Prof. Younghee Lee 1 1 u Lecture 15: MANET, Wireless Mesh and Sensor networks Prof. Younghee Lee Computer Networks.

1Prof. Younghee Lee1

Lecture 15: MANET, Wireless Mesh

and Sensor networks

Prof. Younghee Lee

Computer Networks


Taxonomy

WirelessNetworking

Multi-hop

Infrastructure-less(ad-hoc)

Infrastructure-based(Hybrid)

Infrastructure-less(MANET)

SingleHop

CellularNetworks Wireless Sensor

Networks(?)Wireless Mesh

Networks

Car-to-car Networks(VANETs)

Infrastructure-based(hub&spoke)

802.11 802.16 Bluetooth802.11


Mobile Ad hoc Networks

Not using a pre-existing infrastructure– traditional cellular systems (base station infrastructure)

May need multiple hops to reach a destination Applications

– Military environments: was major motivation» soldiers, tanks, planes

Need mobility, avoid SPF, rapidly deployable, Multi-hop to reach to person outside of LOS(line of sight), when existing infrastructure is unavailable

» Survivable Radio Network(SURAN), Global Mobile(GloMo) Information System

– Civilian environments» taxi cab network, automobile communications(Cellular + ad hoc+..)» Meetings/conferences, sports stadiums, super market, Hotel…» boats, small aircraft

– Emergency operations» search-and-rescue» policing and fire fighting

– Personal area networking» cell phone, laptop, head phone, wrist watch, multimedia devices» Wearable computing


Routing Protocols Proactive protocols

– Establish routes in advance– Determine routes independent of traffic pattern– Traditional link-state and distance-vector routing protocols are proactive– Table driven Routing protocol

» Destination Sequenced Distance Vector Routing(DSDV)» Clusterhead Gateway Switch Routing(CGSR)

Reactive protocols– Establish routes only if needed– Less routing overhead, but higher latency in establishing the path– Source-initiated on-demand

» AODV, DSR, LMR, TORA, ABR, SSR Hybrid protocols

– Proactive within a restricted geographic area, reactive if a packet must traverse several of these areas

– ZRP, LANMAR


Trade-Off Latency of route discovery

– Proactive protocols:Little or no delay for route determination» since routes are maintained at all times

– Reactive protocols: Significant delay in route determination» Employ flooding (global search)» Control traffic may be bursty

Overhead of route discovery/maintenance– Proactive protocols: Consume bandwidth to keep routes up-to-date

» Maintain routes which may never be used

– Reactive protocols: Lower overhead since routes are determined on demand

Which approach achieves a better trade-off depends on the traffic and mobility patterns– Low traffic with high mobility : Reactive– High traffic with low mobility : Proactive


Ad hoc routing protocols

Ad hoc routing protocols

Table-drivenSource-initiated

On-demand

DSDV WRP AODV ABRDSR LMR

TORA SSRCGSR


Proactive Protocols

Proactive schemes based on distance-vector and link-state mechanisms– Distance vector

» Finding shortest path to destination using the route information from neighbor nodes

Bellman-ford Count to infinity problem

– Link state» Each node advertise link information using flooding

» Each node calculate shortest path


Destination-Sequenced Distance-Vector (DSDV) [Perkins94Sigcomm]

Each node maintains a routing table which stores– next hop towards each destination

– a cost metric for the path to each destination

– a destination sequence number that is created by the destination itself

– Sequence numbers used to avoid formation of loops Each node periodically forwards the routing table to its neighbors

– Each node increments and appends its sequence number when sending its local routing table

– This sequence number will be attached to route entries created for this node Each route is tagged with a sequence number; routes with greater

sequence numbers are preferred: newer one When a node decides that a route is broken, it increments the sequence

number of the route and advertises it with infinite metric Node mobility : routing data update period


Destination-Sequenced Distance-Vector (DSDV)

Assume that node X receives routing information from Y about a route to node Z

Let S(X) and S(Y) denote the destination sequence number for node Z as stored at node X, and as sent by node Y with its routing table to node X, respectively

Node X takes the following steps:– If S(X) > S(Y), then X ignores the routing information received from Y

– If S(X) = S(Y), and cost of going through Y is smaller than the route known to X, then X sets Y as the next hop to Z

– If S(X) < S(Y), then X sets Y as the next hop to Z, and S(X) is updated to equal S(Y)

