A Survey on Routing Protocols for Wireless Sensor Networks

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A Survey on Routing Protocols for Wireless Sensor
Networks

• By Kemal Akkaya Mohamed Younis
• Presented by
• Aggelos Vlavianos
• Jorge Mena
• Department of Computer Science and Engineering
• 02/08/05

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Table of Contents

• Goals
• Introduction
• System Architecture Designing
• Protocols for Sensor Networks
• Summary

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Goals

• A survey of recent routing protocols for sensor
  networks
• Classification of these protocols

4
Introduction

• Sensors are micro-electro-mechanical systems
  (MEMS)
• Low power devices
• Data processing capable
• Communication capabilities

5
Introduction - Usage

• Gather data locally (Temperature, Humidity,
  Motion Detection, etc.)
• Send them to a command center (sink)
• Applications
• Surveillance
• Security
• Disaster Management
• Environmental Studies

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Introduction - Constraints

• Limitations
• Energy Constrains
• Bandwidth
• All layers must be energy aware
• Need for energy efficient and reliable network
  routing
• Maximize the lifetime of the network

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Introduction - Routing

• No global addressing
• Redundant data traffic
• Multiple-source single-destination network
• Careful resource management
• Transmission power
• On-board energy
• Processing capacity
• Storage

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System Architecture Designing

• Network Dynamics
• Mobile or Stationary nodes
• Static Events (Temperature)
• Dynamic Events ( Target Detection)
• Node Deployment
• Deterministic Placed manually
• Self-organizing Scattered randomly

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System Architecture Designing

• Energy Considerations
• Direct vs Multi-hop communication
• Direct Preferred Sensors close to sink
• Multi-hop unavoidable in randomly scattered
  networks
• Data Delivery Models
• Continuous
• Event-driven
• Query-driven
• Hybrid

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System Architecture Designing

• Node Capabilities
• Homogenous
• Heterogeneous
• Nodes dedicated to a particular task (relaying,
  sensing, aggregation)
• Data Aggregation/Fusion
• Aggregation Combination of data by eliminating
  redundancy
• Data Fusion is Aggregation through signal
  processing techniques
• Aggregation achieves energy savings

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Introduction - Taxonomy

• Classification of Routing Protocols
• Data Centric
• Hierarchical
• Location-based
• Network Flow QoS Aware

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Data-centric Protocols

• Sink sends queries to certain regions and waits
  data from sensors located in that region
• Attribute-based naming is necessary to specify
  properties of data

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Data-centric Protocols

• Flooding
• Gossiping
• Sensor Protocols for Information via Negotiation
  (SPIN)
• Directed Diffusion
• Energy-aware Routing
• Rumor Routing
• Gradient-Based Routing (GBR)
• Constrained Anisotropic Diffusion Routing (CADR)
• COUGAR
• ACtive QUery forwarding In sensoR nEtworks
  (ACQUIRE)

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Data-centric Protocols

• Flooding
• Sensor broadcasts every packet it receives
• Relay of packet till the destination or maximum
  number of hops
• No topology maintenance or routing
• Gossiping
• Enhanced version of flooding
• Sends received packet to a randomly selected
  neighbor

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Data-centric Protocols Flooding, Gossiping
Problems

• Problems of Implosion, Overlap, Resource
  Blindness

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Data-centric Protocols

• Sensor Protocols for Information via Negotiation
  (SPIN)

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Data-centric Protocols - SPIN

• Topological changes are localized - Each node
  needs to know only its neighbors
• SPIN halves the redundant data in comparison to
  flooding
• Cannot guarantee data delivery
• SPIN NOT good for applications that need reliable
  data delivery

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Data-centric Protocols

• Directed Diffusion
• Uses a naming scheme for the data to save energy
• Attribute-value pairs for data and queries
  on-demand (Interests)
• Interests are broadcasted by the sink (query) to
  its neighbors (caching), which can do in-network
  aggregation
• Gradients reply links to an interest (path
  establishment)

