Next Century Challenges: Scalable Coordination in Sensor Networks

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Next Century Challenges Scalable Coordination in
Sensor Networks

• Deborah Estrin, Ramesh Govindan, John Heidemann,
  Satish Kumar
• (Some images and slides adopted from Santhosh R
  Thampuran - CMU)

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Outline

• Characteristics of sensor devices.
• Motivating applications.
• Key requirements of a sensor network and
  differences with current networks.
• Localized algorithms for coordination.
• Directed Diffusion a model for describing
  localized algorithms.

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Characteristics of Sensor Devices

• Ability to monitor a wide variety of ambient
  conditions
• temperature,
• pressure,
• mechanical stress level on attached objects
• Will be equipped with significant processing,
  memory, and wireless communication capabilities.

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Applications Environmental Analysis
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Applications Contaminant Flow Monitoring
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Applications Traffic Control

• Sensor attached to every vehicle.
• Capable of detecting their location, vehicle
  sizes, speeds and densities road conditions
• Alternate routes, estimate trip times

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Applications Biological Systems
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Key Requirements

• These futuristic scenarios bring out two key
  requirements of sensor networks
• support for very large numbers of unattended
  autonomous nodes.
• adaptivity to environment and task dynamics.

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Differences with Current Networks

• Sensor Networks ratio of communicating nodes to
  users is much greater.
• extremely difficult to pay special attention to
  any individual node.
• Sensors may be inaccessible
• embedded in physical structures.
• thrown into inhospitable terrain.

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Differences with Current Networks

• There are large scale unattended systems, today.
• Automated factories are deployed with very
  careful planning and react to very few external
  events.

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Differences with Current Networks

• Sensor networks deployed in very ad hoc manner.
• They will suffer substantial changes as nodes
  fail battery exhaustion, accidents new nodes
  are added nodes move.
• User and environmental demands also contribute to
  dynamics.

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Overall Design of Sensor Networks

• Is it sufficient to design sensor network
  applications using Internet technologies coupled
  with ad-hoc routing mechanisms?
• Data-Centric Application-Specific.
• Sensor network coordination applications are
  better realized using localized algorithms
  distributed as opposed to centralized.
• scales with increase in network size, robust to
  network partitions and node failures.

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Localized Algorithms for Coordination

• Clustering efficient coordination.

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Localized Clustering Algorithm

• For every sensor, level ? radius
• Advertisement hierarchical level, parent ID,
  remaining energy

C
D
B
E
A
wait time
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Localized Clustering Algorithm

• Start promotion timer if no parent.
• Promotion timer inv prop (remaining energy,
  number of other sensors from whom level 0 adv was
  received)

C
D
B
E
A
promotion timer
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Localized Clustering Algorithm

• Periodic advertisements at the level 1 radius.
• Advertisement B,C,E

C
D
B
E
A
level 1 sensor
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Localized Clustering Algorithm

• Two key design constraints
• asymmetric communication in the network.
• limited energy of sensors.

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Application of Clustering Algorithm

• Aim To pinpoint in an energy-efficient manner,
  the exact location of objects.
• Accuracy widest possible measurement baseline.
• Energy efficiency fewest number of sensors
  participating in the triangulation.

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Triangulation
Z
A

• Determine position in space.
• Can specify approx direction of object relative
  to its own location.

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Base-line Estimation
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Advantages of Cluster-based Approach

• Sensor algorithms only use local information.
• generally lower energy consumption in comparison
  to global communication.
• Robust to link or node failures and network
  partitions
• mechanisms for self-configuration can be simpler.

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Advantages of Cluster-based Approach

• Local communication and per-hop data filtering
• avoid transmitting large amounts of data over
  long distances.
• preserving node energy resources.
• Node energy resources are better utilized
• cluster-heads adapt to changing energy levels.

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Disadvantage of Cluster-based Approach

• Non-optimal under certain terrain conditions.

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Several Sensors Electing Themselves
Obstacle
Allow a cluster-head to switch on some number of
child sensors in its cluster to do object
location.
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Adaptive Fidelity Algorithms
Z
Y
A
quality of the answer can be traded against
battery lifetime, network bandwidth, or number of
active sensors.
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Tradeoffs

• Localized algorithms exhibit good robustness and
  scaling properties.

• May sacrifice resource utilization or sensing
  fidelity, responsiveness, or immunity to
  cascading failures.

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Directed Diffusion

• A novel data-centric, data disemmination paradigm
  for sensor networks.
• Data generated by sensor node is named using
  attribute-value pairs.
• A sensing task is disseminated throughout the
  sensor network as an interest for named data.

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Directed Diffusion

• This dissemination sets up gradients within the
  network designed to "draw" data matching the
  interest.
• Events start flowing towards the originators of
  interests along multiple paths. The sensor
  network reinforces one, or a small number of
  these paths.

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Directed Diffusion
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Directed Diffusion

• Allows intermediate nodes to cache or locally
  transform data.
• leverages the application-specificity that is
  possible in sensor networks.
• The diffusion models data naming and local data
  transformation features capture the
  data-centricity and application-specificity
  inherent in sensor networks.

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Related Work

• Ad-hoc Networks
• Proactive vs. reactive routing protocols
• Energy-efficiency issues
• Distributed Robotics
• Robots cooperate to discover entire map
• Internet Multicast and web caching
• Lightweight session

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Current Developments

• Smartdust project
• cubic millimeter sensors
• Sensors float in air like dust
• WINS (wireless integrated wireless Sensors)
• WSN (Wireless Sensing Network)
• Odyssey
• Habitat monitoring
• The Cricket Indoor Location System