Avoid Count to infinity problem

X Y Z


Optimized Link State Routing (OLSR) [Jacquet00ietf]

Routers maintain awareness of current network topology by exchanging beacons(“HELLO messages”)

Each nodes tells the entire network about its immediate neighbors– So each node forms a picture of the entire network topology– Each node can then calculate the best route to any destination

Flooding the network with HELLO messages incurs too much overhead– OLSR uses multi-point relay(MPR) nodes to decrease the

number of unnecessary broadcasts (only selected nodes broadcast HELLO)


Optimized Link State Routing (OLSR) Multi-point relays of node X are its neighbors such that each two-hop neig

hbor of X is a one-hop neighbor of at least one multipoint relay of X– Each node transmits its neighbor list in periodic beacons, so that all nodes ca

n know their 2-hop neighbors, in order to choose the multipoint relays.– The sender can select its multipoint relays (MPR) based on the one hop node

which offer the best routes to the two hop nodes.– Upon receiving a packet, a node checks it's MPRSelector set to see if the sen

der has chosen the node as a MPR. If so, the packet is forwarded, else the packet is processed and discarded.

A

B F

C

D

E H

GK

J

Node that has broadcast state information from A


OLSR

OLSR floods information through the multipoint relays

The flooded itself is for links connecting nodes to respective multipoint relays

Routes used by OLSR only include multipoint relays as intermediate nodes


A simple, efficient LS type routing protocol FSR exchanges the entire link state information only with neighbors Link state exchange is periodical Periodical broadcasts of LS info are conducted in different frequencies

depending on the hop distances– Bigger hop distance : less frequent– Smaller hop distance : more frequent

for fairly large ad-hoc network

The bold entries in figure 2 are propagated to the neighbors at the highest frequency, as they have low hop counts. The GST entry shows the neighbors corresponding to each node in the network.

FSR (Fisheye State Routing)


Each node maintains 4 tables - Distance table, Routing table, Link-cost table & Message retransmission list table

Link changes are propagated using update messages sent between neighboring nodes

Hello messages are periodically exchanged between neighbors to ensure connectivity

Avoids count-to-infinity problem by forcing each node to check predecessor information

» checks for consistency of all its neighbors every time it detects a change in link of any of its neighbors

The Wireless Routing Protocol (WRP) (‘96)


TBRPF(Topology Broadcast Based on Reverse Path Forwarding)

Full-topology link-state protocol (unlike OLSR) Each link-state update is broadcast reliably along a dynamic

min-hop-path tree rooted at the source u of the update.


TBRPF(Topology Broadcast Based on Reverse Path Forwarding)

Consists of two modules: the neighbor discovery module (TND) and the routing module

TND send differential HELLO messages that reports only the changes of neighbors.

The routing module operates based on partial topology information

TBRPF only propagates LS updates in the reverse direction on the spanning tree formed by the minimum-hop paths.

Only the links that will result in changes to the source tree are included in the updates


Reactive Routing Protocols

On demand routing protocol Large, high mobility ad hoc network Source build routes on-demand by “flooding” Maintain only active routes Route discovery cycle Typically, less control overhead, better scaling

properties Drawback: route acquisition latency

DSR, AODV, LMR, TORA, ABR


Dynamic Source Routing (DSR)

When node S wants to send a packet to node D, but does not know a route to D, node S initiates a route discovery

Source node S floods Route Request (RREQ)

Each node appends own identifier when forwarding RREQ


Route Discovery in DSR

B

A

S E

F

H

J

D

C

G

IK

Represents transmission of RREQ

Z

YBroadcast transmission

M

N

L

[S]

[X,Y] Represents list of identifiers appended to RREQ



B

A

S E

F

H

J

D

C

G

IK

Z

Y

• Node D does not forward RREQ, because node D is the intended target of the route discovery

M

N

L

[S,E,F,J,M]



Destination D on receiving the first RREQ, sends a Route Reply (RREP)

RREP is sent on a route obtained by reversing the route appended to received RREQ

RREP includes the route from S to D on which RREQ was received by node D


Route Reply in DSR

B

A

S E

F

H

J

D

C

G

IK

Z

Y

M

N

L

RREP [S,E,F,J,D]

Represents RREP control message


Dynamic Source Routing (DSR)