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Data-centric Protocols Direct Diffusion

• Energy saving and delay done with caching
• No need for global addressing (neighbor-to-neighbo
  r mechanism)
• Cannot be used for continuous data delivery or
  event-driven applications

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Data-centric Protocols

• Energy-aware Routing
• Occasional use of a set of sub-optimal paths
• Multiple paths used with certain probability
• Increase of the total lifetime of the network
• Hinders the ability for recovering from node
  failure
• Requires address mechanism ?Complicate setup

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Data-centric Protocols

• Rumor Routing
• Variation of Directed Diffusion
• Flood the events instead of the queries
• Creation of an event ? generation of a long live
  packet travel through the network (agent)
• Nodes save the event in a local table
• When a node receives query ? checks its table and
  returns source destination path

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Data-centric Protocols Rumor Routing

• Advantages
• Can handle node failure
• Significant energy savings
• Disadvantages
• Works well only with small number of events
• Overhead through adjusting parameters, like the
  time to live of the agent

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Data-centric Protocols

• Gradient-Based Routing (GBR)
• Slightly changed version of Directed Diffusion
• Keep the number of hops to the sink when an
  interest is created (height of the node)
• Nodes height neighbors height gradient of
  the link
• Node forward packet to the link with largest
  gradient

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Data-centric Protocols -GBR

• Traffic Spreading and Data Aggregation ? Balance
  uniformly the network traffic
• Stochastic scheme
• Energy-based scheme
• Stream-based scheme
• Outperforms Directed Diffusion in terms of total
  communication energy

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Data-centric Protocols

• Constrained Anisotropic Diffusion Routing (CADR)
• General form of Directed Diffusion
• Query Sensors
• Route data in the network
• Activates sensors close to the event and
  dynamically adjusts routes
• Routing based on a local information/cost
  gradient
• More energy efficient than Directed Diffusion

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Data-centric Protocols

• COUGAR
• Views the network as a huge distributed database
• Declarative queries to abstract query processing
  from network layer functions
• Introduces a new query layer
• Leader node performs data aggregation and
  transmits to the sink

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Data-centric Protocols - COUGAR

• Disadvantages
• Additional query layer brings overhead in terms
  of energy consumption and storage
• In network data computation requires
  synchronization (i.e. wait for all data before
  sending data)
• Dynamically maintenance of leader nodes to
  prevent failure

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Data-centric Protocols

• ACtive QUery forwarding In sensoR nEtworks
  (ACQUIRE)
• Views network as a distributed database
• Node receiving a query from the sink tries to
  respond partially and then forwards packet to a
  neighbor
• Use of pre-cached information
• After the query is answered, result is returned
  to the sink by using the reverse path or the
  shortest path
• If cache information is not up to date ? node
  gathers information from neighbors within look
  ahead of d hops

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Data-centric Protocols ACQUIRE

• Motivation Deal with one shot complex queries
• Efficient routing by adjusting parameter d
• If d equals network size ? behaves similar to
  flooding
• If d too small the query has to travel more hops

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Hierarchical Protocols

• Maintain energy consumption of sensor nodes
• By multi-hop communication within a particular
  cluster
• By data aggregation and fusion ? decrease the
  number of the total transmitted packets

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Hierarchical Protocols

• LEACH Low-Energy Adaptive Clustering Hierarchy
• Power-Efficient GAthering in Sensor Information
  Systems (PEGASIS)
• Hierarchical PEGASIS
• Threshold sensitive Energy Efficient sensor
  Network protocol (TEEN)
• Adaptive Threshold TEEN (APTEEN)
• Energy-aware routing for cluster-based sensor
  networks
• Self-organizing protocol

