Low-Power Wireless Bus (LWB) SenSys 2012 Federico Ferrari, Marco Zimmerling(ETH), Luca Mottola(SICS), Lothar Thiele (ETH) ("Potential" BEST PAPER/RUNNER.

Slides:



Advertisements
Similar presentations
Low-Power Wireless Bus
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.
Min Song 1, Yanxiao Zhao 1, Jun Wang 1, E. K. Park 2 1 Old Dominion University, USA 2 University of Missouri at Kansas City, USA IEEE ICC 2009 A High Throughput.
Maximum Battery Life Routing to Support Ubiquitous Mobile Computing in Wireless Ad Hoc Networks By C. K. Toh.
Decentralized Reactive Clustering in Sensor Networks Yingyue Xu April 26, 2015.
TDMA Scheduling in Wireless Sensor Networks
pTunes: Runtime Parameter Adaptation for Low-power MAC Protocols
1 An Approach to Real-Time Support in Ad Hoc Wireless Networks Mark Gleeson Distributed Systems Group Dept.
Medium Access Control in Wireless Sensor Networks.
1 Routing Techniques in Wireless Sensor networks: A Survey.
Efficient Network Flooding and Time Synchronization with Glossy
Investigating Mac Power Consumption in Wireless Sensor Network
PEDS September 18, 2006 Power Efficient System for Sensor Networks1 S. Coleri, A. Puri and P. Varaiya UC Berkeley Eighth IEEE International Symposium on.
Before start… Earlier work single-path routing in sensor networks
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
Analysis of the Performance of IEEE for Medical Sensor Body Area Networking ECE 5900 Computer Engineering Seminar Instructor: Dr. Chigan Huaming.
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.
MAC Layer Protocols for Sensor Networks Leonardo Leiria Fernandes.
Modeling and Evaluation of Fibre Channel Storage Area Networks Xavier Molero, Federico Silla, Vicente Santonia and Jose Duato.
Network Topologies.
Mehmet C. Vuran Vehbi C. Gungor Özgür B. Akan School of Electrical & Computer Engineering Georgia Institute of Technology Atlanta, GA {mcvuran,
Presenter: Abhishek Gupta Dept. of Electrical and Computer Engineering
1 Y-MAC: An Energy-efficient Multi-channel MAC Protocol for Dense Wireless Sensor Networks Youngmin Kim, Hyojeong Shin, and Hojung Cha International Conference.
Itrat Rasool Quadri ST ID COE-543 Wireless and Mobile Networks
Enabling Dependable Communication in Cyber-Physical Systems with a Wireless Bus Federico Ferrari PhD Defense October 18, 2013 — Zurich, Switzerland Computer.
Multimedia & Networking Lab
College of Engineering Non-uniform Grid- based Coordinated Routing Priyanka Kadiyala Major Advisor: Dr. Robert Akl Department of Computer Science and Engineering.
QoS Support in High-Speed, Wormhole Routing Networks Mario Gerla, B. Kannan, Bruce Kwan, Prasasth Palanti,Simon Walton.
Mohamed Hefeeda 1 School of Computing Science Simon Fraser University, Canada Video Streaming over Cooperative Wireless Networks Mohamed Hefeeda (Joint.
On Modeling Low-Power Wireless Protocols Based On Synchronous Packet Transmissions Marco Zimmerling, Federico Ferrari, Luca Mottola *, Lothar Thiele ETH.
1 An Adaptive Energy-Efficient and Low-Latency MAC for Data Gathering in Wireless Sensor Network Gang Lu, Bhaskar Krishnamachari, and Cauligi Raghavendra.
한국기술교육대학교 컴퓨터 공학 김홍연 Habitat Monitoring with Sensor Networks DKE.
4: DataLink Layer1 Multiple Access Links and Protocols Three types of “links”: r point-to-point (single wire, e.g. PPP, SLIP) r broadcast (shared wire.
A Message Ferrying Approach for Data Delivery in Sparse Mobile Ad Hoc Networks Reporter: Yanlin Peng Wenrui Zhao, Mostafa Ammar, College of Computing,
SIMPLE: Stable Increased Throughput Multi-hop Link Efficient Protocol For WBANs Qaisar Nadeem Department of Electrical Engineering Comsats Institute of.
Improving Link Quality by Exploiting Channel Diversity in Wireless Sensor Networks Manjunath D, Mun Choon Chan, and Ben Leong National University of Singapore.
