Adaptive Protocols for Information Dissemination in Wireless Sensor Networks

X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL1

The X – Matrix Team

Adaptive Protocols for

Information Dissemination in

Wireless Sensor Networks

http://www.cs.ucl.ac.uk/students/fshariff/projects/spin


Who, What and How

The X-Matrix Team- Wasif, Fahd, Philip, Muhammad and Kumardev

The paper - Negotiation-based Protocols for Disseminating Information in Wireless Sensor Networks

byJoanna Kulik,Wendi Rabiner Heinzelman,and Hari Balakrishnan, Massachusetts Institute of Technology, Cambridge, MA, USA

The broad concepts outlined in the paper

Our Approach De-construction and Analysis of work Presentation Structure and Flow


Fundamental Concepts

Wireless Sensor Networks Sensors – typical size, weight, power

characteristics Sensor Networks are a subset of Ad Hoc

Networks Fixed / Mobile

Routing in Ad Hoc / Sensor Networks Traditional protocols – Classic flooding,

Gossiping Adaptive protocols – SPIN, Others

What are these so-called ‘adaptive protocols’?


Classic Flooding

B C

D

A

Sink Node


Problems with Classic Flooding

Implosion

A

B C

D

(a)

(a)

(a)

(a)

A B

C (r,s)(q,r)

q sr

Data overlap

Energy Conservation


GossipingAlternative to Classic FloodingRandomisation to conserve energyAvoids implosion

B

C

D

A


The Ideal Protocol“Ideal” Shortest-path routes No wasted energy No redundant data

B

D E

FG

C

A


SPIN: Negotiation and Dissemination

Overview of SPINApplication-Level ControlMeta-Data NegotiationSpin Messages ADV – New data advertisement REQ – Request for data DATA – The actual data

message

SPIN Resource Management

A B

A B

A B

ADV

REQ

DATA


SPIN family of protocols

Point-to-Point SPIN-PP: a 3-stage handshake protocol for

point-to-point media SPIN-EC: SPIN-PP with a low-energy threshold

Broadcast SPIN-BC: a 3-stage handshake protocol for

broadcast media SPIN-RL: SPIN-BC for lossy networks


SPIN-PP

A

B

C

E

D

DATA message

ADV message

REQ message


SPIN-ECSPIN-PP with simple energy conservation heuristicWhen the low-energy threshold is observed, the node reduces its participation in the protocolNode can still receiveData messages cannot be transmitted


Questioning SPIN for Point-to-Point

Why use PP when we already have BC?Do we need energy conservation or is it application dependent?


Point-to-Point Media Simulations

Compare SPIN-PP and SPIN-EC with classic flooding, gossiping and the ideal protocol

Parameters of interest include: Data throughput Energy usage

Enhanced ns simulator


Simulation Testbed25 nodes, 59 edges25 data items3 items/node overlapAntenna reach: 10 m

No network losses or queuing delays

DataMeta-data

500 bytes

16 bytes


Unlimited Energy Simulations

Flooding fastest

-- SPIN-PP-- Ideal-- Flooding

SPIN-PP uses 3.5x less energy than flooding


Limited Energy Simulations

SPIN-EC distributes nearly the same amount as the ideal

SPIN uses energy at a much slower rate

-- SPIN-PP-- SPIN-EC-- Ideal-- Flooding


Simulation IssuesDoes not take into account for any delay caused by meta-data negotiationns constraints: Memory CPU time

A simulator model of a real-world system is necessarily a simplification of the real-world system itself


SPIN-BC MotivationsOne-to-many communication is:1/n times cheaper in a broadcast network than in a point-to-point networkwhere n is the number of neighbours for each nodeSaves energyLets each node overhear all transactions that occur coordinate better


SPIN-BCFor lossless broadcast networkUses a shared channelLike SPIN-PP, uses ADV, REQ and DATA messagesThree differences: Messages sent to a broadcast address When received ADV, sets random timer, sends

REQ upon timeout. Other nodes hearing REQ will cancel their timer

Nodes will send data to the broadcast address only once, assuming lossless network


ADVE

D

REQ

D

E

SPIN-BC Example

DATA E

DC

ADV

E

DC

B

A

A Nodes with data

A Nodes without data

A Nodes waiting to transmit REQ


SPIN-RL

For lossy broadcast networkTwo modifications Firstly, if a node does not receive data

within a period of time, it sends REQ again

Secondly, when a data item is repeatedly requested, the node will wait for a predetermined amount of time before responding to any requests.