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Hierarchical Protocols

• LEACH Low-Energy Adaptive Clustering Hierarchy
• One of the first hierarchical routing protocols
• Forms clusters of the sensor nodes based on
  received signal strength
• Local cluster heads route the information of the
  cluster to the sink
• Cluster heads change randomly over time ? balance
  energy dissipation
• Data processing aggregation done by cluster
  head

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Hierarchical Protocols - LEACH

• Advantages
• Completely distributed
• No global knowledge of the network
• Increases the lifetime of the network
• Disadvantages
• Uses single-hop routing within cluster ?not
  applicable to networks in large regions
• Dynamic clustering brings extra overhead
  (advertisements, etc)

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Hierarchical Protocols

• Power-Efficient GAthering in Sensor Information
  Systems (PEGASIS)
• Improvement of LEACH
• Forms chains from sensors rather than clusters
• Data aggregation in the chain ? one node sends
  the data to the base station
• Outperforms LEACH
• Excessive delay for distant nodes in the chain

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Hierarchical Protocols

• Hierarchical PEGASIS
• Extension of PEGASIS
• Decrease the delay for the packets during
  transmission to the base station
• Solution to the delay data gathering problem
• Simultaneous transmissions of data messages
• Avoid collisions and possible signal interference
• Signal Coding (e.g. CDMA)
• Spatially separated nodes can transmit at the
  same time

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Hierarchical Protocols

• Threshold sensitive Energy Efficient sensor
  Network protocol (TEEN)
• Good for time-critical applications
• Hierarchical along with a data-centric approach
• Hierarchical grouping Close nodes form clusters
  and this process goes on the second level until
  sink is reached
• Cluster headers broadcast
• Hard Threshold
• Soft Threshold
• Not good for applications that need periodic
  reports

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Hierarchical Protocols
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Hierarchical Protocols

• Adaptive Threshold TEEN (APTEEN)
• Captures both periodic data collection and
  reacting to time-critical events
• APTEEN supports queries
• Historical -Analyze past data values
• One-Time Take a snapshot of the current network
  view
• Persistent monitor an event for a period of time

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Hierarchical Protocols TEEN APTEEN

• Advantages
• Outperform LEACH in terms of energy dissipation
  and total lifetime of the network
• Disadvantages
• Overhead and complexity of
• Forming multiple level clusters
• Implementing threshold-based functions
• Dealing with attribute-based naming of queries

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Hierarchical Protocols

• Energy-aware routing for cluster-based sensor
  networks
• Assumptions
• Sensors are grouped into clusters prior to
  network operation
• Cluster Heads (Gateways) less energy constrained
• Cluster Heads know the location of the sensors ?
  Known Multi-Hop routing to collect data
• Communication node (sink) communicates only with
  gateways

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Hierarchical Protocols

• Stages of a Sensor inside a cluster
• Sensing only
• Relaying only
• Sensing-Relaying
• Inactive

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Hierarchical Protocols

• Least Cost path used between nodes and gateway
• Cost function
• Energy Consumption
• Delay Optimization
• Performance Metrics
• TDMA based MAC is used for nodes to send data to
  the gateways
• Protocol performs well for
• Energy-based metrics (e.g. network lifetime)
• Cotemporary metrics (e.g. throughput)

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Hierarchical Protocols

• Self-organizing protocol
• Architecture supports heterogeneous sensors
• Nodes act as routers ? backbone of communication
• Stationary
• Sensing nodes forward data to the routers
• Stationary
• Mobile
• Sensors are a part of the network if they are
  reachable by a router

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Hierarchical Protocols

• The architecture requires addressing
• Sensor identified by the router is connected to
• Algorithm for Self-Organizing Creation of
  routing table
• Discovery phase
• Organization phase
• Maintenance phase
• Self-reorganization phase
• Utilizes router nodes to keep all sensors
  connected by forming a dominating set

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Hierarchical Protocols

• Advantages
• Useful for applications which need communication
  of a specific node (e.g. parking-lot networks)
• Small cost of maintaining routing tables
• Keeping routing hierarchy strictly balanced
• Energy Savings Utilization of a limited subset
  of nodes
• Disadvantages
• Organization phase not on demand
• Many cuts in the network increase the probability
  of applying reorganization phase

