Distributed Hop-by-Hop Rate Adjustment for Congestion Control in Sensor Networks Presented by: Manmohan Voniyadka Sapna Dixit Vipul Bhasin Vishal Kumar.

Slides:

Advertisements

Similar presentations

A DISTRIBUTED CSMA ALGORITHM FOR THROUGHPUT AND UTILITY MAXIMIZATION IN WIRELESS NETWORKS.

Advertisements

Mission-based Joint Optimal Resource Allocation in Wireless Multicast Sensor Networks Yun Hou Prof Kin K. Leung Archan Misra.

Distributed Rate Assignments for Broadband CDMA Networks Tara Javidi Electrical & Computer Engineering University of California, San Diego.

Mobile and Wireless Computing Institute for Computer Science, University of Freiburg Western Australian Interactive Virtual Environments Centre (IVEC)

6LoWPAN Extending IP to Low-Power WPAN 1 By: Shadi Janansefat CS441 Dr. Kemal Akkaya Fall 2011.

1 CONGESTION CONTROL. 2 Congestion Control When one part of the subnet (e.g. one or more routers in an area) becomes overloaded, congestion results. Because.

Queuing Network Models for Delay Analysis of Multihop Wireless Ad Hoc Networks Nabhendra Bisnik and Alhussein Abouzeid Rensselaer Polytechnic Institute.

Improvement on LEACH Protocol of Wireless Sensor Network

Monday, June 01, 2015 ARRIVE: Algorithm for Robust Routing in Volatile Environments 1 NEST Retreat, Lake Tahoe, June

PORT: A Price-Oriented Reliable Transport Protocol for Wireless Sensor Networks Yangfan Zhou, Michael. R. Lyu, Jiangchuan Liu † and Hui Wang The Chinese.

Mac Support for Broadcast-based Ad hoc Forwarding Scheme Ashikur Rahman and Pawel Gburzynski Department of Computing Science University of Alberta

Distributed Hop-by-Hop Rate Adjustment for Congestion Control in Sensor Networks Presented by: Vipul Bhasin Sapna Dixit Vishal Kumar Singh Manmohan Voniyadka.

KUASAR An efficient and light-weight protocol for routing and data dissemination in ad hoc wireless sensor networks David Andrews Aditya Mandapaka Joe.

Network Coding and Reliable Communications Group A Multi-hop Multi-source Algebraic Watchdog Muriel Médard † Joint work with MinJi Kim †, João Barros ‡

Low Delay Marking for TCP in Wireless Ad Hoc Networks Choong-Soo Lee, Mingzhe Li Emmanuel Agu, Mark Claypool, Robert Kinicki Worcester Polytechnic Institute.

Optimal Data Compression and Forwarding in Wireless Sensor Networks Bulent Tavli, Mehmet Kayaalp, Ibrahim E. Bagci TOBB University of Economics and Technology.

1-1 CMPE 259 Sensor Networks Katia Obraczka Winter 2005 Transport Protocols II.

Opportunistic Routing in Multi-hop Wireless Networks Sanjit Biswas and Robert Morris MIT CSAIL

TCP with Adaptive Pacing for Multihop Wireless Networks Sherif M. EIRakabawy, Alexander Klemm, Christoph Lindemann University of Dortmund Germany Proceedings.

A Transmission Control Scheme for Media Access in Sensor Networks Alec Woo, David Culler (University of California, Berkeley) Special thanks to Wei Ye.

FBRT: A Feedback-Based Reliable Transport Protocol for Wireless Sensor Networks Yangfan Zhou November, 2004 Supervisors: Dr. Michael Lyu and Dr. Jiangchuan.

1 A Distributed Algorithm for Joint Sensing and Routing in Wireless Networks with Non-Steerable Directional Antennas Chun Zhang *, Jim Kurose +, Yong Liu.

Mehmet C. Vuran Vehbi C. Gungor Özgür B. Akan School of Electrical & Computer Engineering Georgia Institute of Technology Atlanta, GA {mcvuran,

Adaptive flow control via Interest Aggregation in CCN by Dojun Byun, Byoung-joon, Myeong-Wuk Jang Samsung Electronics, Advanced Institute of Technology.

Secure Data Aggregation in Wireless Sensor Networks: A Survey Yingpeng Sang, Hong Shen Yasushi Inoguchi, Yasuo Tan, Naixue Xiong Proceedings of the Seventh.

