Wireless Sensor and Actor Networks

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• Chapter 14
• Wireless Sensor and Actor Networks

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Wireless Sensor and Actor Networks I.F. Akyildiz
and I. H. Kasimoglu,Wireless Sensor and Actor
Networks Research Challenges Ad Hoc Networks
Journal (Elsevier), pp.351-367, Oct. 2004.
Task Manager Node
Sink
Sensor/Actor Field
Actors
Sensors
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Actuators vs. ActorsWhy do we call them actors?

• Actuator (Texas Instruments Technical Glossary)
• An actuator is a device to convert an electrical
  control signal to a physical action. Actuators
  may be used for flow-control valves, pumps,
  positioning drives, motors, switches, relays and
  meters.
• The mobility of a robot may be enabled by several
  actuators (motors, servo-mechanisms, etc)
• However, the robot represents one single network
  entity which we refer to as actor
• Hence, one actor can be endowed with multiple
  actuators

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Wireless Sensor and Actor Networks

• Sensors
• Passive elements sensing from the environment
• Limited energy, processing and communication
  capabilities
• Actors
• Active elements acting on the environment
• Higher processing and communication capabilities
• Less constrained energy resources (Longer battery
  life or constant power source)

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Sub-Kilogram Intelligent Tele-robots (SKITs)
Networked Robots having Coordination Wireless
Communication Capabilities
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Robotic Mule Autonomous Battlefield Robot
designed for the Army
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Mini-Robot (developed at Sandia National
Laboratories)
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Helicopter Platform
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Components of Sensor Actor Nodes
Sensing Unit
Transceiver
Processor Storage
ADC
Sensor Node
Power Unit
Controller (Decision Unit)
Processor Storage
Actuation Unit
Transceiver
DAC
Actor Node
Power Unit
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Integrated Sensor Actor Nodes
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WSAN Applications

• Environmental Applications
• Detecting and extinguishing forest fire.
• Microclimate control in buildings
• In case of very high or low temperature values,
  trigger the audio alarm actors in that area.
• Distributed Robotics Sensor Network
• (Mobile) robots dispersed throughout a sensor
  network alarm actors in that area.

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WSAN Applications

• Parking
• Airport Safety
• City Maintenance
• Sewage and Contamination Control
• Battlefield Applications
• Sensors detect mines or explosive substances
• Actors annihilate them or function as tanks

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WSANs vs. Wireless Sensor Networks

• Real-Time Requirements for Timely Actions
• Rapidly respond to sensor input (e.g., fire
  application)
• To perform right actions, sensor data must be
  valid at the time of acting
• Heterogeneous Node Deployment
• Sensors
• Actors

Densely deployed
Loosely deployed due to the different coverage
requirements and physical interaction methods of
acting task
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WSANs vs. Wireless Sensor Networks

• Coordination Requirements
• Sensor-Actor Coordination
• Actor-Actor Coordination

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WSAN Communication Architecture Semi-Automated
Architecture
Sink

• Sensors ? Sink ? Actors
• Requires manual intervention at sink
• No sensor-actor and actor-actor coordination
  needed
• Similar to the conventional WSN architecture

Event Area
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WSAN Communication Architecture Automated
Architecture
Sink

Event Area

• Sensors ? Actors
• No intervention from sink is necessary
• Localized information exchange
• Low latency
• Distributed sensor-actor and actor-actor
  coordination required

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SENSOR-ACTOR COORDINATION

• Challenges
• Which sensor(s) communicate with which actor(s)
  (Single or Multiple Actors)
• How should the communication occur? (i.e.,
  single-hop or multi-hop)
• What are the requirements of the communication
  (i.e., real-time, energy efficiency)

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Sensor-Actor Coordination

• Which sensor(s) communicate with which actor(s)?
• CASE 1
• Minimum number of sensors to report the sensed
  event
• CASE 2
• Minimum set of actors to cover the event region
• Both cases above
• The entire set of sensors and actors in the
  vicinity of the region
• The set of actors whose acting regions do not
  overlap

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Sensor-Actor CoordinationSINGLE ACTOR
Sensor
Actor
Event Area

• Selection of the most appropriate actor

• To select, sensors need to coordinate with each
  other

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Sensor-Actor Coordination SINGLE ACTOR

• Selecting a single actor node may be based on
• The distance between the event area and the actor
• The energy consumption of the path from sensors
  to the actor
• The action range of the actor

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Sensor-Actor CoordinationMULTI ACTORS
Sensor
Actor
Event Area

• Clustering is required

• Sensors only need to coordinate with sensors
  within some neighborhood to form clusters or
  groups

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Sensor-Actor Coordination MULTI ACTORS

• Clusters may be formed such a way that
• The event transmission time from sensors to
  actors is minimized
• The events from sensors to actors are transmitted
  through the minimum energy paths
• The action regions can cover the entire event area

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ACTOR-ACTOR COORDINATION

• Challenges
• Which actor(s) should execute which action(s)?
• How should multi-actor task allocation be done?

