Ruzzelli, Cotan O’Hare, Tynan, Havinga Protocol assessment issues in low duty cycle sensor networks: The switching energy.

Slides:



Advertisements
Similar presentations
16-1 ©2006 Raj JainCSE574sWashington University in St. Louis Energy Management in Ad Hoc Wireless Networks Raj Jain Washington University in Saint Louis.
Advertisements

A 2 -MAC: An Adaptive, Anycast MAC Protocol for Wireless Sensor Networks Hwee-Xian TAN and Mun Choon CHAN Department of Computer Science, School of Computing.
An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Network
S-MAC Sensor Medium Access Control Protocol An Energy Efficient MAC protocol for Wireless Sensor Networks.
Medium Access Control in Wireless Sensor Networks.
PERFORMANCE MEASUREMENTS OF WIRELESS SENSOR NETWORKS Gizem ERDOĞAN.
UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP AIC group: Networking Protocols and agent methodology research for Sensor Networks.
Investigating Mac Power Consumption in Wireless Sensor Network
An Energy-Efficient MAC Protocol for Wireless Sensor Networks
UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP Advantages of Dual Channel MAC for Wireless Sensor Networks Antonio G. Ruzzelli, Gregory.
PEDS September 18, 2006 Power Efficient System for Sensor Networks1 S. Coleri, A. Puri and P. Varaiya UC Berkeley Eighth IEEE International Symposium on.
1 Cross-Layer Scheduling for Power Efficiency in Wireless Sensor Networks Mihail L. Sichitiu Department of Electrical and Computer Engineering North Carolina.
By Antonio Ruzzelli MANAGEMENT ISSUES FOR WIRELESS SENSOR NETWORKS, AN OVERVIEW:
UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP An Energy-Efficient and Low- Latency Routing for Wireless Sensor Networks Antonio G.
UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP Ruzzelli, Cotan O’Hare, Tynan, Havinga Protocol assessment.
1 Ultra-Low Duty Cycle MAC with Scheduled Channel Polling Wei Ye Fabio Silva John Heidemann Presented by: Ronak Bhuta Date: 4 th December 2007.
An Energy-efficient MAC protocol for Wireless Sensor Networks
MERLIN: Integrating energy-efficient MAC and Routing MERLIN: A Synergetic Integration of MAC and Routing for.
MERLIN: A synergetic Integration of MAC and Routing for Distributed Sensor Networks A.G.Ruzzelli, M.J.O’Grady, R.Tynan, G.M.P.O’Hare. Adaptive Information.
TiZo-MAC The TIME-ZONE PROTOCOL for mobile wireless sensor networks by Antonio G. Ruzzelli Supervisor : Paul Havinga This work is performed as part of.
On the Energy Efficient Design of Wireless Sensor Networks Tariq M. Jadoon, PhD Department of Computer Science Lahore University of Management Sciences.
Versatile low power media access for wireless sensor networks Joseph PolastreJason HillDavid Culler Computer Science Department University of California,Berkeley.
Ruzzelli, Cotan O’Hare, Tynan, Havinga Protocol assessment issues in low duty cycle sensor networks: The switching energy.
Power saving technique for multi-hop ad hoc wireless networks.
UNIVERSITY COLLEGE DUBLINDUBLIN CITY UNIVERSITY SMI || NCSR || CDVP Advantages of Dual Channel MAC for Wireless Sensor Networks Antonio G. Ruzzelli, Gregory.
MAC Layer Protocols for Sensor Networks Leonardo Leiria Fernandes.
RF Wakeup Sensor – On-Demand Wakeup for Zero Idle Listening and Zero Sleep Delay.
Energy Saving In Sensor Network Using Specialized Nodes Shahab Salehi EE 695.
1 An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Networks The First ACM Conference on Embedded Networked Sensor Systems (SenSys 2003) November.
A Multi-Channel MAC Protocol for Wireless Sensor Networks Chen xun, Han peng, He qiu-sheng, Tu shi-liang, Chen zhang-long The Sixth IEEE International.
1 Adaptive QoS Framework for Wireless Sensor Networks Lucy He Honeywell Technology & Solutions Lab No. 430 Guo Li Bin Road, Pudong New Area, Shanghai,
College of Engineering Non-uniform Grid- based Coordinated Routing Priyanka Kadiyala Major Advisor: Dr. Robert Akl Department of Computer Science and Engineering.
An Energy Efficient MAC Protocol for Wireless Sensor Networks “S-MAC” Wei Ye, John Heidemann, Deborah Estrin Presentation: Deniz Çokuslu May 2008.
On-Demand Traffic-Embedded Clock Synchronization for Wireless Sensor Networks Sang Hoon Lee.
An Energy-Efficient MAC Protocol for Wireless Sensor Networks (S-MAC) Wei Ye, John Heidemann, Deborah Estrin.
RT-Link: A Time-Synchronized Link Protocol for Energy-Constrained Multi- hop Wireless Networks Anthony Rowe, Rahul Mangharam and Raj Rajkumar CMU SECON.