Node S on receiving RREP, caches the route included in the RREP

When node S sends a data packet to D, the entire route is included in the packet header– hence the name source routing

Intermediate nodes use the source route included in a packet to determine to whom a packet should be forwarded


Data Delivery in DSR

B

A

S E

F

H

J

D

C

G

IK

Z

Y

M

N

L

DATA [S,E,F,J,D]

Packet header size grows with route length


Ad Hoc On-Demand Distance Vector Routing (AODV) [Perkins99Wmcsa]

DSR includes source routes in packet headers– Resulting large headers can sometimes degrade performance

AODV attempts to improve on DSR by maintaining routing tables at the nodes, so that data packets do not have to contain routes

When a node re-broadcasts a Route Request, it sets up a reverse path pointing towards the source– AODV assumes symmetric (bi-directional) links

When the intended destination receives a Route Request, it replies by sending a Route Reply

Route Reply travels along the reverse path set-up when Route Request is forwarded


Reverse Path Setup in AODV

B

A

S E

F

H

J

D

C

G

IK

• Node C receives RREQ from G and H, but does not forward it again, because node C has already forwarded RREQ once

Z

Y

M

N

L


Route Reply in AODV

B

A

S E

F

H

J

D

C

G

IK

Z

Y

Represents links on path taken by RREP

M

N

L


Forward Path Setup in AODV

B

A

S E

F

H

J

D

C

G

IK

Z

Y

M

N

L

Forward links are setup when RREP travels alongthe reverse path

Represents a link on the forward path

Routing table entries used to forward data packet.

Route is not included in packet header.


AODV and DSR Differences DSR uses source routing; AODV uses next hop entry

DSR uses route cache; AODV uses route table

DSR route cache entries do not have lifetimes; AODV route table entries do have lifetimes

DSR nodes respond to each RREQ duplicate; AODV nodes only respond to first RREQ, unless one

arrives along a better path


DYMO – an integration of AODV and DSR

The Dynamic MANET On-demand (DYMO) routing protocol

Descendant of DSR and AODV a rewrite of AODV, using different terminology and packet

format, but having the same basic functionality IETF Draft submitted by MANET WG

– Work in progress => 4th revision Makes use of the generalised MANET packet format

– Extensible through tlvs

Path accumulation (cf. DSR) is optional No precursor list in routing table entries


DYMO – Route Discovery

Same as for AODV, except:– RREQ and RREP share the same message format

– Address blocks can be added to indicate path accumulation along route or addresses that need processing at each node

Originating node causes dissemination of a Routing Message (RM) throughout the network to find the target node.

Each intermediate node creates a route to the originating node. When target node receives the RM it responds with RM unicast toward

originating node. During propagation each node creates a route to the target node. When the originating node is reached routes have been established

between the originating node and the target node in both directions.


DYMO – Route Management

To react quickly to changes in the network topology nodes should maintain their routes and monitor their links.

When a packet is received for a route that is no longer available the source of the packet should be notified.

RERR) is sent to the packet source to indicate the current route is broken.

Once the source receives the RERR, it will re-initiate route discovery if it still has packets to deliver.


Flooding of Control Packets

How to reduce the scope of the route request flood ?– LAR [Ko98Mobicom]– Query localization [Castaneda99Mobicom]

How to reduce redundant broadcasts ?– The Broadcast Storm Problem [Ni99Mobicom]


(Flooding) Advantages

– Simplicity– May be more efficient than other protocols when rate of information

transmission is low enough» small data packets relatively infrequently, and many topology changes occur between

consecutive packet transmissions

– Potentially higher reliability of data delivery» Multiple path

Disadvantages– Potentially, very high overhead– Potentially lower reliability of data delivery

» Flooding uses broadcasting -- hard to implement reliable broadcast delivery without significantly increasing overhead

– Broadcasting in IEEE 802.11 MAC is unreliable» nodes J and K may transmit to node D simultaneously, resulting in loss of the packet

Flooding of Control Packets– The control packets are used to discover routes


Solutions for Broadcast Storm

Probabilistic scheme: On receiving a route request for the first time, a node will re-broadcast (forward) the request with probability p

