analysis of an IP based protocol stack for WSNs
AODV-OLSR Scalable Ad hoc Routing
Energy Constrained Routing Algorithm for Wireless Networks
Bhavish Aggarwal Guide: Prof. Bhaskaran Raman
Presented by: Rohit Rangera
Trusted Routing in IoT Dr Ivana Tomić In collaboration with:
Algorithms for Big Data Delivery over the Internet of Things
Routing Metrics for Wireless Mesh Networks
A New Multipath Routing Protocol for Ad Hoc Wireless Networks
Ekereuke Udoh Distributed and Intelligent Systems Research Group
ECE453 – Introduction to Computer Networks
Speaker:Chen-Yu Tseng Advisor : Dr. Ho-Ting, Wu
The Impact of Multihop Wireless Channel on TCP Performance
Tony Sun, Guang Yang, Ling-Jyh Chen, M. Y. Sanadidi, Mario Gerla
<month year> <doc.: IEEE doc> January 2013
Hongchao Zhou, Xiaohong Guan, Chengjie Wu
Presentation transcript:

An Efficient Routing Protocol for Energy Management in WSN-Assisted loT Sarah Ammar Rafea and Abdulkareem A. Kadhim

Content Background Problem Definition Aim of the work Methodology Publication References Results Thesis contribution Conclusion Futur work

Background IoT

What is IOT? Its a technology that enable the intelligent objects (things) to collect and exchange data through the internet for different purposes Things refer to any physical object with a device that has its own IP address and can connect to a network that also sends/receives data via network

WSN & IoT 04 Internet of Things (IoT) system is observed to have the potential to improve the overall efficiency of many applications. WSNs distribute hundreds to thousands of inexpensive micro-sensor nodes in their areas, and these nodes are fundamental parts of IoT.

WSN Node Small Devices Communicating Node Low Cost Low Power Sensing Processing Energy Consumption

Connecting WSN to the Internet There are three main approaches to connect WSN to the Internet Single Gateway Multiple Gateway Direct Access Inflexible Delay

IoT- WSN Protocol stack Application layer Transport layer Network layer Link layer physical layer

Routing Protocol LEACH RPL LEACH Internet Engineering Task Force (IETF) Proactive routing protocol IPv6 based protocol Tree-like topology (DODAG) Used different Objective Functions

Routing Protocol for Low Power and Lossy Network (RPL) DODAG Information Object DODAG Information Solicitation DODAG Advertisement Object DAO-ACKnologment RPL Control messages DIO DIS DAO DAO- ACK Rank=0 Rank=1 Rank=2 Rank=3 Rank=2

Route Selection in RPL Objective Function (OF) Objective Function Zero (OF0) Minimum Rank with Hysteresis Objective Function (MRHOF) Hop count metric Expected Transmission count (ETX) Routing Metrics Node Metric Link Metric Hop and residual energy Throughput, latency and link reliability

Related Works Hop count or Expected Transmission count (ETX) Objective Function Hop Count & Residual Energy Objective Function Node energy & power & link qual ity & success tran smission data rat e & congestion de tection factor New Metric Expected Transmi ssion Count (ETX ) & Received Sig nal Strength Indic ator (RSSI) Objective function RPL ELB- FLR LCI Tx- tuned 2018 Delay & Energy Objective function OFQS

Problem definition ?

Problem Definition In WSN assisted IoT (IP over WSN) the resources are constrained in many ways: Energy resources storage resources computing resources

Problem Definition (cont..) The routing protocol for low power and lossy network (RPL) is the most common protocols used for WSN assisted IOT. The Objective function of RPL protocol depend s on either: link quality hop count There is no consideration to energy metric

Problem Definition (cont..) Node-4 will not switch its preferred parent Hop count ETX Bad link quality for path from node-5 through node-3 Node-4 will not switch its preferred parent Select 3 hops with 3 ETX rather than 2 hops with 3.5 ETX

Aim of the work

Propose a new energy-efficient routing protocol for WSN assisted loT based on RPL to improve the performance of the network by reducing the required energy. modify RPL routing protocol to work in energy efficient way by taking into consideration the energy metric with link quality metric.

Thesis contribution

Running the RPL protocol on Cooja simulator. The proposal of two modified versions of RPL protocols called ETRPL and EERPL aiming to improve the IoT-WSN network performance. Implementing the proposed protocols in Cooja simulator As a result of implementing the proposed protocols, better performance is achieved compared to RPL protocol. 04

Methodology

Using Contiki OS which is one of most widely used operating system for WSN supporting IoT. Using Cooja simulator which is the most important tool in Contiki OS used to simulate & emulate WSN. Implement the proposed protocols and compare it with the existing protocols.

Methodology ETX and remaining energy (ETRPL) - Node-4 will switch its preferred parent ETX and consumed energy (EERPL) - Not select old preferred parent - Create new metric (EE) based on summation of ETX and energy consumption - Node 5 change its parent in case when energy consumption became 95% since the path cost will be ( =15). - Based on remaining energy of preferred parent

Results

Infographic Style Remaining Energy Packet Delivery Ratio Average Time Delay Number of Dead Nodes The main parameters Evaluation Method

Main Assumptions ParameterSpecification or Value TopologyRandom Area 100mX100m 150mX150m 200mX200m Number of nodes20, 40 and 80 Simulation time60 Mins. Transmission range50m Interference range70m and without int.

