Wireless Communication Issues in Sensor Networks

Slides:



Advertisements
Similar presentations
Ch. 12 Routing in Switched Networks
Advertisements

Nick Feamster CS 4251 Computer Networking II Spring 2008
Distributed Assignment of Encoded MAC Addresses in Sensor Networks By Curt Schcurgers Gautam Kulkarni Mani Srivastava Presented By Charuka Silva.
Mobile and Wireless Computing Institute for Computer Science, University of Freiburg Western Australian Interactive Virtual Environments Centre (IVEC)
1 S4: Small State and Small Stretch Routing for Large Wireless Sensor Networks Yun Mao 2, Feng Wang 1, Lili Qiu 1, Simon S. Lam 1, Jonathan M. Smith 2.
Winter 2004 UCSC CMPE252B1 CMPE 257: Wireless and Mobile Networking SET 3f: Medium Access Control Protocols.
Understanding Packet Delivery Performance in Dense Wireless Sensor Networks Jerry Zhao & Ramesh Govindan SenSys ‘03.
A Transmission Control Scheme for Media Access in Sensor Networks Lee, dooyoung AN lab A.Woo, D.E. Culler Mobicom’01.
Monday, June 01, 2015 ARRIVE: Algorithm for Robust Routing in Volatile Environments 1 NEST Retreat, Lake Tahoe, June
Mobile and Wireless Computing Institute for Computer Science, University of Freiburg Western Australian Interactive Virtual Environments Centre (IVEC)
Beneficial Caching in Mobile Ad Hoc Networks Bin Tang, Samir Das, Himanshu Gupta Computer Science Department Stony Brook University.
More routing protocols Alec Woo June 18 th, 2002.
1 Link Characteristics in Sensor Networks. 2 Why Such a Study? (in)validate whether the basic model used in design is accurate or not  Remember you have.
CS 410/510 Sensor Networks Portland State University Lecture 3 Wireless Communication.
Robust Topology Control for Indoor Wireless Sensor Networks Greg Hackmann, Octav Chipara, and Chenyang Lu SenSys 2009 S Slides from Greg Hackmann at Washington.
Taming the Underlying Challenges of Reliable Multihop Routing in Sensor Networks.
Towards a Connectivity-Based, Reliable Routing Framework Alec Woo Winter NEST Retreat 2004 UC Berkeley.
Reliability-based Multihop Routing for Sensor Networks Alec Woo David Culler NEST Winter Retreat January 16 th, 2003.
A Transmission Control Scheme for Media Access in Sensor Networks Presented by Jianhua Shao.
Adaptive Self-Configuring Sensor Network Topologies ns-2 simulation & performance analysis Zhenghua Fu Ben Greenstein Petros Zerfos.
Multi-hop Data Collection Alec Woo, UCB Terence Tong, UCB Phil Buonadonna, Intel Nest Summer Retreat 2003 June 18 th, 2003.
A Transmission Control Scheme for Media Access in Sensor Networks Alec Woo, David Culler (University of California, Berkeley) Special thanks to Wei Ye.
Empirical Analysis of Transmission Power Control Algorithms for Wireless Sensor Networks CENTS Retreat – May 26, 2005 Jaein Jeong (1), David Culler (1),
Jennifer Rexford Princeton University MW 11:00am-12:20pm Wide-Area Traffic Management COS 597E: Software Defined Networking.
Ad Hoc Wireless Routing COS 461: Computer Networks
Itrat Rasool Quadri ST ID COE-543 Wireless and Mobile Networks
Wireless Networked Sensors Routing Challenges Mikhail Nesterenko In this presentation I used the material from a presentation by David Culler, USB
