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1 Exploiting Heterogeneity for Routing in Wireless Sensor Networks CENS Seminar Series 6 October 2006 Thanos Stathopoulos CENS Systems Lab [email protected]

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Page 1: 1 Exploiting Heterogeneity for Routing in Wireless Sensor Networks CENS Seminar Series 6 October 2006 Thanos Stathopoulos CENS Systems Lab thanos@cs.ucla.edu

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Exploiting Heterogeneity for Routing in Wireless Sensor Networks

CENS Seminar Series

6 October 2006

Thanos Stathopoulos

CENS Systems Lab

[email protected]

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Talk Outline

• Overview of Heterogeneous Wireless Sensor Networks– Problem Statement

• Tier 1: Centralized Routing for Mote Networks• Tier 2: End-to-End Routing for Dual-Radio Sensor Networks• Conclusion

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Heterogeneity in WSNs

• WSNs in 2000: Homogeneous– Single (uniform) platform per research group– Peer design: All nodes in the network share the same

functionality

• WSNs in 2006: Heterogeneous– Tier-1: mote-class devices– Tier-2: microservers– Discrete tasks: nodes in the network treated differently

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Problem Statement

• WSN architectures becoming heterogeneous

• Should network protocol design be homogeneous or heterogeneous?

• Design with heterogeneity in mind or mask it?

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A closer look at the hardware platforms:motes and microservers

• Microserver advantages– High-bandwidth radios– Storage– CPU power– I/O interfaces– Can use “traditional” OS– Relatively easy to program

• Microserver challenges– Power consumption– Infrastructure cost

• Mote advantages– Low cost– Low power consumption– High spatial density

• Mote challenges– Very limited storage (RAM, EEPROM)– More difficult to program– Very limited computational power– Low-bandwidth radios

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Why heterogeneous design?

• Neither platform by itself can sufficiently meet all application requirements

• “Use each platform for what it’s good for, not for everything”– Successfully applied to other systems i.e. Internet

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Focus of this talk

• “Exploit heterogeneity for routing in wireless sensor networks”– Use one platform’s advantage to offset the other

platform’s disadvantage

• Can often lead to performance improvements– Demonstrated through two separate protocol

designs• Mote tier: Centralized routing• Microserver tier: end-to-end routing for dual-radio duty-

cycled microservers

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Tier 1: Centralized Routing for Mote Networks

• Overview of Heterogeneous Wireless Sensor Networks• Tier 1: Centralized Routing for Mote Networks

– Mote routing overview

– Problem description: distributed routing for motes

– Proposed solution: CentRoute

– CentRoute design details

– Performance evaluation

• Tier 2: End-to-End Routing for Dual-Radio Sensor Networks• Conclusion

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Overview: Differences between traditional and WSN routing

• Traditional routing– Any-to-any– Reliable links– Optimized for delay, path length, throughput

• WSN routing– Mostly many-to-few or many-to-one– Unreliable links– Optimized for energy consumption

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Overview: Mote-based WSN Routing

• Established mote-based WSN routing: Tree-based, Distributed, Proactive

– Tree-based: Data usually flows from leaves to root(s)

– Distributed: Each node makes its own decisions • Uses information from neighboring nodes

• Distance-Vector based

– Proactive: Paths continuously maintained• Continuously evaluate “best path”

• Examples:– MintRoute (popular mote routing protocol)– Directed diffusion (microserver-based but mote

implementations exist)

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Problems with existingmote routing protocols

• Mote-specific problems:– Distributed decision making in conjunction with storage

constraints leads to routing instabilities and inconsistencies

– Limited RAM also creates scalability challenges in terms of network density and network size

• Additional problems– Proactive nature leads to increased energy consumption– Distance-vector leads to count-to-infinity scenarios and

routing loops

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Problems in more detail:Distributed decision making under RAM constraints

• Selection of the next hop to a destination is based on neighbor table– Memory requirements are O(neighborhood size)