1 Core-PC: A Class of Correlative Power Control Algorithms for Single Channel Mobile Ad Hoc Networks Jun Zhang and Brahim Bensaou The Hong Kong University.
Why Visual Sensor Network & SMAC Implementation Group Presentation Raghul Gunasekaran.
Wireless Sensor Network Protocols Dr. Monir Hossen ECE, KUET Department of Electronics and Communication Engineering, KUET.
Hao Chen, Guoliang Yao, Hao Liu National ASIC System Engineering Research Center Southeast University WICOM 2008.
UNIVERSITY COLLEGE DUBLIN Adaptive Radio Modes in Sensor Networks: How Deep to Sleep? SECON 2008 San Francisco, CA June 17, 2008 Raja Jurdak Antonio Ruzzelli.
Presenter: Abhishek Gupta Dept. of Electrical and Computer Engineering
Presentation of Wireless sensor network A New Energy Aware Routing Protocol for Wireless Multimedia Sensor Networks Supporting QoS 王 文 毅
Collision-free Time Slot Reuse in Multi-hop Wireless Sensor Networks
Versatile Low Power Media Access for Wireless Sensor Networks Sarat Chandra Subramaniam.
A SURVEY OF MAC PROTOCOLS FOR WIRELESS SENSOR NETWORKS
An Adaptive Energy-Efficient and Low- Latency MAC for Data Gathering in Wireless Sensor Networks Gang Lu, Bhaskar Krishnamachari, and Cauligi S. Raghavendra.
An Energy-Efficient and Low-Latency Routing Protocol for Wireless Sensor Networks Antonio G. Ruzzelli, Richard Tynan and G.M.P. O’Hare Adaptive Information.
An Energy Efficient MAC Protocol for Wireless LANs, E.-S. Jung and N.H. Vaidya, INFOCOM 2002, June 2002 吳豐州.
A Wakeup Scheme for Sensor Networks: Achieving Balance between Energy Saving and End-to-end Delay Xue Yang, Nitin H.Vaidya Department of Electrical and.
Adaptive Sleep Scheduling for Energy-efficient Movement-predicted Wireless Communication David K. Y. Yau Purdue University Department of Computer Science.
1 An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Networks Tijs van Dam, Koen Langendoen In ACM SenSys /1/2005 Hong-Shi Wang.
A+MAC: A Streamlined Variable Duty-Cycle MAC Protocol for Wireless Sensor Networks 1 Sang Hoon Lee, 2 Byung Joon Park and 1 Lynn Choi 1 School of Electrical.
SEA-MAC: A Simple Energy Aware MAC Protocol for Wireless Sensor Networks for Environmental Monitoring Applications By: Miguel A. Erazo and Yi Qian International.
KAIS T Medium Access Control with Coordinated Adaptive Sleeping for Wireless Sensor Network Wei Ye, John Heidemann, Deborah Estrin 2003 IEEE/ACM TRANSACTIONS.
A Throughput-Adaptive MAC Protocol for Wireless Sensor Networks Zuo Luo, Liu Danpu, Ma Yan, Wu Huarui Beijing University of Posts and Telecommunications.
An Energy-Efficient MAC Protocol for Wireless Sensor Networks Speaker: hsiwei Wei Ye, John Heidemann and Deborah Estrin. IEEE INFOCOM 2002 Page
Delivery ratio-maximized wakeup scheduling for ultra-low duty-cycled WSNs under real-time constraints Fei Yang, Isabelle Augé-Blum National Institute of.
Link Layer Support for Unified Radio Power Management in Wireless Sensor Networks IPSN 2007 Kevin Klues, Guoliang Xing and Chenyang Lu Database Lab.
Turkmen Canli ± and Ashfaq Khokhar* Electrical and Computer Engineering Department ± Computer Science Department* The University of Illinois at Chicago.
Utilization Based Duty Cycle Tuning MAC Protocol for Wireless Sensor Networks Shih-Hsien Yang, Hung-Wei Tseng, Eric Hsiao-Kuang Wu, and Gen-Huey Chen Computer.
UNIT IV INFRASTRUCTURE ESTABLISHMENT. INTRODUCTION When a sensor network is first activated, various tasks must be performed to establish the necessary.
Cross-Layer Scheduling for Power Efficiency in Wireless Sensor Networks Mihail L. Sichitiu Department of Electrical and Computer Engineering North Carolina.
Energy-Efficient, Application-Aware Medium Access for Sensor Networks Venkatesh Rajenfran, J. J. Garcia-Luna-Aceves, and Katia Obraczka Computer Engineering.
A Bit-Map-Assisted Energy- Efficient MAC Scheme for Wireless Sensor Networks Jing Li and Georgios Y. Lazarou Department of Electrical and Computer Engineering,
Power-Efficient Rendez- vous Schemes for Dense Wireless Sensor Networks En-Yi A. Lin, Jan M. Rabaey Berkeley Wireless Research Center University of California,
Z-MAC : a Hybrid MAC for Wireless Sensor Networks Injong Rhee, Ajit Warrier, Mahesh Aia and Jeongki Min ACM SenSys Systems Modeling.
AN EFFICIENT TDMA SCHEME WITH DYNAMIC SLOT ASSIGNMENT IN CLUSTERED WIRELESS SENSOR NETWORKS Shafiq U. Hashmi, Jahangir H. Sarker, Hussein T. Mouftah and.
SENSYS Presented by Cheolki Lee
Ultra-Low Duty Cycle MAC with Scheduled Channel Polling
Presentation transcript:

Ruzzelli, Cotan O’Hare, Tynan, Havinga Protocol assessment issues in low duty cycle sensor networks: The switching energy A.G. Ruzzelli, P. Cotan*, G.M.P. O’Hare, R. Tynan, and P.J.M Havinga** Adaptive Information Cluster (AIC) PRISM Laboratory School of Computer Science and Informatics, University College Dublin (UCD), Ireland. *Department of Electronic Engineering, Technical University of Catalonia, Spain. **Department of Computer Science, University of Twente, The Netherlands.

Ruzzelli, Cotan O’Hare, Tynan, Havinga Summary Generality on protocol energy assessment The low duty Cycle through the wake up concept Switching between transceiver states Phase1: Board measurements –The sensor node –The experimental approach –The measured results Phase2: Switching energy assessment –The S-MAC protocol –Performance evaluation –Simulation setup –Simulated results Considerations Conclusions

Ruzzelli, Cotan O’Hare, Tynan, Havinga Generality on protocol energy assessment Energy consumption mainly due to the transceiver activity; Protocol energy assessment based on transceiver states: –Transmit time; –Receive time; –Idle time (Sleeping time in sensor-nets); –Switching time (USUALLY NOT ASSESSED); Switching energy negligible in ad-hoc wireless network protocol assessment (e.g. WiFi);

Ruzzelli, Cotan O’Hare, Tynan, Havinga Switching in standard wireless networks Is defined as the transition time that elapses between the end of a transceiver state and the beginning of the following one; Possible switching states consist of: –RX/TX and TX/RX –TX/Sleep and Sleep/TX –RX/Sleep and Sleep/RX State transition is fast  little amount of energy is consumed. Switching energy is much smaller than total energy spent. Transceiver data sheets report average switching time but not the energy spent. Related work show that assessment of novel protocol architectures for WSNs inherited the switching energy negligibility.

Ruzzelli, Cotan O’Hare, Tynan, Havinga Sensor network characteristics Energy consumption: primary objective The wake-up concept Very low duty cycle (even less than 5%) Small packets smaller than in ad-hoc networks (e.g. temperature data is few bytes) Low data traffic per node Can we consider switching energy still negligible for low duty cycle sensor networks?

Ruzzelli, Cotan O’Hare, Tynan, Havinga Phase 1: The experimental model Analysis conducted on different EYES sensor node prototypes Prototypes mounted different off-the shelf transceiver for sensor networks; Investigation of Tr1001, CC1000 and CC1010 transceivers;

Ruzzelli, Cotan O’Hare, Tynan, Havinga Phase 1:The experimental approach The voltage drop is gauged across high-side series resistor placed between the battery (+ terminal) and the input power connector; Current consumption, power and energy consumption derived from the voltage. Hardware connected to an oscilloscope.

Ruzzelli, Cotan O’Hare, Tynan, Havinga The measuring circuit Based on INA110 instrumentation amplifier fast settling time and high slew rate device. Two resistors used: “low power mode” and “Tx/Rx mode”. Test performed by a square waveform of 1 kHz and of 5 V amplitude at the input of the INA 110 connected through an attenuating resistive divider circuit. Good precision and low distortion for conducting measurements at the edges. INA110 main characteristics Bias50 pA max Settling time (Vout 20V)3 us to 0.1 % CMRR106 dB min Gain1, 10, 100, 200, 500 Input impedance5x10^12 ohm || 6pF Slew Rate17 V/us Small signal BW470 kHz (Gain = 100)