A Transmission Control Scheme for Media Access in Sensor Networks Alec Woo and David Culler University of California at Berkeley Intel Research ACM SIGMOBILE.
Lecture 4: Link Characteristics Anish Arora CIS788.11J Introduction to Wireless Sensor Networks Material uses slides from Alberto Cerpa, ZhaoGovindan,
A High-Throughput Path Metric for Multi-Hop Wireless Routing Presenter: Gregory Filpus Slides borrowed and modified from: Douglas S. J. De Couto MIT CSAIL.
Copyright: S.Krishnamurthy, UCR Power Controlled Medium Access Control in Wireless Networks – The story continues.
A High-Throughput Path Metric for Multi-Hop Wireless Routing Douglas S. J. De Couto MIT CSAIL (LCS) Daniel Aguayo, John Bicket, and Robert Morris
Link Estimation, CTP and MultiHopLQI. Learning Objectives Understand the motivation of link estimation protocols – the time varying nature of a wireless.
ENERGY-EFFICIENT FORWARDING STRATEGIES FOR GEOGRAPHIC ROUTING in LOSSY WIRELESS SENSOR NETWORKS Presented by Prasad D. Karnik.
A High-Throughput Path Metric for Multi- Hop Wireless Routing Douglas S. J. De Couto, Daniel Aguayo, John Bicket, Robert Morris MIT Computer Science and.
GPSR: Greedy Perimeter Stateless Routing for Wireless Networks EECS 600 Advanced Network Research, Spring 2005 Shudong Jin February 14, 2005.
Mitigating Congestion in Wireless Sensor Networks Bret Hull, Kyle Jamieson, Hari Balakrishnan Networks and Mobile Systems Group MIT Computer Science and.
SRL: A Bidirectional Abstraction for Unidirectional Ad Hoc Networks. Venugopalan Ramasubramanian Ranveer Chandra Daniel Mosse.
11/25/2015 Wireless Sensor Networks COE 499 Localization Tarek Sheltami KFUPM CCSE COE 1.
Routing and Clustering Xing Zheng 01/24/05. References Routing A. Woo, T. Tong, D. Culler, "Taming the Underlying Challenges of Reliable Multihop Routing.
Self-stabilizing energy-efficient multicast for MANETs.
Mitigating Congestion in Wireless Sensor Networks Bret Hull, Kyle Jamieson, Hari Balakrishnan MIT Computer Science and Artificial Intelligence Laborartory.
Spring Routing: Part I Section 4.2 Outline Algorithms Scalability.
Distance Vector Routing
Medium Access in Sensor Networks. Presented by: Vikram Shankar.
Performance Comparison of Ad Hoc Network Routing Protocols Presented by Venkata Suresh Tamminiedi Computer Science Department Georgia State University.
Frame counter: Achieving Accurate and Real-Time Link Estimation in Low Power Wireless Sensor Networks Daibo Liu, Zhichao Cao, Mengshu Hou and Yi Zhang.
MAC Protocols for Sensor Networks
William Stallings Data and Computer Communications
MAC Protocols for Sensor Networks
IHP: Innovation for High Performance Microelectronics
Delay-Tolerant Networks (DTNs)
Transport layer.
Dynamic Fine-Grained Localization in Ad-Hoc Networks of Sensors
Data Collection and Dissemination
Sensor Network Routing
Intra-Domain Routing Jacob Strauss September 14, 2006.
Ramakrishna Gummadi, Ramesh Govindan, Konstantinos Psounis
by Saltanat Mashirova & Afshin Mahini
CS 410/510 Sensor Networks Portland State University
High Throughput Route Selection in Multi-Rate Ad Hoc Wireless Networks
Topology Control and Its Effects in Wireless Networks
Effective Replica Allocation
Data Collection and Dissemination
Routing.
Protocols.
Adaptive Topology Control for Ad-hoc Sensor Networks
Protocols.
Presentation transcript:

Wireless Communication Issues in Sensor Networks Alec Woo UC Berkeley October 2nd, 2003

Theme Explore underlying communication issues and their effects on high-level protocol design Single hop Zhao and Govindan, SenSys 2003 Extra: SCALE (Cerpa et al. CENS TR 2003) Network-level protocol multi-hop routing for data collection. (Woo et al., SenSys 2003)

Motivation Why do we care about all these details? we will experience it! if we want to implement our protocols actual deployment decision

Roadmap Single Hop packet loss characteristics Core dimensions Environment, distance, transmit power, temporal correlation, data rate, packet size Services for High Level Protocols/Applications Link estimation Neighborhood management Reliable Multihop Routing

Zhao’s Study Hardware MAC Encoding Environment Mica, RFM 433MHz TinyOS Mac (CSMA) Encoding Manchester (1:2) 4b/6b (1:1.5) SECDED (1:3) Environment Indoor, Open Structure, Habitat Environment

Indoor is the Harshest Linear topology over a hallway (0.5/0.25m spacing) 40% of the links have quality < 70% Lower transmit power yields smaller tail distribution SECDEC significantly helps to lower the heavy tail

Packet Loss and Distance Gray/Transitional Area ranges from 20% to 50% of the communication range Habitat has smaller communication range? Other evidence (Cerpa et al., Woo et al.) RFM: BAD RADIO??

ChipCon Radio (Cerpa et al.) Mica On Ceiling Higher transmit power doesn’t eliminate transitional region Range in (a) and (b) are the same? Indoor RFM result is worst than that in Zhao’s work cannot even see the effective region

Can better coding help? SECDED is effective if start symbol is detected but does not increase “communication range” Bit error rate (BER) is higher in transitional region Missing start symbol is fatal Better coding for start symbol?

Loss Variation (Cerpa et al.) Variation over distance and over time binomial approximation for variation over time? Zhao shows that SECDED helps decrease the variation over distance (but very large SD here)

Packet Loss vs. Workload Packet loss increases as network load increases But what is the network load? How many nodes are in range? Not sure! Is 0.5packets/s already in saturation? Difficult to observe is it hidden node terminal

Packet Loss vs. RSSI Low packet loss => good RSSI But not vice versa Too high a threshold limits number of links Network partition??

Other Findings Correlation of Packet Loss correlation at the gray (transitional) region for indoor Habitat: much less Independent losses are reasonable 50%-80% of the retransmissions are wasted Neighbor = hear a node once Asymmetric links are common > 10% of link pairs have link quality difference > 50% Cerpa et al. Moving a little bit doesn’t help Swap the two nodes, asymmetrical link swaps too i.e. not due to the environment

Packet Size (Cerpa et al.) Loss over distance is relatively the same for different packet size (25 bytes and 150 bytes) at different transmit power

Take Away Who to blame? What is the effective communication range? Radio? Similar results found over RFM and ChipCon radio Hardware calibration! Yeah!  Base-band radio Multi-path will remain unless spread-spectrum radio is used But 802.11 is also not ideal (Decouto et al. Mobicom 03) What is the effective communication range? What does it mean when you deploy a network What defines a neighbor? Why study high density sensor network? Break?

Roadmap Single Hop packet loss characteristics Core dimensions Environment, distance, transmit power, temporal correlation, data rate, packet size Services for High Level Protocols/Applications Link estimation Neighborhood management Reliable multihop routing for data collection

Link Quality Estimation Estimate rate of successful reception from neighboring nodes RSSI may not work well Neighbors exchange estimations to derive bi-directional link quality 2 Techniques: Passive vs. Active Key decision factor: broadcast medium Passive: snoop on neighbor packets

What is a good Estimator? For a given error bound and agility, yields the most stable estimation with the smallest memory footprint and the simplest algorithm Agility and stability are at odds with each other

Agility and Error Bound Simulation worst case: 10% error ~ 100 packet time Assuming IID Binomial model, by the central limit theorem Worst case (p = 0.5) requires 10% error with 90% confidence requires ~100 packet opportunities to learn For example: at 30sec/packet 50 minutes for 100 packets forwarding traffic helps to reduce this time but potentially a long delay Major disadvantage

Infer Packet Loss Packet sequence number for inferring packet loss Issue: cannot infer loss until hearing the next packet E.g. dead node or mobility Can infer losses based on time Assume minimum data rate is known Likely to be true in periodic data collection

WMEWMA Estimator Compute an average success rate over time, T, and smoothes with an exponentially weighted moving average (EWMA) Average calculation Packet Received over T divided by Max of Number of packets expected over T Number of packets sent over T suggested by sequence number Tuning parameters: T and history size of EWMA Performance Yields agile and stable estimations Uses constant memory, and is very simple

Neighbor Table Maintain link estimation statistics and routing information of each neighbor How large should this table be? O(cell density) * meta-data for each neighbor Issue: Density can be high but memory is limited At high density, many links are poor or asymmetric Question: Can we use constant memory to maintain a set of good neighbors regardless of cell density?