• Memory constraints place upper bound on table size– Cache eviction policies used when capacity is exceeded (MintRoute)

• Subject to thrashing, especially in dense networks• Leads to routing instabilities (“flapping”)

• Independent decisions by nodes based on artificially constrained information lead to inconsistencies

A BNode A has node B in neighbor table and as a next hop to a destination

Node B doesn’t have node A in neighbor table and thus doesn’t forward the packet further

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Proposed solution: Centralized Routing

• Exploit heterogeneity: utilize microservers as routing decision points– Remove decisions from individual motes– Centralize the decision-making on the microservers

• Not resource constrained• Natural centralization points due to tree-based nature

• Centralization refers to a single tree– Multiple trees can exist, each rooted at a different sink– Multiple trees improve performance and lead to better scaling

• ExScal• Tenet

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Disadvantages of Centralized Routing

• Centralization point: Single-point-of-failure– A problem with all tree-based routing protocols

– Solution: support for multiple sinks• Data will be routed to alternative sink if primary sink fails• Standard practice even in distributed protocols (Directed Diffusion,

Multihop, Drain etc)

• Potentially high control overhead– Control data needs to be forwarded back to the central point

• Scales poorly with path length

– Potential solution: on-demand protocol• No periodic control messages• Still an issue in long, unreliable paths

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CentRoute: Centralized on-demandrouting protocol for motes

• Addresses mote-based routing problems– Minimizes routing inconsistencies, including loops– Minimizes memory (state) requirements on motes – Increases routing stability– Can scale to dense networks

• Provides additional functionality– Bidirectional unicast routing (to and from the sink)– Global view of the entire mote network at each sink

• Uses StateSync for reliable sink state dissemination

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CentRoute design overview

• Runs on both motes and their sink (microserver)– Motes forward control data to microserver– Decision-making logic implemented exclusively on microserver

• On-demand protocol– Tree maintained by data packets

• Dynamic single-sink support– Sink selected at runtime– At-most-one protocol

• Motes only send data to (and keep state for) one sink at a time

– Multi-sink ambiguity resolved in microserver tier• StateSync(*) used for inter-sink communication

• Uses Source Routing

* StateSync is work done by Lewis Girod

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CentRoute design: Tree Formulation

CentRoute Motes that aren’t part of a tree periodically broadcast “join request” beacons.

A mote receiving a join beacon will only forward it if it has a unicast path to the sink.

A sink receiving a join request will send a source-routed unicast “join reply” to the requesting mote thus grafting it to the tree.

Motes receiving the join reply will set their “next hop” to be the mote that forwarded them the join reply

A sink receiving multiple join requests from a mote will select the “best path” to send the reply to, based on its routing metric

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CentRoute design: Path Maintenance

• Paths in CentRoute maintained by data packets– Tradeoff: reduced control overhead vs potential higher path repair

time

• Link-layer ACKs and retransmissions used to determine if next hop is valid– Each data packet is retransmitted N times– If link to parent fails (no ACK received), mote invalidates path and

invokes join mechanism again

• CentRoute doesn’t attempt to find better path once one has been established– Only “bad news” can force a path to change– Tradeoff: path stability vs potential sub-optimal paths

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CentRoute: Performance Evaluation

• Simulation and testbed experiments to evaluate:– Network connectivity– Control overhead– Performance in sparse, long networks– Convergence time– Path length and stability– Inconsistencies and loops

• Simulation scenario:– 100 motes arranged in a 100x100 grid– 1 sink in the middle of the top row– Adjusted power to control mote neighbor density:

• Number of motes in neighborhood with average link quality of 70% or better– 3 hour-long experiments

• Performance comparison with MintRoute and Multihop

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Centroute Performance:Network Connectivity

• At very low densities, CentRoute’s performance suffers• At low and medium densities, both CentRoute and MintRoute can

maintain 100% connectivity• At higher densities, CentRoute maintains 100% connectivity while