A Transmission Control Scheme for Media Access in Sensor Networks Alec Woo and David Culler University of California at Berkeley Intel Research ACM SIGMOBILE.

A Distributed Scheduling Algorithm for Real-time (D-SAR) Industrial Wireless Sensor and Actuator Networks By Kiana Karimpour.

Understanding the Real-World Performance of Carrier Sense MIT Computer Science and Artificial Intelligence Laboratory Networks and Mobile Systems

CSE 6590 Fall 2010 Routing Metrics for Wireless Mesh Networks 1 4 October, 2015.

An End-to-end Approach to Increase TCP Throughput Over Ad-hoc Networks Sarah Sharafkandi and Naceur Malouch.

DRAND: Distributed Randomized TDMA Scheduling for Wireless Ad- Hoc Networks Injong Rhee (with Ajit Warrier, Jeongki Min, Lisong Xu) Department of Computer.

 Network Segments  NICs  Repeaters  Hubs  Bridges  Switches  Routers and Brouters  Gateways 2.

Wireless Sensor Networks COE 499 Energy Aware Routing

ACN: RED paper1 Random Early Detection Gateways for Congestion Avoidance Sally Floyd and Van Jacobson, IEEE Transactions on Networking, Vol.1, No. 4, (Aug.

Copyright: S.Krishnamurthy, UCR Power Controlled Medium Access Control in Wireless Networks – The story continues.

1 Siphon: Overload Traffic Management using Multi-Radio Virtual Sinks in Sensor Networks Chieh-Yih Wan, Intel Research, et al. SenSys ’05 Presented by.

Integrated Relay Architecture for IEEE m Systems Document Number: S802.16m-07_299 Date Submitted: November 12, 2007 Source: Sassan Ahmadi

Congestion Control in CSMA-Based Networks with Inconsistent Channel State V. Gambiroza and E. Knightly Rice Networks Group

Cross-layer Packet Size Optimization for Wireless Terrestrial, Underwater, and Underground Sensor Networks IEEE INFOCOM 2008 Mehmet C. Vuran and Ian F.

CSE 6590 Fall 2009 Routing Metrics for Wireless Mesh Networks 1 12 November, 2015.

Interference-Aware Fair Rate Control in Wireless Sensor Networks by Sumit Rangwala, Ramakrishna Gummadi, Ramesh Govindan and Konstantinos Psounis in ACM.

Mitigating Congestion in Wireless Sensor Networks Bret Hull, Kyle Jamieson, Hari Balakrishnan Networks and Mobile Systems Group MIT Computer Science and.

Localized Algorithm for Aggregate Fairness in Wireless Sensor Networks Authors : Shigang Chen, Zhan Zhang CISE university of Florida CISE university of.

SRL: A Bidirectional Abstraction for Unidirectional Ad Hoc Networks. Venugopalan Ramasubramanian Ranveer Chandra Daniel Mosse.

SenProbe: Path Capacity Estimation in Wireless Sensor Networks Tony Sun, Ling-Jyh Chen, Guang Yang M. Y. Sanadidi, Mario Gerla.

Rate-Based Channel Assignment Algorithm for Multi-Channel Multi- Rate Wireless Mesh Networks Sok-Hyong Kim and Young-Joo Suh Department of Computer Science.

Illinois Center for Wireless Systems Wireless Networks: Algorithms and Optimization R. Srikant ECE/CSL.

Speaker: Yi-Lei Chang Advisor: Dr. Kai-Wei Ke 2012/05/15 IPv6-based wireless sensor network 1.

IEEE j Relay-Based Wireless Access Networks VASKEN GENC, SEAN MURPHY, YANG YU, AND JOHN MURPHY, UNIVERSITY COLLEGE DUBLIN SCHOOL OF COMPUTER SCIENCE.

An Energy Efficient MAC Protocol for Wireless LANs, E.-S. Jung and N.H. Vaidya, INFOCOM 2002, June 2002 吳豐州.

M. Veeraraghavan (originals by J. Liebeherr) 1 Need for Routing in Ethernet switched networks What do bridges do if some LANs are reachable only in multiple.

Chapter 7 OSI Data Link Layer.

Efficient Resource Allocation for Wireless Multicast De-Nian Yang, Member, IEEE Ming-Syan Chen, Fellow, IEEE IEEE Transactions on Mobile Computing, April.

Mitigating starvation in Wireless Ad hoc Networks: Multi-channel MAC and Power Control Adviser : Frank, Yeong-Sung Lin Presented by Shin-Yao Chen.