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Actor-Actor Coordination

• Single-Actor Task vs. Multi-Actor Task
• Single-Actor Task
• How is the single actor selected?
• Multi-Actor Task
• What is the optimum number of actors performing
  actions?
• Selection of most fit actors among the capable
  actors for that task
• Only a subset of actors covering the entire event
  region may perform the task to save action energy

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A Distributed Coordination Framework for WSANsT.
Melodia, D. Pompili, V. C. Gungor, I. F.
Akyildiz, ACM MOBIHOC05, May 2005. Also in IEEE
Transactions on Mobile Computing, 2007.

• Comprehensive framework for coordination problems
• SENSOR-ACTOR COORDINATION
• Optimal Event-driven Clustering
• A Distributed Scalable Protocol
• ACTOR-ACTOR COORDINATION
• Optimal Solution
• Real-time Localized Auction

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Coordination Requirements

• Sensor-Actor Coordination
• Establish data paths between sensors and actors
• Meet energy efficiency and real time requirements
• Actor-Actor Coordination
• Decision Does an action need to be performed?
• Which action should be performed?
• How to share the workload among actors?

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Sensor-Actor Coordination

• Objectives
• Establish data paths between sensors and actors
• Meet energy efficiency and real-time requirements
• Question
• To which actor does each sensor send its data?
• Solution
• Event Driven Clustering with Multiple Actors

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Event-Driven Clustering with Multiple Actors
Event Area
1. Event Occurs 2. Sensor-Actor Coordination
Event-Driven Clustering
What is the optimal clustering
strategy?Distributed algorithm?
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Reliability

• Definition 1.
• The latency bound B is the maximum allowed time
  between sampling of the physical features of the
  event and the moment when the actor receives a
  data packet describing these event features

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Reliability

• Definition 2
• A data packet is EXPIRED (UNRELIABLE), if it does
  not meet the latency bound B
• Definition 3
• A data packet is UNEXPIRED (RELIABLE), if it is
  received within the latency bound B

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Reliability

• Definition 4
• The event reliability r is the ratio of reliable
  data packets over all packets received in a
  decision interval
• Definition 5
• The event reliability threshold rth is the
  minimum event reliability required by the
  application
• OBJECTIVE
• Comply with the event reliability threshold
  (rgtrth) with minimum energy expenditure!

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Event-Driven Clustering with Multiple Actors

• Objective
• Find the optimal strategy for event-driven
  clustering (To which actors is data sent? Which
  paths are used?)
• ? a joint Clustering and Routing problem

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Event-Driven Clustering with Multiple Actors

• Requirements of the Optimal Solution
• Provide reliability above the event reliability
  threshold (rgtrth)
• Minimize overall Energy Consumption
• Optimal solution obtained by ? Integer Linear
  Programming formulation

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Event-Driven Clustering with Multiple Actors

• ILP Formulation is provided -gt allows finding the
  optimal solution
• BUT NP-Complete problem
• Not scalable (lt100 nodes)
• Centralized solution
• Helps gaining insight in the properties of the
  optimal solution
• Performance benchmark for distributed, more
  scalable solutions

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A Distributed Protocol

• Find the optimal working point of the network,
  i.e.
• rgtrth (? reliability over the threshold)
• Minimum energy consumption
• Based on the feedbacks from actors
• Actor calculates reliability r and broadcasts its
  value to the sensors

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A Distributed Protocol

• If the reliability r is complied with (rgtrth), a
  certain portion of the sensors switch in the
  aggregation state to save energy (lower energy
  consumption, higher delay)
• Equilibrium is reached when reliability threshold
  is met (r rth) with minimum energy consumption.