MintRoute’s performance suffers due to its linear scaling properties

CentRoute stays at 100%

MintRoute drops to 90%

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CentRoute performance: Control Overhead

• At very low densities, CentRoute has a high overhead– Sparse network leads to longer paths which incur higher overhead

• As density increases, CentRoute’s overhead is 5 times less than that of the DV proactive protocols.– On-demand nature

CentRoute at 0.3 b/s/m

Mintroute at 4 b/s/m

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CentRoute PerformancePath Inconsistencies and Loops

• Inconsistency: source mote believes it has a route to the sink but that opinion is not shared by all motes along the path.

– A loop is a special kind of inconsistency

• CentRoute exhibited no inconsistencies and no loops– Reasons: centralized decision making, sink-delegated paths, fast broken

path notification and source routing

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CentRoute performance:Convergence Time

• CentRoute can quickly connect a significant part of the network– No need to wait for periodic link estimator to “warm up”

• Phased join operation– Nodes near the sink connect quickly– Linear latency cost for modes further away from the sink

20% in 10 seconds

80% in ~60 seconds

100% in 150 seconds

20% in 150 seconds

80% in ~180 seconds

100% in 210 seconds

CentRoute MintRoute

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CentRoute Summary

• A centralized, on-demand routing protocol for motes

• Based on a heterogeneous design– Exploits heterogeneity by centralizing routing decisions on the

microserver– Alleviates hardware limitations of motes

• Addresses problems of current mote routing protocols– Scales well with density

• More than 99% connectivity in medium and high densities

– Energy and memory efficient• As low as 0.3 bytes/sec/mote transmission cost

• Constant RAM requirements on motes

– Robust and stable• Very stable paths, loop-free

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Tier 2: End-to-End Routing for Dual-Radio Sensor Networks

• Overview of Heterogeneous Wireless Sensor Networks• Tier 1: Centralized Routing for Mote Networks• Tier 2: End-to-End Routing for Dual-Radio Sensor Networks

– Problem description: routing for duty-cycled nodes

– Proposed solution: using the low-power radio

– Wake-path design

– Performance evaluation

• Conclusion

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Overview: Duty Cycling in the Microserver Tier

• Microserver resources come at a price: energy consumption– CPU, RAM, network interface, peripherals

• Line-powering not always possible– Outdoors deployments, infrastructure costs

• Solution: duty-cycling– Turn off radio, put CPU to sleep when not needed

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Problem Description:Routing in Duty Cycled Nodes

• Problem: Creating an end-to-end multihop path in the presence of duty-cycled microservers while minimizing– Energy consumption

– Data transmission latency

• Example applications– Seismic event detection

– Intrusion detection and tracking

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Potential solution: Periodic wakeup

• Nodes periodically wake up to send data– Well-known solution used in e.g. TDMA MACs

• Wakeup schedule can be static or adaptive– Works well if a model for the observed phenomenon exists

or can be learned

• Tradeoff: energy efficiency vs event (and data) latency– Periodic algorithm cannot always provide both

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Proposed solution overview: Using a second, low-power radio

• Wake-path: wake up nodes along the expected 802.11 path by using a low-power radio

• Exploit heterogeneity: use the low-power advantages of motes to offset the disadvantages of microservers

• Use mote-class devices to:– Remain vigilant for large periods of time while

microservers are asleep– Wake up the host microserver when needed– Coordinate with other motes to wake up the microservers

required for the multihop path

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Wake-path: Assumptions

• Each microserver has a mote-class device attached– Either Stargate+mote, or LEAP nodes

• The MCU that controls the low-bandwidth radio is not put to sleep– Can at any point wake up the main CPU

• The low-bandwidth network is connected– Required if the low-bandwidth network is to be used as a control channel

• No-partition assumption does not imply that the two network topologies match!