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Location-based Protocols

• Distance between two nodes is calculated using
  location information
• Energy consumption can be estimated
• Efficient energy utilization
• Protocols designed for Ad hoc networks with
  mobility in mind
• Applicable to Sensor Networks as well
• Only energy-aware protocols are considered

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Location-based Protocols

• MECN SMECN
• Minimum Energy Communication Network
• GAF
• Geographic Adaptive Fidelity
• GEAR
• Geographic and Energy Aware Routing

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MECN SMECN

• Utilizes low power GPS
• Best applicable to non-mobile sensor networks
• Identifies a relay region
• Find a sub-network
• to relay traffic
• Self-reconfiguring
• Dynamically adaptive

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SMECN

• Assumption broadcasting allowed
• Obstacles considered
• Smaller network (number of edges)
• Less hops per transmission
• More energy efficient than MECN
• Less maintenance cost of links
• More overhead introduced

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GAF

• Forms a virtual grid for covered area
• Nodes use GPS to associate itself to the grid
• Nodes are allowed
• to be turned off if are
• equivalent.
• Handle mobility

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GAF

• Three States
• Discovery
• Active
• Sleep
• Representative Node is always active
• No aggregation or fusion performed
• As good as a normal Ad hoc in terms of latency
  and packet loss (saving energy)

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GEAR

• Uses heuristics to route packets
• Energy aware neighbor
• Geographic informed neighbor
• Same as Direct Diffusion but restricts interest
  by region
• Estimated Cost
• Residual energy and distance to destination
• Learned Cost
• Accounts for routing around holes

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Network Flow QoS-aware Protocols

• Network Flow Maximize traffic flow between two
  nodes, respecting the capacities of the links
• QoS-aware protocols consider end-to-end delay
  requirements while setting up paths

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Network Flow QoS-aware Protocols

• Maximum Lifetime Energy Routing
• Maximum Lifetime Data Gathering
• Minimum Cost Forwarding
• Sequential Assignment Routing
• Energy Aware QoS Routing Protocol
• SPEED

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Maximum Lifetime Energy Routing

• Maximizes network lifetime by defining link cost
  as a function of
• Remaining energy
• Required transmission energy
• Tries to find traffic distribution (Network flow
  problem)
• The least cost path is one with the highest
  residual energy among paths

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Maximum Lifetime Data Gathering

• Maximizes the Data-gathering schedule
• Maximum Lifetime Data Aggregation
• Data aggregation plus setting up maximum lifetime
  of routes
• Maximum Lifetime Data Routing
• When data aggregation is not possible
• Computational Expensive (scalability)
• Clustering MLDA

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Minimum Cost Forwarding

• Aims at finding the minimum cost path in a large
  network, simple and scalable
• Cost function captures delay, throughput, and
  energy metrics from node to sink
• Back-off based algorithm
• Finds optimal cost of all nodes to the sink by
  using only one message per node
• Does not require addressing or forwarding paths

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Sequential Assignment Routing

• Table-driven, multi-path protocol
• Creates trees rooted at immediate neighbors of
  the sink (multiple paths)
• QoS metrics, energy resource, priority level of
  each packet
• Failure recoverable (done locally)
• High overhead to maintain tables and states at
  each sensor

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Energy Aware QoS Routing Protocol

• Finds least cost and energy efficient paths that
  meet the end-to-end delay during connection
• Energy reserve, transmission energy, error rate
• Class-based queuing model used to support
  best-effort and real-time traffic

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Energy Aware QoS Routing Protocol
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SPEED

• Each node maintains info about its neighbors and
  uses geographic forwarding to find the paths
• Tries to ensure a certain speed for each packet
  in the network
• Congestion avoidance

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Summary
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Questions