Data Dissemination and Fusion

1
Data Dissemination and Fusion In Sensor Networks
2
The need for Data Dissemination and Fusion

• Energy efficiency is an essential factor
  therefore, short-range hop-by-hop communication
  is preferred over direct long-range communication
  to the destination
• Since sensor network contains large amount of
  data for the end user, methods of combining or
  aggregating data into small set of information is
  necessary and contributes to energy savings
• Data aggregation (aka data fusion) can combine
  unreliable data readings to produce accurate
  signal by improving the common signal and
  reducing the noise

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Energy-Efficient Communication Protocol
Architecture for Wireless Microsensor Networks
(LEACH Protocol) Heinzelman 2000, 2002

• LEACH (Low-Energy Adaptive Clustering Hierarchy)
  is a clustering-based protocol that utilizes the
  randomized rotation of local cluster base
  stations to evenly distribute the energy load
  within the network of sensors
• It is a distributed, does not require any control
  information from base station (BS) and the nodes
  do not need to have knowledge of global network
  for LEACH to function
• The energy saving of LEACH is achieved by
  combining compression with data routing
• Key features of LEACH include
• Localized coordination and control of cluster
  set-up and operation
• Randomized rotation of the cluster base stations
  or clusterheads and their clusters
• Local compression of information to reduce global
  communication

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LEACH

• Considered microsensor network has the following
  characteristics
• The base station is fixed and located far from
  the sensors
• All the sensor nodes are homogeneous and energy
  constrained
• Communication between sensor nodes and the base
  station is expensive and no high energy nodes
  exist to achieve communication
• By using clusters to transmit data to the BS,
  only few nodes need to transmit for larger
  distances to the BS while other nodes in each
  cluster use small transmit distances
• LEACH achieves superior performance compared to
  classical clustering algorithms by using adaptive
  clustering and rotating clusterheads assisting
  the total energy of the system to be distributed
  among all the nodes
• By performing load computation in each cluster,
  amount of data to be transmitted to BS is
  reduced. Therefore, large reduction in the energy
  dissipation is achieved since communication is
  more expensive than computation

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LEACH

• Algorithm Overview
• The nodes are grouped into local clusters with
  one node acting as the local base station (BS) or
  clusterhead (CH)
• The CHs are rotated in random fashion among the
  various sensors
• Local data fusion is achieved to compress the
  data being sent from clusters to the BS
  resulting the reduction in the energy dissipation
  and increase in the network lifetime
• Sensor elect themselves to be local BSs at any
  any given time with a certain probability and
  these CHs broadcast their status to other sensor
  nodes
• Each node decided which CH to join based on the
  minimum communication energy
• Upon clusters formation, each CH creates a
  schedule for the nodes in its cluster such that
  radio components of each non-clusterhead node
  need to be turned OFF always except during the
  transmit time
• The CH aggregates all the data received from the
  nodes in its cluster before transmitting the
  compressed data to BS

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LEACH

• Algorithm Overview
• The transmission between CH and BS requires high
  energy transmission
• In order to evenly distribute energy usage among
  the sensor nodes, clusterheads are self-elected
  at different time intervals
• The nodes decides to become a CH depending on the
  amount of energy it has left
• The decisions to become CH are made
  independently of the other nodes
• The system can determine the optimal number of
  CHs prior to election procedure based on
  parameters such as network topology and relative
  costs of computation vs. communication (Optimal
  number of CHs considered is 5 of the nodes)
• It has been observed that nodes die in a random
  fashion
• No communication exists between CHs
• Each node has same probability to become a CH

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LEACH

• Algorithm Details
• The operation of LEACH is achieved by rounds
• Each round begins with a set-up phase (clusters
  are selected) followed by steady-state phase
  (data transmission to BS occurs)
• Advertisement Phase
• Initially, each node need to decide to become a
  CH for the current round based on the suggested
  percentage of CHs for the network (set prior to
  this phase) and the number times the node has
  acted as a CH
• The node (n) decides by choosing a random number
  between 0 and 1
• If this random number is less than T(n), the
  nodes become a CH for this round
• The threshold is set as follows