Remaining Energy Results Without interference range With interference range for 20 nodes AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m mX150m mX200m AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m mX150m mX200m

Remaining Energy Results for 40 nodes AreaRPLETRPL 25%ETRPL 50%ETRPL 75% EERPL 100mX100m mX150m mX200m AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m mX150m mX200m Without interference range With interference range

Remaining Energy Results for 80 nodes AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m mX150m mX200m AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m mX150m mX200m Without interference range With interference range

Packet Delivery Ratio Results for 20 nodes AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m99.72%100% 150mX150m99.54%99.64%99.55%99.64% 200mX200m98.98%99.36%99.54%98.26%98.82% AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m99.54%100% mX150m99.54%99.64%99.73%99.64% 200mX200m98.14%98.52%97.96%97.88%98.73% Without interference range With interference range

Packet Delivery Ratio Results for 40 nodes AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m98.74%99.6%99.69%99.28%99.56% 150mX150m97.39%99.5%98.73%98.77%99.73% 200mX200m96.42%98.02%97.83%97.62%98.12% AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m98.47%99.78%99.6%99.243%99.6% 150mX150m96.94%98.77%98.817%98.511%98.65% 200mX200m94.99%97.74%98.086%97.318%96.17% Without interference range With interference range

Packet Delivery Ratio Results for 80 nodes AreaRPLETRPL 25%ETRPL 50%ETRPL 75% EERPL 100mX100m 96.66%99.22%99.27%98.95%99.59% 150mX150m97.97%98.82%98.5%97.97% 200mX200m97.1%97.24%97.28%97.108% 97.1% AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m89.64%99.177%99.296%98.947%97.2% 150mX150m89.99%91.074%92.508%89.994%89.99% 200mX200m90.81%89.6%90.11%89.6%90.81% Without interference range With interference range

Average Time Delay Results for 20 nodes AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m mX150m mX200m AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m mX150m mX200m Without interference range With interference range

Average Time Delay Results for 40 nodes AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m mX150m mX200m AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m mX150m mX200m Without interference range With interference range

Average Time Delay Results for 80 nodes AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m mX150m mX200m AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m mX150m mX200m Without interference range With interference range

Number of Dead Nodes for 20 nodes AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m mX150m mX200m53365 AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m mX150m mX200m76666 Without interference range With interference range

Number of Dead Nodes for 40 nodes AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m mX150m mX200m AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m mX150m mX200m Without interference range With interference range

Number of Dead Nodes for 80 nodes AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m mX150m mX200m AreaRPLETRPL 25%ETRPL 50%ETRPL 75%EERPL 100mX100m mX150m mX200m76 Without interference range With interference range

Conclusion

The energy consumption of ETRPL is better than that of RPL protocol. For small area of 100mX100m, an increase in the remaining energy of at least 36%, 64.7% and 87% is achieved using 20, 40 and 80 nodes, respectively. ETRPL also performed better than RPL in regards to average time delay, Packet Reception Ratio, and the number of dead nodes in small area. For large area of 200mX200m, the performance is degraded for some test conditions. The proposed ETRPL protocol is useful for IoT networks with relatively small areas with high number of nodes Regarding ETRPL

Conclusion The energy consumption of EERPL is better than that of RPL protocol. For small area of 100mX100m, an increase in the remaining energy of 37.7%, 67.39% and 82.08% is achieved using 20, 40 and 80 nodes, respectively. ETRPL perform better than EERPL in small area while EERPL perform better in large area with interferen ce range for 20 nodes and also in medium and large area with 40 nodes. The EERPL performs as RPL for most cases with 80 nodes. EERPL also performed better than RPL in regards to Time Delay, Packet Reception Ratio, and the number of dead nodes in small area. For large area of 200mX200 m, the performance is degraded for some test conditions. The proposed EERPL protocol is useful for IoT networks with relatively large area with small or medium number of nodes Regarding EERPL

Future works

Implementing ETRPL and EERPL protocol using real hardware devices. Propose another objective function by taking into consideration other nodes/link metric such as Received Signal Strength Indicator (RSSI). Use different node platform such as Zolertia Z1 mote rather than Tmote sky to see the performance of the proposed protocols Use the proposed protocols in different wireless environment such as fast fading channel to see the strength of the protocols in real environments. 04

References

[1] Z. Wang, L. Zhang, Z. Zheng, and J. Wang, “An Optimized RPL Protocol for Wireless Sensor Net works,” IEEE 22nd Int. Conf. Parallel Distrib. Syst., [2]Q. Q. Abuein and et al., “Performance Evaluation of Routing Protocol (RPL) for Internet of Thing s,” Int. J. Adv. Comput. Sci. Appl., vol. 7, no. 7, pp. 17–20, [3]Z. Wang, L. Zhang, Z. Zheng, and J. Wang, “Energy balancing RPL protocol with multipat h for wireless sensor networks,” Peer-to-Peer Netw. Appl., pp. 1–16, [4] M. A. Mahmud, A. Abdelgawad, and K. Yelamarthi, “Energy efficient routing for Internet of Things (IoT) applications,” 2017 IEEE Int. Conf. Electro Inf. Technol., pp. 442–446, [5] J. Nassar, M. Berthomé, J. Dubrulle, N. Gouvy, and B. Quoitin, “Multiple Instances QoS Routing I n RPL: Application To Smart Grids,” pp. 0–16, [6] P. Sanmartin and et al., “Sigma routing metric for rpl protocol,” Sensors, vol. 18, no [7] S. Kharche and S. Pawar, “Stability model for RPL with minimum rank hysterisis objective functio n in 6LoWPAN,” Int. J. Pure Appl. Math., vol. 118, no. 5 Special Issue, pp. 731–737, 2018.

Thank you