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A Distributed Protocol

• BASIC IDEA
• When the event is first sensed, sensors all begin
  in the start-up state and establish data paths to
  the actors
• If reliability is advertised to be low (rltrth)
• Certain portion of the sensors switch to speed-up
  state, which shortens the end-to-end paths (lower
  delay, higher energy consumption)

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A Distributed Protocol

• Sensors probabilistically switch among three
  different states according to feedback from the
  actors
• Start-up State
• Quickly establish a data path from each source to
  one actor
• Compromise between energy consumption and latency

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A Distributed Protocol

• Speed-up State
• Reduce the number of hops in sensor-actor paths
  so as to reduce the end-to-end delay
• Obtained by sending packets to far neighbors
  (closer to the destination actor)

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A Distributed Protocol

• Aggregation state
• Reduce the overall energy consumption when
  compliant with event reliability
• Send packets to closer neighbors (higher number
  of hops)

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Example Path Establishment
nodes establish paths (start-up state)
idlestart-up state
an event occurs
Another actor is too far away and thus not
energy efficient for any of the nodes in the
event area
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Example Low Reliability
Some sensors switch to the speed-up state
(probabilistically) and select as next hop the
closest node to the actor ? reduce latency
The actor advertises low reliability (rltrth)
idlestart-up statespeed-up state
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Example High Reliability
Some sensors switch to the aggregation state
(probabilistically) and select as next hop the
closest node already in the da-tree ? reduce
energy consumption
The actor advertises high reliability (rgtrth)
idlestart-up statespeed-up
stateaggregation state
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Actor-Actor Coordination

• Objective
• Selecting the best actor(s) in terms of action
  completion time and energy consumption so as to
  perform the action!
• Challenges
• Which actor(s) should execute which action(s)?
• How should multi-actor task allocation be done?

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Actor-Actor Coordination Model

• DEFINITIONs
• Overlapping Area
• Area can be acted upon by multiple actors
• Non-Overlapping Area
• Area can be acted upon only by one actor

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Actor-Actor Coordination Model

• Action Completion Time Bound
• The maximum allowed time from the moment when the
  event is sensed to the moment when the action is
  completed
• Power Levels
• Discrete levels of power for performing the
  action ? A higher power level corresponds to a
  lower action completion time!

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Actor-Actor Coordination Problems

• For an Overlapping Area, actor-actor coordination
  problem
• Selecting a subset of actors
• Adjusting action power levels ? Maximize the
  residual energy and complete the action within
  the action completion bound

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Actor-Actor Coordination Problems

• For a Non-Overlapping Area, actor-actor
  coordination problem
• Adjusting action power levels ? Maximize the
  residual energy

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Actor-Actor Coordination

• Optimal Solution
• Actor-actor coordination problem formulated as a
  Residual Energy Maximization Problem using Mixed
  Integer Non-Linear Programming (MINLP)
• Distributed Solution
• Real-Time Localized Auction-Based Mechanism

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Real-Time Localized Auction-Based Mechanism

• Inspired by the behaviors of agents in a Market
  Economy ? Interactions between buyers and sellers
• Possible Roles of the Actors
• Seller Actor receiving the event features
• Auctioneer Actor in charge of conducting the
  auction
• Buyer Actor(s) that can act on a particular
  overlapping area

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Real-Time Localized Auction-Based Mechanism

• For overlapping areas
• Seller selects one auctioneer for each
  overlapping area, i.e., the closest actor to the
  center of the overlapping area ? Energy spent for
  auction and auction time reduced!
• Seller informs each auctioneer about the auction
  area and the action time bound

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Real-Time Localized Auction-Based Mechanism

• Auctioneer determines the winners of the auction
  based on the bids received from the buyers.
• Bids consists of available energy, power level
  and action completion time

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Real-Time Localized Auction-Based Mechanism

• The auctioneer finds the winners by calculating
  the optimal solution of the Residual Energy
  Maximization Problem
• For Non-Overlapping areas
• The corresponding actor is directly assigned the
  action task

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Sensor-Actor Coordination
Start-up (speed-up) configuration all nodes are
in the start-up (speed-up) state
Comparison between the optimal solution of the
event-driven clustering problem and the energy
consumption of start-up, speed-up, aggregation
configuration with varying event ranges (60
sensors 4 actors)
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Sensor-Actor Coordination
Comparison of the energy consumption of
different configurations The energy
consumption in the aggregation configuration is
much lower that in the start-up and speed-up
configuration
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Sensor-Actor Coordination
Comparison of average number of hops for
start-up and speed-up configuration. The
speed-up configuration shows paths with lower
delay (less hops)
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Cyber Physical Systems

• Integration of computation with physical
  processes. Embedded computers and networks
  monitor and control physical processes in
  feedback loops where physical processes affect
  computations and vice versa.  
• CPS will blend sensing, actuation,
  computation, networking, and physical processes
  as action networks.
• "Networked Information Technology Systems
  Connected With The Physical World", also referred
  to as cyber-physical systems, are cited as the
  top technical priority for networking and IT
  research and development.
• President's Council of Advisors on Science and
  Technology