P desired percentage of CHs r current
round G set of nodes that have not been
CHs in the last 1/P rounds
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LEACH

• Algorithm Details
• 1. Advertisement Phase
• Assumptions are (i) each node starts with the
  same amount of energy and (ii) each CHs consumes
  relatively same amount of energy for each node
• Each node elected as CH broadcasts an
  advertisement message to the rest
• During this clusterhead-advertisement phase,
  the non-clusterhead nodes hear the ads of all CHs
  and decide which CH to join
• A node joins to a CH in which it hears with its
  advertisement with the highest signal strength
• 2. Cluster Set-Up Phase
• Each node informs its clusterhead that it will be
  member of the cluster
• 3. Schedule Creation
• Upon receiving all the join messages from its
  members, CH creates a TDMA schedule about their
  allowed transmission time based on the total
  number of members in the cluster

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LEACH

• Algorithm Details
• 4. Data Transmission
• Each node starts data transmission to their CH
  based on their TDMA schedule
• The radio of each cluster member nodes can be
  turned OFF until their allocated transmission
  time comes minimizing the energy dissipation
• The CH nodes must keep its receiver ON to receive
  all the data
• Once all the data is received, the CH compresses
  the data to send it to BS
• Multiple Clusters
• In order to minimize the radio interference
  between nearby clusters, each CH chooses randomly
  from a list of spreading CDMA codes and it
  informs its cluster members to transmit using
  this code
• The neighboring CHs radio signals will be
  filtered out to avoid corruption in the
  transmission

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LEACH

• Advantages
• Localized coordination to enable scalability, and
  robustness for dynamic networks
• Incorporates data fusion into the routing
  protocol in order to reduce the amount of
  information transmitted to BS
• Distributes energy dissipation evenly throughout
  the sensors, thus increasing the system lifetime
  of the network

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LEACH

• Disadvantages
• How to decide the percentage of cluster heads for
  a network? The topology, density and number of
  nodes of a network could be different from other
  networks
• No suggestions about when the re-election needs
  to be invoked
• The clusterheads farther away from the base
  station will use higher power and die more
  quickly than the nearby ones

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LEACH

• Suggestions/Improvements/Future Work
• Extensions can be included to have hierarchical
  clustering where each CH will communicate with
  super-clusterhead until the top layer of
  hierarchy in which the data needs to be sent to
  BS
• The degree and remaining energy of a node may be
  considered as parameters to decide a clusterhead
  in a round. If a clusterhead with a limited power
  used up its power in a round, the data to be
  transmitting may be lost
• Since TDMA schedule is used, a large delay may be
  introduced between event detection and
  notification at base station. Therefore, the
  protocol is not suitable for a real-time
  application

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Negotiation-Based Protocols for Disseminating
Information in Wireless Sensor Networks (SPIN
Protocols) Kulik 2002

• SPIN (Sensor Protocols for Information via
  Negotiation) is a family of negotiation-based
  information dissemination protocols which is
  designed to address the deficiencies of classic
  flooding by negotiation and resource-adaptation
• SPIN disseminates each sensor readings to all
  sensors in the network, treating all sensors as
  potential sink nodes
• Nodes using SPIN protocols names their data using
  high-level data descriptors, called meta-data and
  usage of meta-data negotiations eliminate
  transmission of redundant data in the network
• Communication decisions can be based upon both
  application-specific knowledge of the data and
  knowledge of the resources available to nodes

