adaptive protocols for information dissemination in wireless sensor networks
DESCRIPTION
Adaptive Protocols for Information Dissemination in Wireless Sensor Networks. The X – Matrix Team. http://www.cs.ucl.ac.uk/students/fshariff/projects/spin. Who, What and How. The X-Matrix Team - Wasif, Fahd, Philip, Muhammad and Kumardev - PowerPoint PPT PresentationTRANSCRIPT
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL2
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL3
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’?
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL4
Classic Flooding
B C
D
A
Sink Node
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL5
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL6
GossipingAlternative to Classic FloodingRandomisation to conserve energyAvoids implosion
B
C
D
A
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL7
The Ideal Protocol“Ideal” Shortest-path routes No wasted energy No redundant data
B
D E
FG
C
A
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL8
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL9
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL10
SPIN-PP
A
B
C
E
D
DATA message
ADV message
REQ message
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL11
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL12
Questioning SPIN for Point-to-Point
Why use PP when we already have BC?Do we need energy conservation or is it application dependent?
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL13
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL14
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL15
Unlimited Energy Simulations
Flooding fastest
-- SPIN-PP-- Ideal-- Flooding
SPIN-PP uses 3.5x less energy than flooding
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL16
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL17
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL18
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL19
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL20
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL21
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.
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL22
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.
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL23
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL24
Simulations with No Packet Losses
--- SPIN-BC--- Ideal--- Flooding
SPIN-BC Converges quicker than flooding Dissipates 50% less energy as compared to
flooding
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL25
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL26
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL27
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL28
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL29
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL30
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL31
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.
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL32
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 ?
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL33
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?
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL34
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
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL35
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.”
X-Matrix TeamMSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL36
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]