Also, re-broadcasts by different nodes should be staggered by using a collision avoidance technique (wait a random delay when channel is idle)– this would reduce the probability that nodes B and C would forward

a packet simultaneously in the previous example Counter-Based Scheme: If node E hears more than k

neighbors broadcasting a given route request, before it can itself forward it, then node E will not forward the request– Intuition: k neighbors together have probably already forwarded the

request to all of E’s neighbors


Temporally-Ordered Routing Algorithm(TORA) [Park97Infocom]

TORA modifies the partial link reversal method to be able to detect partitions

When a partition is detected, all nodes in the partition are informed, and link reversals in that partition cease

Gradient based. Height Hi (τi, oidi, ri, δi, i)

– δi : order nodes w.r.t. common reference level


Temporally-Ordered Routing Algorithm(TORA) [Park97Infocom]

Source

Destination

Ad hoc node

Height metric

• DAG


Hierarchical Routing Protocols

1.CGSR (Clusterhead-Gateway Switch Routing) 2.HSR (Hierarchical State Routing) 3.ZRP (Zone Routing Protocol) 4.LANMAR (Landmark Ad Hoc Routing

Protocol)


CGSR (cont’d)


Hybrid Protocols

Zone Routing Protocol (ZRP) [Haas98] combines

– Intra-zone routing: Pro-actively maintain state information for links within a short distance from any given node

» Routes to nodes within short distance are thus maintained proactively (using, say, link state or distance vector protocol)

– Inter-zone routing: Use a route discovery protocol for determining routes to far away nodes. Route discovery is similar to DSR with the exception that route requests are propagated via peripheral nodes. => Reactive


Routing Summary Protocols

– Proactive, reactive and hybrid – Plenty of routing protocols

Performance Studies– Typically studied by simulations using ns, discrete event simulator– Nodes (10-30) remains stationary for pause time seconds (0-900s) and then

move to a random destination (1500m X300m space) at a uniform speed (0-20m/s). CBR traffic sources (4-30 packets/sec, 64-1024 bytes/packet)

– Attempt to estimate latency of route discovery, routing overhead …– Still many things to be done

Actual trade-off depends a lot on traffic and mobility patterns– Higher traffic diversity (more source-destination pairs) increases overhead in

on-demand protocols– Higher mobility will always increase overhead in all protocols


Existing Ad Hoc Multicast Routing Protocols

Tree based multicast– Source Based Tree: DVMRP, MOSPF, PIM-DM

» Scalability problem, require prior knowledge of topology information – frequent topological change !

– Core Based Tree: AODV, CBT, PIM-SM, AmRoute, AMRIS» Concentration on the shared link

Mesh based multicast– Multicast Mesh: CAMP

» Single mesh structure spanning all multicast group member» Multiple redundant paths -> avoiding frequent mesh reconfiguration, unnecessary forw

arding of multicast packet

– Group Based Forwarding: ODMRP, LBM» Location Based: LBM» A group of node: multicast forwarding nodes for each multicast group,

Is maintained instead of the links that constitute the tree or mesh» multicast packets are forwarded only by forwarding nodes: rebroadcast

Redundant path are available


QoS in Ad Hoc Networks QoS support in Mobile Ad hoc NETworks

– QoS support in the Internet can’t be directly used in MANETs» Bandwidth constraints» Dynamic network topology» Link state information such as delay, bandwidth, cost, error rate

Difficult to get and to manage because link states change with the surrounding circumstance

– The research on QoS support in MANETs» QoS models: feasible model» QoS resource reservation signaling: acts as control center. Coordinates the beha

viors of QoS routing, QoS MAC and other components such as scheduling, admission control..

» QoS routing: search for path with enough resource(does not reserve resources). QoS signaling without QoS routing can still work. But it works better with QoS routing.

» QoS MAC: essential component » Other components: scheduling, admission control <- can be borrowed from the othe

r network architectures without or with few modification


Multilayer approach to mobile networking

Why multilayer?– Layered design approach can’t meet the technical challenges of mobi

le networks– QoS can’t be provided unless it is supported across all layer of the ne

twork

Major challenge: What is the interface? Between wired network and various kinds of wireless networks (cellular, ad hoc, broadband,….)