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SPIN

• SPIN has two basic ideas
• Operate efficiently and conserve energy
  communicate with each other about the sensor data
  received already and the data needed still
• Monitor and adapt changes in their own energy
  resources extend the lifetime of the system
• Four difference SPIN protocols
• SPIN-PP
• SPIN-EC
• SPIN-BC
• SPIN-RL
• Meta Data
• Used to uniquely and completely describe the data
  being collected by sensors
• If two pieces of actual data are distinguishable,
  then their meta-data should also be
  distinguishable
• Since the format of meta-data is
  application-specific, each application needs to
  interpret and synthesize its own meta-data

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SPIN

• Meta Data
• SPIN applications must define a meta-data format
  for representing data that concerns with the
  costs of storing, retrieving and managing the
  meta-data
• SPIN nodes uses three types of communication
  messages
• ADV (new data advertisement)
• REQ (request for data)
• DATA (data message)
• ADV and REQ messages contain only meta-data that
  is smaller than the DATA message
• SPIN Resource Management
• SPIN applications are resource-aware and
  resource-adaptive
• By knowing the resources at hand, the nodes makes
  informed decisions about using their resources
  effectively
• SPIN specifies an interface that applications can
  use to find out their available resources rather
  than specifying a specific energy management
  protocols

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SPIN

• The Problem
• In conventional classic flooding, the source
  nodes sends data to all its neighbors and the
  neighbors check their record of already sent data
  to see if they have forwarded the data to their
  neighbors. If not, they forward the data and
  update the record
• This requires small amount of protocol state at
  any node, disseminates data quickly in the
  network where neither the bandwidth is scarce and
  the links are error prone
• The problems include implosion, overlap and
  resource blindness
• Implosion A node always sends data to its
  neighbors without being concerned about
• if the same data has been received by the
  neighbors from other nodes
• Overlap The nodes waste energy and bandwidth by
  sending the overlapping data
• Resource Blindness Nodes do not make decisions
  based on the energy available

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SPIN

• The Solution
• SPIN provides solution to the problems of
  implosion and overlap by negotiating with each
  other before transmitting data eliminates the
  transmission of redundant data
• Nodes poll their resources before transmitting or
  processing data by probing the resource manager
  which keeps track of the resource consumption
• Nodes can make efficient decisions based on the
  available energy level
• The use meta-data descriptors eliminates the
  possibility of overlap since the nodes can name
  the part of the data the nodes are interested in
  receiving
• Resource-awareness of local resources allow
  sensors to make meaningful decisions to extend
  longevity

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SPIN

• SPIN Protocols
• 1. SPIN-PP A Threestage handshake protocol for
  point-to-point media
• This protocol works in three stages
  (ADV-REQ-DATA) with each stage corresponding to
  one of the messages
• The node sends ADV message to its neighbors
• Neighbors check to see if they already have
  received or requested this data
• If not, the neighbors respond by sending REQ
  message to the sender
• The sender responds to the REQ message sent by
  sending the actual DATA to the neighbors
  requesting the data
• If the neighbor already has the advertised data,
  it does not send any message
• Simplicity is the main strength, meaning that
  nodes make simple decisions, resulting in usage
  of small energy in computation
• Each node only needs to know about its one hop
  neighbors

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SPIN

• SPIN Protocols
• 2. SPIN-EC SPIN-PP with low-energy threshold
• Adds simple energy-conservation heuristic to the
  SPIN-PP protocol
• When energy is abundant, SPIN-EC acts as SPIN-PP
  protocol
• Whenever energy comes close to low-energy
  threshold, it adapts by reducing its
  participation
• The node will only participate in the full
  protocol if it believes that it has enough energy
  to complete the protocol without reaching below
  the threshold value
• It does not prevent nodes from receiving messages
  such as ADV or REQ below its low-energy
  threshold, but prevents the nodes to handle a
  DATA message below the threshold

