Dependable Computing Systems Lab Middleware for Robust Sensor Networks

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Dependable Computing Systems LabMiddleware for
Robust Sensor Networks

• School of Electrical Computer Engineering
• Purdue University

Members Faculty Saurabh Bagchi Students Nipoon
Malhotra Gunjan Khanna Yu-Sung Wu Issa
Khalil Yen-Shiang Shue Jin-Yi Wang Bingrui
Foo Blake Matheny
URL http//shay.ecn.purdue.edu/dcsl/
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Data Dissemination in Sensor Networks

• Large part of a sensor networks role is sensor
  data gathering and dissemination
• The data is often critical and has soft real-time
  requirements
• The paths on which the data traverses are often
  unreliable nodes and links may fail transiently
  or permanently
• Motivation of robust data dissemination
• Goals of data dissemination protocols
• Minimize energy drain
• Distribute data among the nodes quickly
• Reduce redundant data transmissions
• Tolerate node and link failures

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Existing Approaches to Data Dissemination

• TTDD Sources are the sensor nodes and sinks are
  mobile nodes interested in sensor data
• Sets up a grid structure and proactively
  determines routing from data source to sink
• At runtime, when sink needs data it locates a
  near dissemination point which uses
  pre-computed route from source to sink
• Drawbacks Cost of setting up entire routing
  grid.
• LEACH - Clustering of nodes for data forwarding
  to base station
• Clusters formed and cluster heads chosen
• Data forwarded to cluster head in TDMA manner,
  which is responsible for sending data to sink
• Drawbacks Data exchange on pre-determined
  schedule, all nodes need to be able to
  communicate directly with base station

• PEGASIS - Single node responsible for sending
  entire data to the sink
• Aggregate data from all cluster heads at single
  node
• Drawbacks Uneven drain of energy, higher delay
• SPIN - Exchange of meta data prior to actual
  data exchange, mix of push-pull
• Advertisement and request with meta-data before
  data sent only to interested nodes
• Drawbacks Single hop communication leading to
  high energy expenditure and contention delay

ADV
SPIN
B
REQ
DAT
S
S Sender B Interested node C Disinterested node
ADV
C
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Our Approach SPMS

• Single hop communication is inefficient in energy
  consumption and delay
• Forming efficient clusters and reconfiguring them
  in the face of motion are difficult
• Our protocol Shortest Path Minded SPIN (SPMS)
• Use meta data to avoid redundant data
  transmissions
• Incorporate multi-hop communication to use the
  available multiple transmit power levels
• Reduce energy and latency (due to MAC contention)
  by using smaller power.

SPMS
Pmax(ADV)
P1(REQ)
B
S
I1
I2
P1(DAT)
P1 lt Pmax
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Results Energy Dissipation Delay
Failure Free Cases
Failure Case
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SensorNMR A Data Fault Tolerant Approach In
Sensor Networks

• Motivation
• Protect integrity of sensed data reaching the
  sink node
• Error correction is wasteful in bandwidth, energy
  and requires complicated hardware and/or software
• Using N-Modular Redundancy (NMR) utilizes the
  redundancy inherent in the broadcast nature of
  wireless sensor network protocols
• Our Approach
• Vote at the sink node on data from multiple
  redundant paths to achieve data fault tolerance
• Competing idea use a hybrid-ARQ scheme (H-ARQ)
• H-ARQ is a method that combines FEC with
  automatic repeat request (ARQ)

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Problem With H-ARQ

• Energy consumption of H-ARQ scheme is much worse
  than NMR schemes

• Energy consumption for some H-ARQ schemes and
  broadcast TMR against different bit error rates
  for different grid (network)sizes

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The Directed Gossip Protocol

• NMR is applicable to current sensor network
  protocols
• Broadcast protocol There are more redundant
  packets than necessary for voting at the sink, so
  wasteful power is wasted in transmitting them
• Directed diffusion protocol Although sensors
  have a sense of direction in this protocol, there
  are still more packets than needed for voting at
  the sink
• Gossip Packets have no directional sense and so
  will take a long time to converge to the
  destination
• Solutions Directed Gossip Protocol!
• Combines the directional sense of directed
  diffusion with advantage of low energy cost of
  gossip protocol

Sink
Source
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Results Reliability, Convergence Time Energy
Usage
(C) Energy Usage

• (A) Reliability

(B) Convergence Time
CWSA Center for Wireless Systems and Applications
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Scalable Energy Efficient Crypto on Sensors
(SECOS)

• Sensors deployed in hostile environments where
  communication susceptible to eavesdropping
• Solution Protect message communication using
  symmetric key cryptography
• Challenge How to manage keys in a manner that is
• Scalable
• Secure
• Resource Aware
• Current Approaches
• Every sensor node has the keys of all other nodes
  (poor security, poor scalability, high storage
  requirements)
• Using the sink to hand the keys to parties
  wanting to communicate (not scalable,
  energy-expensive, no key refreshment)

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Our Approach SECOS

• Use a structured hierarchy of nodes divided into
  control groups
• Control node chosen randomly by base station
• Control node changed frequently
• Control node provides key management for sensor
  nodes in group
• Communication within control group is optimized
• Communication across control group involves
  secure session between control nodes
• Keys refreshed frequently

M
M
Base station
K1,i
K2,i
Ci
K3,i
Control node
C2
C3
C1
Sensor node
Si,j



S3,1
S3,1
S2,n
S1,n
S2,1
S1,1