Multilayer synergy


Wireless routers

Gateways

Printers, servers

Mobile clients

Stationary clients

Intra-mesh wireless links

Stationary client access

Mobile client access

Internet access links

Node Types Link Types

Overview


Broadband Internet Access

CableDSL

WMAN(802.16)

Cellular(2.5-3G)

WMN

Bandwidth VeryGood

VeryGood

Limited Good

Upfront Investments

VeryHigh

High High Low

Total Investments

VeryHigh

High High Moderate

Market Coverage Good Good GoodModest


Existing Routing Protocols

Internet routing protocols (e.g., OSPF, BGP, RIPv2)– Well known and trusted– Designed on the

assumption of seldom link changes

– Without significant modifications are unsuitable for WMNs in particular or for ad hoc networks in general.

Ad-hoc routing protocols (e.g., DSR, AODV, OLSR, TBRPF)– Newcomers by comparison

with the Internet protocols– Designed for high rates of

link changes; hence perform well on WMNs

– May be further optimized to account for WMNs’ particularities

Ad HocNetworks

Wireless MeshNetworks


Routing – Cross-Layer Design (cont)

Routing – Transport– Choosing routes with low

error rates may improve TCP’s throughput.

– Especially important when multiple routes are used

– Freezing TCP when a route fails.

Routing – Application– Especially with respect of sa

tisfying QoS constraints


Embedded Networked Sensing: Motivation

Examples; high-rise buildings self-detect structural faults (e.g., weld cracks) schools detect airborne toxins at low concentrations, trace contaminant t

ransport to source buoys alert swimmers to dangerous bacterial levels earthquake-rubbled building infiltrated with robots and sensors: locate su

rvivors, evaluate structural damage ecosystems infused with chemical, physical, acoustic, image sensors to t

rack global change parameters battlefield sprinkled with sensors that identify track friendly/foe air, groun

d vehicles, personnel Micro-sensors, on-board processing, wireless interfaces feasible at very

small scale--can monitor phenomena “up close”– Embedded Networked Sensing will reveal previously unobservable phe

nomena


Overall Design of Sensor Networks

One possible solution?– Internet technology coupled with ad-hoc routing mechanism

Each node has one IP address. Each node can run applications and services Application instances running on each node can communicate with each other

Why must it be different and difficult?– A sensor node is not an identity (address): Content based and data centric

» Where are nodes whose temperatures will exceed more than 10 degrees for next 10 minutes?

» Tell me the location of the object ( with interest specification) every 100ms for 2 minutes.

– Multiple sensors collaborate to achieve one goal.

– Intermediate nodes can perform data aggregation and caching in addition to routing.: where, when, how?

– Not node-to-node packet switching, but node-to-node data propagation.

– High level tasks are needed:» At what speed and in what direction was that elephant traveling?

» Is it the time to order more inventory?


Classifications of Sensor Nets

Sensor position– Static (Habitat, CORIE, Biomedical) – Mobile (Smart Dust, Biomedical)

Goal-driven– Monitoring: Real-time/Not-real-time (Habitat, Smart

Dust)– Forecasting (CORIE)– Function substitution (Biomedical)– …

Communication medium– Radio Frequency (Habitat, CORIE, Biomedical)– Light (Smart Dust)


Wireless Communication: Topology

Fixed topology– Tree based– Cluster basedCluster-based approach provides better energy-

efficiency than the tree-based approach. Dynamic topology - mobility

– Ad hoc– Infrastructure– Mixed


802.15 WG is developing 3 MACs and 5 PHYs, TG3a is the 6th PHY

= Draft in process or complete

= Draft not defined e.g., CFP, etc.

1 Mb/s

2.4 GH zW PAN-Bluetooth

Bluetooth(TM)802.15.1

MAC Sublayer802.15.1

11 Mb/s22 Mb/s55 Mb/s

2.4 GH zW PAN-HRHigh Rate802.15.3

110 Mb/s? Mb/s

?W PAN-HR

Higher Rate802.15.3a


2 kb /s20 kb /s

868-868.6 MH zW PAN-LRLow Rate802.15.4

2 kb /s20 kb /s

902-928 MH zW PAN-LRLow Rate802.15.4

2 kb /s250 kb /s

2400-2483.5 GH zW PAN-LRLow Rate802.15.4


802.15

802.2 LLC

PhysicalLayer

Medium AccessControl Sublayer

Logical LinkControl Sublayer

{

{

{

= Other LLC

Service SpecificConvergence Sublayer

(SSCS)


Comparison of routing algorithms Attributes

Algo.