An Energy-Efficient MAC Protocol for Wireless Sensor Networks Qingchun Ren and Qilian Liang Department of Electrical Engineering, University of Texas at.
Network and Systems Laboratory nslab.ee.ntu.edu.tw Branislav Kusy, Christian Richter, Wen Hu, Mikhail Afanasyev, Raja Jurdak, Michael Brunig, David Abbott,
An Adaptive Energy-Efficient and Low- Latency MAC for Data Gathering in Wireless Sensor Networks Gang Lu, Bhaskar Krishnamachari, and Cauligi S. Raghavendra.
MMAC: A Mobility- Adaptive, Collision-Free MAC Protocol for Wireless Sensor Networks Muneeb Ali, Tashfeen Suleman, and Zartash Afzal Uzmi IEEE Performance,
A Quorum-Based Energy-Saving MAC Protocol Design for Wireless Sensor Networks Chih-Min Chao, Yi-Wei Lee IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2010.
Self Organization and Energy Efficient TDMA MAC Protocol by Wake Up for Wireless Sensor Networks Zhihui Chen and Ashfaq Khokhar ECE Department, University.
Copyright © 2011, Scalable and Energy-Efficient Broadcasting in Multi-hop Cluster-Based Wireless Sensor Networks Long Cheng ∗ †, Sajal K. Das†,
An Energy Efficient MAC Protocol for Wireless LANs, E.-S. Jung and N.H. Vaidya, INFOCOM 2002, June 2002 吳豐州.
We hope that it is more important to know where you are going than to get there quickly. SNU INC Lab. A Survey of Energy Efficient Network Protocols for.
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.
KAIS T Medium Access Control with Coordinated Adaptive Sleeping for Wireless Sensor Network Wei Ye, John Heidemann, Deborah Estrin 2003 IEEE/ACM TRANSACTIONS.
A Multi-Channel Cooperative MIMO MAC Protocol for Wireless Sensor Networks(MCCMIMO) MASS 2010.
An Energy-Efficient MAC Protocol for Wireless Sensor Networks Speaker: hsiwei Wei Ye, John Heidemann and Deborah Estrin. IEEE INFOCOM 2002 Page
Link Layer Support for Unified Radio Power Management in Wireless Sensor Networks IPSN 2007 Kevin Klues, Guoliang Xing and Chenyang Lu Database Lab.
Self-stabilizing energy-efficient multicast for MANETs.
Quality of Service Schemes for IEEE Wireless LANs-An Evaluation 主講人 : 黃政偉.
CS541 Advanced Networking 1 Contention-based MAC Protocol for Wireless Sensor Networks Neil Tang 4/20/2009.
PTunes: Runtime Parameter Adaptation for Low-power MAC Protocols IPSN 2012 Marco Zimmerling, Federico Ferrari (ETH - Zurich), Luca Mottola, Thiemo Voigt.
A Cluster Based On-demand Multi- Channel MAC Protocol for Wireless Multimedia Sensor Network Cheng Li1, Pu Wang1, Hsiao-Hwa Chen2, and Mohsen Guizani3.
FERMA: An Efficient Geocasting Protocol for Wireless Sensor Networks with Multiple Target Regions Young-Mi Song, Sung-Hee Lee and Young- Bae Ko Ajou University.
SERENA: SchEduling RoutEr Nodes Activity in wireless ad hoc and sensor networks Pascale Minet and Saoucene Mahfoudh INRIA, Rocquencourt Le Chesnay.
A Bit-Map-Assisted Energy- Efficient MAC Scheme for Wireless Sensor Networks Jing Li and Georgios Y. Lazarou Department of Electrical and Computer Engineering,
AUTO-ADAPTIVE MAC FOR ENERGY-EFfiCIENT BURST TRANSMISSIONS IN WIRELESS SENSOR NETWORKS Romain Kuntz, Antoine Gallais and Thomas No¨el IEEE WCNC 2011 Speaker.
Medium Access in Sensor Networks. Presented by: Vikram Shankar.
ROUTING TECHNIQUES IN WIRELESS SENSOR NETWORKS: A SURVEY.
Wireless sensor and actor networks: research challenges Ian. F. Akyildiz, Ismail H. Kasimoglu
-1/16- Maximum Battery Life Routing to Support Ubiquitous Mobile Computing in Wireless Ad Hoc Networks C.-K. Toh, Georgia Institute of Technology IEEE.
How to minimize energy consumption of Sensors in WSN Dileep Kumar HMCL 30 th Jan, 2015.
An Energy-efficient MAC protocol for Wireless Sensor Networks
TCP in Mobile Ad-hoc Networks
TCP in Wireless Ad-hoc Networks
Gang Lu Bhaskar Krishnamachari Cauligi S. Raghavendra
Investigating Mac Power Consumption in Wireless Sensor Network
Presentation transcript:

Low-Power Wireless Bus (LWB) SenSys 2012 Federico Ferrari, Marco Zimmerling(ETH), Luca Mottola(SICS), Lothar Thiele (ETH) ("Potential" BEST PAPER/RUNNER UP) NSLab study group 2012/11/05 Presented by: Yu-Ting 1

Outline Introduction Protocol Operation Evaluation Discussion 2

Comment Part1 Good writing structure Clearly explain how this protocol operates An extended work of Glossy – Take the efficient flooding advantage of Glossy A brand-new and awesome unified solution for WSN communication 3

Feature Bootstraps quickly and efficiently, while distributing energy costs evenly In many-to-one scenarios, LWB operates reliably and efficiently under a wide range of traffic loads, and promptly adapts when traffic demands change Supports many-to-many communication without any changes Topology-independent Supports mobile nodes acting as sinks, sources, or both without any changes or performance loss Very good energy consumption! 4

Comment Part2 Compare with 7 different protocols – Good to get familiar with important related work Seems to beats all the other state-of-art protocols Clearly describe the scenario and parameters in evaluation – Use fair choices of parameter for the other protocols – With brief explanation of how other protocols operate Multi-Sink is actually not an easy task (few protocols support that) 5

Outline Introduction Protocol Operation Evaluation Discussion 6

Overview 7

Operation Sink acts as host here Inter-packet interval (IPI) = 6s here 8

Host Failure Failure of host: complete absence of communication within T hf – Upon detect it, nodes switch to the next channel Hardcode a circular ordered list After not receiving stream request for T hf, host also switch the the next channel 9

Scheduler Determining the round period – T min (1s) : > total duration of a round T l – T max (30s) : < time of synchronization failing due to clock skew – d max (60 slots) : number of data slots that the scheduler can map in a single schedule packet (so, # of pkts / round) – When T opt <T min, the network is saturated Allocation data slots to streams – where 10 a s : number of data slots the scheduler allocates to streams during a round r s = T/IPI s

Outline Introduction Protocol Operation Evaluation Discussion 11

Metrics 12

Bootstrapping Fully bootstrapped: when all source nodes delivered at least one packet to the sink LWB, CTP: 18min Fairness in energy consumption: only LWB – Battery depletion may cause a network partition 13

Many-to-One Scenario: Light/Heavy/Fluctuating Traffic 14

Many-to-Many Scenario 8 sinks 15

Topology Changes - External Interference 16

Topology Changes - Node Failures 17

Mobile Sink 18

Mobile Sources(4) and Mobile Sink(1) 19

Real-World Trial Many-to-many One-to-many Change traffic demands Change active nodes 5 mobile nodes (B,M 1 ~M 4 ) as both sources and sinks 7 days during working B: trigger high rate stream of all mobile nodes 20

Outline Introduction Protocol Operation Evaluation Discussion 21

Scalability The more number of streams, the more consumption of memory and computation time – TelosB can support several hundreds of streams (each stream with 15bytes/pkt and 13bytes to store in memory) – [YT] Memory is used to store a burst of received data within 1 round The more number of streams, the more saturated the bandwidth is 22

Network Diameter Difficult to determine the network diameter in advance, which affect the length of data (Td) and schedule (Ts) – Current prototype is 7 hops ([YT] it's not short…) When the network spans "several tens" of hops, other approaches may perform better Longer slots (Ts,Td) leads to fewer available slots per round and thus bandwidth – Default setting: support 300 streams with IPI=5s, so double-length slots support at most IPI=10s 23

Alternative Scheduling Policies Trade off between latency and energy consumption LWB-low-latency: adapts the round period T such that the next round occurs immediately after the generation of new packets LWB-fixed-period: fixes T = T min LWB is easy to modify this, unlike others! 24

Q&A 25