SPIN - BC and RL : best option?

Open questions: Bandwidth-saving, how about utilising IP

Multicast? Reliable multicast?

Need further research Our opinion: if yes, a trimmed-down

version of multicasting is needed.


Broadcast Media Simulations

Simulation Testbed same as the one used in SPIN-PP with following variations:

Single shared-media channel Nodes use 802.11 MAC layer protocol Delay and packet losses taken into account

Simulation Setup monarch – extension of ns


Simulations with No Packet Losses

--- SPIN-BC--- Ideal--- Flooding

SPIN-BC Converges quicker than flooding Dissipates 50% less energy as compared to

flooding


Simulations with Packet Losses

--- SPIN-BC--- SPIN-RL--- Ideal-- Flooding-

SPIN-RL Only ideal and SPIN-RL converge because of their ability to

recover from packet loss, rest do not converge This is closer to reality scenario. Expends more energy as compared to BC and the ideal


Data Distributed Per Unit Energy

SPIN-RL delivers twice as much data per unit energy than flooding (100% more)

--- SPIN-BC--- SPIN-RL--- Ideal--- Flooding


Validity/Relevance of results

Simulation environment selected in SPIN-RL is a better representation of real world scenarioChannel interference and collision which were ignored in SPIN-BC, PP and EC have been taken into accountSPIN-RL: Theoretical integrity consistent


Major Short-comingsSimulation Environment does not closely model Wireless Sensor Networks environmentFalse assumption: the infinite supply of energy in SPIN-RLResults fall short of supporting a convincing argument in favour of SPIN protocols


Summary of relevant/similar work

What is similar and/or relevant?

SPIN and NNTP – comparable?

SPIN and Energy-Conservation based routing

SPIN and other Flat Multi-hop routing protocols

Spin and Others – AIDA, LEACH


SPIN vs Directed DiffusionWhat is directed diffusion? Similarities:

Optimized for disseminating application-specific information in a sensor network, specifically between source and sink nodes

Use of data naming allows negotiation between nodes prior to data forwarding to eliminate redundancy

Interest (REQ) and data (DATA) caches maintained at each node

Node-local decision making


SPIN vs Directed Diffusion - 2Dissimilarities:

SPIN uses a push model for disseminating information to all nodes, while DD uses a pull model for obtaining information

Data is sent to all nodes in SPIN while data is NOT sent to all nodes in Directed diffusion.


Sensor Network Applications and SPIN

Applications make the Networks SPIN around

Typical Sensor Network Applications

Application/Network type – Time Critical

Application/Network type – Reliable & Re-Usable

What kind of Protocols are optimal ?


Applications and SPIN

Application/Network type – Time Critical Characteristics Typical example – Seismic Activity Detection SPIN – is it optimal for this type of apps?

Application/Network type – Reliable & Re-usable

Characteristics Typical example – MARS Habitat Monitoring SPIN – is it optimal for this type of apps?


Summary and Crystal Ball

The Potential of Wireless Sensor NetworksThe Future of Wireless Sensor Networks

The Potential of SPINThe Limitations of SPIN The Future of SPIN


Ask us!We asked Joanna Kulik, one of the SPIN authors..

X-Matrix: “Could you address any SPIN protocol weaknesses (if any?)”

Joanna: “I haven't thought about SPIN in many years. I'm sure that there are many weaknesses, and that they would be easy to find. With SPIN we were just trying to lay some initial groundwork in the field. With anyinitial work, there are hundreds of ways that the workcould be improved.”


References1. D. Estrin, R. Govindan, J. Heidemann, S. Kumar,

Next century challenges: Scalable coordination in sensor networks, Proc. MOBICOM, 1999, Seattle, 263-270.

2. C. Intanagonwiwat, R. Govindan, , and D. Estrin. Directed diffusion: A scalable and robust communication paradigm for sensor networks. In MobiCOM, Boston, MA, August 2000.

3. Wireless Networks of Devices (WIND) [http://wind.lcs.mit.edu]

4. Praveen Rentala, Ravi Musunnuri, Shashidhar Gandham, Udit Saxena, Survey on Sensor Networks

5. LEACH [http://nms.lcs.mit.edu/projects/leach]

Adaptive Protocols for Information Dissemination in Wireless Sensor Networks

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