Data EfficiencyEnergy Efficiency

(data/energy ratio)State complexity

Flooding Fastest Low b/c

ImplosionSmall, upstream

GossipingSlowest

No. 7

Lowest

Random walkNone

Rumor RoutingVery slow

No. 6Very low Some

SPIN Very Fast Higher than above, SPIN-EC close to ideal

Data- neighbor pairs

Directed DiffusionQuite Fast

No. 3Higher than TTDD global flooding + strong aggregation

Complex:

Neighbor X Interest

TTDDVery Fast

No.2

Reasonable

local flooding+ reasonable aggregation

OK:

Four neighbor, Constant

IP Multicast Fastest Low: b/c heavy machinery, ‘big’ node

Most complex


Sensor node

Sensing:– Temperature– Humidity– Light – Present of chemical– Vehicular movement– Pressure, noise level…

Data processing:– Partially process data before sending

Communicating:– Send only required data– Sensor node to base node– Base node to end user

Base node:– Gateway to user or external networks


Variety of Real-life Sensor Node Platforms

RSC WINS & Hidra Sensoria WINS UCLA’s iBadge UCLA’s Medusa MK-II Berkeley’s Motes Berkeley Piconodes MIT’s AMPs And many more…

Different points in (cost, power, functionality, form factor) space


Rockwell WINS & Hidra Nodes Consists of 2”x2” boards in a 3.5”x3.5”x

3” enclosure– StrongARM 1100 processor @ 133 MH

z» 4MB Flash, 1MB SRAM

– Various sensors» Seismic (geophone)» Acoustic» magnetometer,» accelerometer, temperature, pressure

– RF communications» Connexant’s RDSSS9M Radio @ 100 kbps, 1-

100 mW, 40 channels

– eCos RTOS Commercial version: Hidra

C/OS-II– TDMA MACwith multihop routing

http://wins.rsc.rockwell.com/


Berkeley Motes

Devices that incorporate communications, processing, sensors, and batteries into a small package

Atmel microcontroller with sensors and a communication unit – RF transceiver, laser module,

or a corner cube reflector

– temperature, light, humidity, pressure, 3 axis magnetometers, 3 axis accelerometers

TinyOS

light, temperature,10 kbps @ 20m


TinyOS System composed of concurrent FSM modules

– Single execution context Component model

– Frame (storage)– Commands & event handlers– Tasks (computation)– Command & Event interface – Easy migration across h/w -s/w boundary

Two level scheduling structure– Preemptive scheduling of event handlers– Non-preemptive FIFO scheduling of tasks

Compile time memory allocation NestC http://webs.cs.berkeley.edu

Messaging Component

Internal StateInternal Tasks

Commands Events

bit_cnt++ bit_cnt==8

Send Byte Eventbit_cnt = 0

DoneNo

Yes

Bit_Arrival_Event_Handler

State: {bit_cnt}Start

Ref: from Hill, Szewczyk et. al., ASPLOS 2000


UCLA iBadge

Wearable Sensor Badge– acoustic in/out + DSP– temperature, pressure, humid

ity, magnetometer, accelerometer

– ultrasound localization– orientation via magnetometer

and accelerometer– bluetooth radio

Sylph Middleware


Processing Common sensor node processors:

– Atmel AVR, Intel 8051, StrongARM, XScale, ARM Thumb, SH Risc Power consumption all over the map, e.g.

– 16.5 mW for ATMega128L @ 4MHz– 75 mW for ARM Thumb @ 40 MHz

But, don’t confuse low-power and energy-efficiency!– Example

» 242 MIPS/W for ATMega128L @ 4MHz (4nJ/Instruction)» 480 MIPS/W for ARM Thumb @ 40 MHz (2.1 nJ/Instruction)

– And, the above don’t even factor in operand size differences! However, need power management to actually exploit energy efficiency

– Idle and sleep modes, variable voltage and frequency


Sensing Several energy consumption sources

– transducer– front-end processing and signal conditioning

» analog, digital

– ADC conversion Diversity of sensors: no general conclusions can be drawn

– Low-power modalities» Temperature, light, accelerometer

– Medium-power modalities» Acoustic, magnetic

– High-power modalities» Image, video, beamforming


Putting it All Together: Power-aware Sensor Node

Sensors RadioCPU

Energy-aware RTOS, Protocols, & Middleware

PA-APIs for Communication, Computation, & Sensing

Dynamic Voltage & Freq.