Neighborhood Management Question: when table becomes full, should we add new neighbor? If so, evict which old neighbor? Neighbor Goodness Basic one is link quality but it is unknown Signal strength is a hint Rely on frequency of packet reception Assume periodic data packets or beacons Similar to frequency estimation of data streams, or classical cache policy

Management Algorithm When we hear a node, if Eviction: (FREQUENCY) In table: increment a counter for this node Not in table Insert if table is not full down-sample if table is full If successful, insert only if some nodes can be evicted Eviction: (FREQUENCY) Decrement counter for each table entry Nodes with counter = 0 can be evicted Otherwise, all nodes stay in the table

Key Results FREQUENCY algorithm can effectively Routing simulation: utilize 50% to 70% of the table space to maintain a set of good neighbors while being adaptive to neighborhood changes Routing simulation: Neighbor goodness is augmented to avoid maintaining sibling nodes based on routing cost difference

Reliable Routing 3 core components for Routing Routing protocol Neighbor table management Link estimation Example Tree based routing for data collection Reliable end-to-end packet delivery with minimum number of transmissions (link retransmissions) Advocate stability Simple

Design Issues Shortest path alone yields poor end-to-end success rate Multi-hop over bad links has exponential loss effect Two approaches SP over some link quality threshold Minimum expected number of transmissions as routing cost Route damping New route is not evaluated on every route updates Link failure detection using consecutive packet loss leads to instability link quality characterization is better Queuing Policy Two queues Fair allocation between forwarding and originating traffic Cycles Detection vs. loop-free

SP with Threshold High threshold (e.g. 70%) fails to form a tree Works fine in simulation! link quality degrades when there is traffic High threshold leads to network partition Echo the observation made in Zhao’s work Lower threshold (e.g. 40%) is also problematic Tree prunes and rebuilds over time when traffic is high

MT No predefine threshold is necessary Captures both reliability and energy cost Routing cost builds upon individual estimations along the path Cost = hops + number of expected link retransmissions if link quality = 100%, MT reduces to normal SP routing

Methodology Graph analysis Network simulation Empirical evaluation Assuming packet loss are independent, following Binomial model Empirical evaluation On site connectivity vs. distance study Find minimum transmit power Transitional/gray area starts at average node distance

Findings (I) Hop distribution and success rate longer majority hop-count yields higher success Hop distribution and distance Evidence of long links, potentially reliable Retransmissions are not too effective MT yields ~80% success rate packets delivered only experience 1 retransmission along the path A maximum of 2 retransmission per hop can Needs a maximum of 3 per hop to achieve over 90% end-to-end success rate

Findings (II) Link failure detection with consecutive packet loss leads to instability Stability and Congestion link quality fluctuates at congestion period creates global instability BS can hear half the number of neighbors in the network even with a low power setting MT metrics build upon link estimations are stable No cycles are detected

Discussions (I) Passive snooping Neighborhood management argument What are the assumptions for this to work? Estimation takes too long Can we infer from BER before FEC? (tricky)? But missing start symbol is the major cause! Neighborhood management argument Do you buy it? Stability Do we care? Congestion How to avoid it? Scheduled communication?

Discussions (II) Can we define a hop? Deployment Overhead One hop neighbor? What is the averaged hop distance? Deployment What’s the expected hop-count? What distance or transmit power should we use? Overhead Anecdotal setting of route update rate Can it be adaptive?

Discussion (III) Power DSDV (Yarvis et al. ICPP Workshop 2002) No address on power management How does it work with scheduled communication which avoids overhearing? Potentially run over low-power listening What’s used in Great Duck Island DSDV (Yarvis et al. ICPP Workshop 2002) Different kinds of link estimation and routing cost Do we need to prevent cycle like DSDV in a relatively static network? N-to-N Routing?