Ruzzelli, Cotan O’Hare, Tynan, Havinga Preliminary notes: The CC1010 had a processor built in and therefore the CPU on that board could be put into sleep mode. CC chipcon class presented higher sensitivity than TR1001. CC1000 and CC1010 boards were configured with the oscillator ON in low power mode  shorter switching time (2ms activation if OFF) Board measurement results Boards current and power consumption Current [mA]Power [mW] SLRXTXSLRXTX TR CC CC Boards switching energy Boards switching times Switching Energy [uJ] SL to RXSL to TXRX to SLTX to SLRX to TXTX to RX TR CC CC Switching Times [us] SL to RXSL to TXRX to SLTX to SLRX to TXTX to RX TR CC CC

Ruzzelli, Cotan O’Hare, Tynan, Havinga Phase 2: Switching energy assessment The values obtained are applied to the SMAC protocol; SMAC is normally used as benchmark against other novel architectures; Results obtained by using the OmNet++ simulator

Ruzzelli, Cotan O’Hare, Tynan, Havinga The SMAC protocol SMAC divides time in two periods: active time and sleeping time; Active period = SYNC period for node sync update, Request To Send (RTS), Clear to Send (CTS). Communication establishing: – neighboring nodes synchronize to the start of the active period then local broadcast of SYNC packets. Data message exchanges follow the RTS/CTS/DATA/ACK; –  nodes switch between different states periodically. RTS CTS Data Transmitter Receiver time ACK

Ruzzelli, Cotan O’Hare, Tynan, Havinga Simulation setup Three nodes and one gateway in a line –Node 3 = Source; Node1 & Node2 = Forwarder; Gateway = Destination nodes communicate with direct neighbours only. Results averaged between node2 and node1 values (higher node switching activity) 13 independent simulations of 20 minutes each. 10 independent random seeds for clock skew and offset inaccuracies. Traffic load regulated by Node 3 –16 bytes packet –Generation rate: 60s(low traffic) and 2s (high traffic).

Ruzzelli, Cotan O’Hare, Tynan, Havinga Performance evaluation metrics Energy TX %: spent by per node per bit transmitted; Energy Switch %: spent per node for the total number of transitions of two consecutive states; Energy Sleep %: energy spent by one node during the time of inactivity referred to as the sleeping state; Total consumption per node: all previous metrics plus RX energy and idle listening. Duty cycle changed by varying the node active period

Ruzzelli, Cotan O’Hare, Tynan, Havinga Simulated results (1): Total consumption Low traffic High traffic The simulations ended after 50 packets were correctly relayed from source to destination; The results show only a little increase of consumption in high data traffic conditions; The CC family present higher energy consumption profile than Tr1001 due to: –The processor built; –The oscillator left ON in low power mode (oscillator OFF → >5mA current consumption to wake-up)

Ruzzelli, Cotan O’Hare, Tynan, Havinga Simulated results (2): Low traffic condition For all transceivers and duty cycles, switching energy is between the sleeping energy and energy TX; Switching energy can be higher than the energy TX. Lower bound of 1.7% for the duty cycle due to an intrinsic operational limit of SMAC. Other existing protocols that can work below 1% duty cycle (e.g. BMAC) Switching energy as percentage of the total consumption

Ruzzelli, Cotan O’Hare, Tynan, Havinga Simulated results (3): High traffic condition Maximum switching value above 6% for 1.7% duty; Oscillator ON causes higher sleeping energy of CC family thanTR1001. Expected higher % of switching energy for duty cycle lower than 1.7% Switching energy as percentage of the total consumption

Ruzzelli, Cotan O’Hare, Tynan, Havinga Considerations and guidelines Considering 5% as the lower bound of energy consumption significance: –For TR1001 and CC1010, the switching energy needs to be computed if the node duty cycle is equal to or less than 3% and 3.6% respectively; –For CC1000, the switching energy needs to be computed if the node duty cycle is equal to or less than 2.7% and 3.6% respectively; –Sleeping energy consumption of TR1001 can be neglected in any case simulated as less than 2%; –For CC1000 and CC1010 in low traffic load conditions, the transmitting energy becomes significant at 2.5% duty cycle or lower. Although similar, total energy consumptions might greatly differ in their inner energy usage composition  The choice of a protocol to use is not only based on the application but also on the radio on board

Ruzzelli, Cotan O’Hare, Tynan, Havinga Conclusion Values of switching energy have been obtained by direct measurements on different boards; The measurements have been applied to the SMAC protocol; Considerations and protocol assessment guidelines have been derived; In low duty cycle sensor-nets, the switching energy should be computed together with transmitting, receiving and sleeping energies; The obtained results help improve the MAC protocol evaluation process and empowers decisions relating to the judicious protocol/hardware choice for an specific set of WSN applications; Switching energy is expected to account for an even more significant percentage of the total power consumed as the duty cycle get closer to 1% such as in BMAC; Future work activities include the investigation of TDMA protocols that allow lower node duty cycle and more complex topologies.

Ruzzelli, Cotan O’Hare, Tynan, Havinga Thank you for your kind attention! Questions are welcome! Thank you