ETH Zurich – Distributed Computing – www.disco.ethz.ch Sharing a Medium Between Concurrent Protocols Without Overhead Using the Capture Effect Michael.

Slides:



Advertisements
Similar presentations
Christoph Lenzen Philipp Sommer Philipp Sommer Roger Wattenhofer Roger Wattenhofer Optimal Clock Synchronization in Networks.
Advertisements

Gradient Clock Synchronization in Wireless Sensor Networks
1 MMSN: Multi-Frequency Media Access Control for Wireless Sensor Networks Gang Zhou, Chengdu Huang, Ting Yan, Tian He John. A. Stankovic, Tarek F. Abdelzaher.
1 An Approach to Real-Time Support in Ad Hoc Wireless Networks Mark Gleeson Distributed Systems Group Dept.
Efficient Network Flooding and Time Synchronization with Glossy
Routing, Anycast, and Multicast for Mesh and Sensor Networks Roland Flury Roger Wattenhofer RAM Distributed Computing Group.
Dynamic Internet Congestion with Bursts Stefan Schmid Roger Wattenhofer Distributed Computing Group, ETH Zurich 13th International Conference On High Performance.
ETH Zurich – Distributed Computing Group Roger Wattenhofer 1ETH Zurich – Distributed Computing – Christoph Lenzen Roger Wattenhofer Exponential.
Performance of DS-CDMA Protocols in Wireless LANS M.Parikh, P.Sharma, R.Garg, K. Chandra, C. Thompson Center for Advanced Computation and Telecommunications.
1 C-MAC: Model-driven Concurrent Medium Access Control for Wireless Sensor Networks Mo Sha ; Guoliang Xing ; Gang Zhou ; Shucheng Liu ; Xiaorui Wang City.
1 Experimental Study of Concurrent Transmission in Wireless Sensor Networks Dongjin Son, Bhaskar Krishnamachari (USC/EE), and John Heidemann (USC/ISI)
SANS A Simple Ad hoc Network Simulator Nicolas Burri Roger Wattenhofer Yves Weber Aaron Zollinger.
ETH Zurich – Distributed Computing Group Jasmin Smula 1ETH Zurich – Distributed Computing – Stephan Holzer Yvonne Anne Pignolet Jasmin.
1 University of Freiburg Computer Networks and Telematics Prof. Christian Schindelhauer Wireless Sensor Networks 7th Lecture Christian Schindelhauer.
A TCP With Guaranteed Performance in Networks with Dynamic Congestion and Random Wireless Losses Stefan Schmid, ETH Zurich Roger Wattenhofer, ETH Zurich.
Chapter 1 NETWORKING BASICS.
Submission doc.: IEEE /0336r1 March 2015 Xiaofei Wang (InterDigital)Slide 1 MAC Overhead Analysis of MU Transmissions Date: Authors:
Protocol Implementation An Engineering Approach to Computer Networking.
Efficient MAC Protocols for Wireless Sensor Networks
Network Topologies An introduction to Network Topologies and the Link Layer.
Networking Components By: Michael J. Hardrick. HUB  A low cost device that sends data from one computer to all others usually operating on Layer 1 of.
Voice over the Dins: Improving Wireless Channel Utilization with Collision Tolerance Xiaoyu Ji Xiaoyu Ji, Yuan He, Jiliang Wang, Kaishun Wu, Ke Yi, Yunhao.
The Case for Addressing the Limiting Impact of Interference on Wireless Scheduling Xin Che, Xi Ju, Hongwei Zhang {chexin, xiju,
MOJO: A Distributed Physical Layer Anomaly Detection System for WLANs Richard D. Gopaul CSCI 388.
1 The Power of Non-Uniform Wireless Power ETH Zurich – Distributed Computing Group Magnus M. Halldorsson Reykjavik University Stephan Holzer ETH Zürich.
Mitigating Congestion in Wireless Sensor Networks Bret Hull, Kyle Jamieson, Hari Balakrishnan Networks and Mobile Systems Group MIT Computer Science and.
Doc.: IEEE yy/xxxxr0 SubmissionMukul Goyal, U Wisconsin MilwaukeeSlide 1 Impact of IEEE n Operation On IEEE Performance Notice: This.
DISSense: An Adaptive Ultralow-power Communication Protocol for Wireless Sensor Networks Ugo Maria Colesanti*, Silvia Santini°, Andrea Vitaletti* * Dipartimento.
A Systematic Approach to the Design of Distributed Wearable Systems Urs Anliker, Jan Beutel, Matthias Dyer, Rolf Enzler, Paul Lukowicz Computer Engineering.
© 2006 Cisco Systems, Inc. All rights reserved.Cisco Public 1 LAN Design LAN Switching and Wireless – Chapter 1.
LAN Switching and Wireless – Chapter 1
© 2006 Cisco Systems, Inc. All rights reserved.Cisco Public 1 Version 4.0 LAN Design LAN Switching and Wireless – Chapter 1.
ETH Zurich – Distributed Computing – Klaus-Tycho Förster, Rijad Nuridini, Jara Uitto, Roger Wattenhofer Lower Bounds for the Capture.
ETH Zurich – Distributed Computing – Silvio Frischknecht, Barbara Keller, Roger Wattenhofer Convergence in (Social) Influence Networks.
Wireless Sensor Networks M Homework #2. IEEE MAC Protocol - Star topology – Part I Consider a square area equipped with 30 nodes distributed.
Doc.: IEEE /30r2 SubmissionMukul Goyal, U Wisconsin MilwaukeeSlide 1 Impact of IEEE n Operation On IEEE Performance Notice: This.
Communication for the Wearable Platform Jan Beutel Computer Engineering and Networks Lab Swiss Federal Institute of Technology (ETH) Zurich October 19,
ETH Zurich – Distributed Computing Group Stephan Holzer 1ETH Zurich – Distributed Computing – Stephan Holzer Yvonne Anne Pignolet Jasmin.
ETH Zurich – Distributed Computing Group Stephan Holzer 1ETH Zurich – Distributed Computing – Stephan Holzer Yvonne Anne Pignolet Jasmin.
Energy-Efficient, Application-Aware Medium Access for Sensor Networks Venkatesh Rajenfran, J. J. Garcia-Luna-Aceves, and Katia Obraczka Computer Engineering.
ETH Zurich – Distributed Computing Group Stephan Holzer 1ETH Zurich – Distributed Computing – Stephan Holzer Yvonne Anne Pignolet Jasmin.
Trading Structure for Randomness in Wireless Opportunistic Routing Szymon Chachulski, Michael Jennings, Sachin Katti and Dina Katabi MIT CSAIL SIGCOMM.
A Theory of QoS for Wireless I-Hong Hou Vivek Borkar P.R. Kumar University of Illinois, Urbana-Champaign.
MMSN: Multi-Frequency Media Access Control for Wireless Sensor Networks Cheoleun Moon Computer Science Div. at KAIST.
Vehicle Traffic Simulator and Intersection Collision Warning System Wireless repeater Rebroadcast received packets (once) Packet transmission behavior.
A Bit-Map-Assisted Energy- Efficient MAC Scheme for Wireless Sensor Networks Jing Li and Georgios Y. Lazarou Department of Electrical and Computer Engineering,
ETH Zurich – Distributed Computing Group Stephan HolzerSODA Stephan Holzer Silvio Frischknecht Roger Wattenhofer Networks Cannot Compute Their Diameter.
Artur BarczykRT2003, High Rate Event Building with Gigabit Ethernet Introduction Transport protocols Methods to enhance link utilisation Test.
PAC: Perceptive Admission Control for Mobile Wireless Networks Ian D. Chakeres Elizabeth M. Belding-Royer.
Exploring Random Access and Handshaking Techniques in Large- Scale Underwater Wireless Acoustic Sensor Networks Peng Xie and Jun-Hong Cui Computer Science.
Discovering Sensor Networks: Applications in Structural Health Monitoring Summary Lecture Wireless Communications.
Data Communication Networks Lec 18. Wired LAN:Ethernet Datalink layer – Logical link control(LLC) – MAC Physical layer.
ETH Zurich – Distributed Computing – Klaus-Tycho Förster, Ratul Mahajan, and Roger Wattenhofer Consistent Updates in Software Defined.
ETH Zurich – Distributed Computing Group Stephan HolzerETH Zurich – Distributed Computing – Stephan Holzer - ETH Zürich Thomas Locher.
MAC Protocols for Sensor Networks
Projects.
Chris Cai, Shayan Saeed, Indranil Gupta, Roy Campbell, Franck Le
Contention-based protocols with Reservation Mechanisms
Jan 2017 report.
LAN Switching and Wireless – Chapter 1
Effectively Capturing Attention Using the Capture Effect
Communication Networks NETW 501
ATP TCP Reducing the Latency-Tail of Short-Lived Flows: Adding Forward Error Correction in Data Centers Klaus-Tycho Foerster, Demian Jaeger, David Stolz,
EECS Department University of California, Berkeley
CSE 451: Operating Systems Spring 2005 Module in 9 slides
CSE 451: Operating Systems Winter 2007 Module in 9 slides
LAN Switching and Wireless – Chapter 1
CSE 451: Operating Systems Autumn 2009 Module in 9 slides
doc.: IEEE <doc#>
LAN Switching and Wireless – Chapter 1
Presentation transcript:

ETH Zurich – Distributed Computing – Sharing a Medium Between Concurrent Protocols Without Overhead Using the Capture Effect Michael König Roger Wattenhofer

Wireless Sensor Networks

? ? Priority Traffic – CSMA

Priority Traffic – Scheduling

The Capture Effect

The Capture Effect – Power Difference

The Capture Effect – Packet Timing Preamble SFD Len Payload... Time Preamble SFD Len Payload... (weaker) (stronger)

The Capture Effect – Packet Timing Preamble SFD Len Payload... Time Preamble SFD Len Payload µs (weaker) (stronger)

The Capture Effect – Packet Timing

Priority Traffic – Using the Capture Effect

Halfway Summary MethodAlarm DelayRegular Operation Impairment CSMAArbitrarily largeNone SchedulingBoundedConstant fraction Capture EffectNone *

Network Heterogeneity vs

Testbed Example

Network Heterogeneity

Layer 4 Layer 3 Layer 2 Layer dBm -70 dBm -75 dBm -81 dBm “Layer” Abstraction: Receiving

“Layer” Abstraction: Sending Layer 4 Layer 3 Layer 2 Layer 1

“Layer” Abstraction Layer 4 Layer 3 Layer 2 Layer 1

“Layer” Abstraction: Caveat Layer 4 Layer 3 Layer 2 Layer 1

Feasible number of layers vs

Summary Layer 4 Layer 3 Layer 2 Layer 1

ETH Zurich – Distributed Computing – Questions Michael König

Backup Slides

Layer 1 - Convergecast