– Two different, independent routing protocols used– Radios can have similar ranges, or– The low-bandwidth topology needs to be sufficiently augmented by adding

standalone motes

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Wake-path design: Establishing a Path

• Microserver wakes up based on an external event (i.e. sensor input)

• Microserver uses low-bandwidth radio to request a multihop path via the topology controller

• Controller uses 802.11 routing information to decide which microservers to wake up

• Controller sends messages via the mote network to required microservers

• Once all required microservers are up, controller informs the source and data transfer can begin over 802.11

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Performance Evaluation Overview

• Wake-path compared to alternative approaches

• Analysis: Simple numerical models to determine energy consumption of each approach– Studies effects of event frequency, data size and network

topology– Quantifies impact of transition constants

• Testbed evaluation– Energy and latency evaluation of Wake-path– Testbed characterization

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Performance evaluation:Alternative approaches

• Always-On: All radio and CPU resources on all the time– No need for a second radio

– Lowest latency, highest energy consumption

• Periodic-wakeup: Nodes periodically wake up to send data– No need for a second radio

– Energy/latency tradeoff

• Wake-all: Nodes are all woken up when an event occurs– Needs a second radio to inform nodes about wakeup

– Wakes up all nodes in the network

– Low latency, energy consumption depends on size of the network

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Numerical Analysis:The impact of transition constants

• High-bandwidth radio more efficient if:– Powerdown-to-on: Data size > 464 KBytes

– Suspend-to-on: Data size > 63.8 KBytes

– Testbed results: high-bandwidth radio increasingly more efficient in multihop case

• Effect of different power saving modes on energy efficiency:– Suspend preferred to powerdown mode in medium event

frequencies:• 6 events/hour for 400 Kbytes of data

– Powerdown mode better for smaller frequencies

– Above 100 events/hour: no duty-cycling better

– Increasing the data size results in even smaller event thresholds

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Experimental Testbed Setup

• 11 Stargates with attached Mica2 motes

• 13 extra standalone motes providing strong connectivity for the CC1000 network

• DSR in 802.11 network– 4 MB data transfers to node 169 using TCP

• Performance comparison of Wake-path vs Wake-all– Energy consumption– Latency– Reliability

• Testbed characterization– Multihop efficiency of the two radios– Topology correlation

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Wake-path performance: Energy Consumption

• Wake-path consistently better than Wake-all– Less pronounced difference at larger path lengths

• Path-to-total-nodes ratio increases

– Expected result from numerical models

• Significant energy consumption for both mechanisms in larger path lengths– Byproduct of sparsely connected 802.11 testbed and TCP– Still, energy consumption much higher than model

More than 60% energy savings

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Wake-Path performance: Latency

• Wake-path adds low extra latency compared to Wake-all– Grows almost linearly with number of nodes in the path

• Considerable extra latency added by DSR– Conservative timers– Optimization: disable DSR path establishment

• Carry next hop information in low-bandwidth radio control packets

• Considerable data transfer latency due to poor links and TCP

~6 sec

DSR latency due to internal timers

Large latency due to poor links and TCP

retransmissions

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End-to-end routing for duty-cycled microservers: Summary

• Wake-path: Topology control protocol for duty-cycled dual-radio microservers– Enables low-latency and low energy consumption multihop

path construction over 802.11• Uses low-bandwidth radios as multihop control channel

• Selectively wakes up only the nodes required for the path

• Numerical and testbed performance evaluation– Energy savings up to 60% compared to waking up all the

nodes– Low additional latency: 6 sec compared to wake-all, 9 sec

compared to always-on

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Conclusion

• Heterogeneous WSNs– Different platforms with distinct advantages and

disadvantages

• Exploiting heterogeneity for routing in WSNs– Take advantage of different capabilities of platforms in

heterogeneous system– Can often lead to performance improvements

• Mote tier: CentRoute

• Microserver tier: end-to-end routing for duty-cycled microservers

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The End

Thank you!