Scaling

Scalable Sensor

Processing

Freq., Power, Modulation, & Code Scaling

Coordinated Power Management

PASTA Sensor Node Hardware Stack


Tracking: Mobile Script Flooding

Sensor Node

User Node

Video Node

Monitoring Target

“Tracking Script Code” injecting


Tracking: Event Sensing

Sensor Node

User Node

Video Node

Monitoring Target

Event Sensing

Event Sensing

Event Sensing

Event Sensing

Event Sensing

Event Sensing

Event Sensing

Event Sensing


Tracking: Mobile Script Activation

Tracking Code Activated

Sensor Node

User Node

Video Node

Target

Tracking Code Activated


Tracking: Position Notification and Code Migration

Position Information

Tracking Sensor

Node

User Node

Video Node

Target


Tracking Script Migration

Script Migration

Monitoring


Tracking: Position Notification

Tracking

Sensor Node

User Node

Video Node

Target


Tracking Script Migration

Script Migration

Monitoring

Tracking


Elements of Directed Diffusion

Naming– Data is named using attribute-value pairs

Interests – A node requests data by sending interests for named

data Gradients

– Gradients is set up within the network designed to “draw” events, i.e. data matching the interest.

Reinforcement– Sink reinforces particular neighbors to draw higher

quality ( higher data rate) events


Interest Propagation

Flooding Constrained or Directional flooding based on location. Directional Propagation based on previously cached data.

Source

Sink

Interest

Gradient


Data Propagation

Reinforcement to single path delivery.

Multipath delivery with probabilistic forwarding.

Multipath delivery with selective quality along different paths.

Source

Sink

Gradient

Data


Reinforcement

Reinforce one of the neighbor after receiving initial data.– Neighbor(s) from whom new events received.– Neighbor who’s consistently performing better than others.– Neighbor from whom most events received.

Source

Sink

Gradient

Data

Reinforcement


Naming

Content based naming– Tasks are named by a list of attribute – value pairs– Task description specifies an interest for data

matching the attributes – Animal tracking:

Interest ( Task ) DescriptionType = four-legged animalInterval = 20 msDuration = 1 minuteLocation = [-100, 100; 200, 400]

RequestRequest

Node dataType =four-legged animalInstance = elephantLocation = [125, 220]Confidence = 0.85Time = 02:10:35

ReplyReply


Interest

The sink periodically broadcasts interest messages to each of its neighbors

Every node maintains an interest cache– Each item corresponds to a distinct interest

– No information about the sink

– Interest aggregation : identical type, completely overlap rectangle attributes

Each entry in the cache has several fields– Timestamp: last received matching interest

– Several gradients: data rate, duration, direction


WSN (ZigBee) vs. IP-USN (6LoWPAN)

Transport Layer(TCP/UDP)

Network Layer(IPv6)

Adaptation Layer

Application Layer

IEEE 802.15.4MAC/PHY


Network Layer(IP)

Ethernet of otherMAC/PHY

Application Layer

Network Layer(IP)

Ethernet of otherMAC/PHY

Adaptation LayerIEEE 802.15.4

MAC/PHY

IP network 의 호스트

Data

6LowPAN 의 호스트

Data

Application Layer

Application SupportLayer

ZigBee NetworkLayer


Application Layer

Application SupportLayer

ZigBee NetworkLayer


Application Layer


Network Layer(IP)

Ethernet of other MAC


Network Layer(IP)

Ethernet of other MAC

IP network 의 호스트

Data

ZigBee 센서노드

Data

ZigBee 게이트웨이


WSN (ZigBee) vs. IP-USN (6LoWPAN)

Sink Node

Coordinator

Sensor Node (16bit ZigBee ID)

EventRequest / Response

6LoWPAN Gateway

Coordinator

Sensor Node (IPv6 address)

EventRequest / Response

Event DB

Monitoring Center

Monitoring Center

Monitoring Center

EventUpdate

- Breaking end-to-end transparency- Limited adaptation for generic Service Architecture

Prof. Younghee Lee 1 1 u Lecture 15: MANET, Wireless Mesh and Sensor networks Prof. Younghee Lee Computer Networks.

Documents

networks u

demand u

proactive slide

u lecture

younghee lee computer

times reactive protocols

planes u need mobility

lanmar slide