An Enhanced Cross-Layer Protocol for Energy Efficiency in Wireless Sensor Networks Jaehyun Kim, Dept. of Electrical & Electronic Eng., Yonsei University;

DRAND: Distributed Randomized TDMA Scheduling for Wireless Ad-Hoc Networks Injong Rhee (with Ajit Warrier, Jeongki Min, Lisong Xu) Department of Computer.

Distributed Topology Control In Wireless Sensor Networks with Assymetric Links Presenter: Himali Saxena.

Critical Area Attention in Traffic Aware Dynamic Node Scheduling for Low Power Sensor Network Proceeding of the 2005 IEEE Wireless Communications and Networking.

Mitigating Congestion in Wireless Sensor Networks Bret Hull, Kyle Jamieson, Hari Balakrishnan MIT Computer Science and Artificial Intelligence Laborartory.

1 Post Lunch Session Cooperative Strategies and Optimal Scheduling for Tree Networks Alexandre de Baynast †, Omer Gurewitz ‡, Edward W. Knightly ‡ † RWTH.

Optimization-based Cross-Layer Design in Networked Control Systems Jia Bai, Emeka P. Eyisi Yuan Xue and Xenofon D. Koutsoukos.

MAC Protocols for Sensor Networks

MAC Protocols for Sensor Networks

Transport layer.

SENSYS Presented by Cheolki Lee

Mobile and Wireless Networking

Tarun Banka Department of Computer Science Colorado State University

Date Submitted: [November 9, 2009]

Date Submitted: [November 9, 2009]

Presentation transcript:

Distributed Hop-by-Hop Rate Adjustment for Congestion Control in Sensor Networks Presented by: Manmohan Voniyadka Sapna Dixit Vipul Bhasin Vishal Kumar Singh

Agenda Problem description Solution requirements Algorithm description Congestion pricing scheme Rate adjustment using price of congestion Protocol details Open Issues Schedules and Work Distribution

Problem Description Rate Adjustment to avoid congestion Calculation of congestion pricing via a distributed mechanism

Solution Requirements Develop a congestion pricing scheme Develop a relationship between rate and the congestion pricing. Modify CODA Protocol to incorporate these changes

Congestion Pricing Scheme Factors for pricing MAC utilization. Congestion Price at Downstream Nodes. Calculate a cumulative congestion pricing factor. Calculate pricing factor in a distributed manner. Weigh the pricing on congestion nodes appropriately.

Congestion Pricing Calculation Cumulative Congestion Pricing: w i – relative weight of downstream node, i w i = N is the N th node from the congested node cp i congestion pricing at the i th node p j is a marking function (As given in [1])

Rate Adjustment Using Congestion Pricing Use an AIMD Strategy:

Protocol Details Conditions for Backpressure Origination Send backpressure when threshold is exceeded as done in CODA Threshold based on channel sampling Header Format Changes Extra field for price of congestion value in backpressure messages End-to-End Loop Control

Open Issues Relative weight in Congestion pricing is only based on congestion price at downstream nodes, Need to add Transmission rate at i th node as factor in weight. Whether to use price of congestion for end to end loop control for controlling the source rate during persistent congestion. What happens with Asymmetric links ?

Changes to existing CODA Changes in Suppression Message generation. Threshold based on MAC Utilization / channel Sampling. Calculate and Send Congestion Price. Changes in ReceiveBackPressure Message -> AdjustSourceRate.

Glossary CP j = P (j) * MAC Utilization (j). CP j is the congestion price for using node j per unit time. P(j) is the marking function at node j and determines the fraction of flow to be marked. MAC Util is the fraction of time node j spends in receiving and re- transmitting to next hop. P (j) = P (j) = (y - t j ) / y y is sum of MAC utilization time by all flows at node j. t j is a parameter for controlling MAC time utilization. P (j) indicates fraction of flow exceeding the threshold parameter. If link quality is bad, We make t j << 1 for lower MAC time utilization.

References [1] Chieh-Yih Wan, Shane B. Eisenman and Andrew T. Campbell, “CODA: Congestion Detection and Avoidance in Sensor Networks”, ACM SenSys 2003, November 2003.CODA: Congestion Detection and Avoidance in Sensor Networks [2] Y. Yi and S. Shakkottai. Hop-by-hop Congestion Control over a Wireless Multi-hop Network,“ IEEE INFOCOM, Hop-by-hop Congestion Control over a Wireless Multi-hop Network