20
SPIN

• SPIN Protocols
• 3. SPIN-BC A Threestage handshake protocol for
  broadcast media
• Improves upon SPIN-PP for broadcast networks by
  using cheap, one-to-many communications, meaning
  that all messages are sent to broadcast address
  and processed by all the nodes that are within
  transmission range of the sender
• This approach is often called broadcast-message-su
  ppression
• SPIN-BC has three main differences from SPIN-PP
  are
• All SPIN-BC nodes send their messages to the
  broadcast address such that all nodes within the
  transmission range of sender will receive message
• Upon receiving ADV message, each node checks to
  see if they already have the data. If not, node
  sets a random timer to expire, uniformly chosen
  from a predetermined interval. After timer
  expires, the node sends an REQ message to the
  broadcast address, including the original
  advertiser in the header of message. When the
  nodes who are not original advertiser receive the
  REQ, they cancel their own request timers,
  preventing from sending out redundant copies of
  the same REQ
• The nodes will send out the requested data to the
  broadcast address only once to get the data all
  its neighbors. It will not respond to multiple
  requests of the same data

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SPIN

• SPIN Protocols
• 4. SPIN-RL SPIN-BC for lossy networks
• Reliable version of SPIN-BC which disseminates
  data through a broadcast network even in the
  cases of network loses packets or communication
  is asymmetric
• Adds two adjustments to SPIN-BC to achieve
  reliability
• Each node maintains a record of which
  advertisements it hears from which nodes, and if
  does not receive the data within a set time after
  request, node rerequests the data
• Nodes limit the frequency with which they will
  resend the data, meaning that it will wait for a
  set time before responding to any additional
  requests for the same data

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SPIN

• Advantages
• Meta-data negotiation and resource adaptation
• Maintains only local information about the
  nearest neighbors
• Suitable for mobile sensors since the nodes base
  their forwarding decisions on local neighborhood
  information

• Disadvantages
• It cannot isolate the nodes that do not want to
  receive information unnecessary power may be
  consumed

• Suggestions/Improvements/Future Work
• Study SPIN protocols in mobile wireless network
  models
• Develop more sophisticated resource-adaptation
  protocols to use available energy well
• Design protocols that make adaptive decisions
  based not only on the cost of communicating data,
  but also the cost of synthesizing it

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Directed DiffusionIntanagonwiwat 2000

• Motivated by scaling, robustness and energy
  efficiency requirements
• Directed diffusion is data-centric in that all
  communication is for named data
• Data generated by sensor nodes is named using
  attribute-value pairs
• All nodes in the network are application-aware
• A node requests data by sending interests for
  named data
• A sensing task is disseminated via sequence of
  local interactions throughout the sensor network
  as an interest for named data
• Nodes diffusing the interest sets up their own
  caches and gradients within the network to which
  channel the delivery of data
• During the data transmission, reinforcement and
  negative reinforcement are used to converge to
  efficient distribution
• Intermediate nodes fuse interests, aggregate,
  correlate or cache data

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Directed Diffusion

• Assumes that sensor networks are task-specific
  the task types are known at the time the sensor
  network is deployed
• An essential feature of directed diffusion is
  that interest, data propagation and data
  aggregation are determined by local interactions
• Focused on design of dissemination protocols for
  tasks and events
• Naming
• Task descriptions are named (specifies an
  interest for data matching the list of
  attribute-value pairs) and also called as
  interest
• Example task Every I ms, for the next T
  seconds, send me a location of any four-legged
  animal in subregion R of the sensor field.
• task four-legged animal // detect animal
  location
• interval 20 ms // send back events every 20 ms
• duration 10 seconds // for the next 10
  seconds
• rect -100, 100, 200, 400 // from sensors
  within rectangle

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Directed Diffusion

• Naming
• A sensor detecting an animal may generate the
  following data
• task four-legged animal // type of animal seen
• instance horse // instance of this type
• location 150, 200 // node location
• intensity 0.5 // signal amplitude measure
• confidence 0.85 // confidence in the match
• timestamp 013045 // event generation time
• Interests and Gradients
• Interest is generally given by the sink node
• For each active task, sink periodically
  broadcasts an interest message to each of its
  neighbors (including rect and duration
  attributes)
• Sink periodically refreshes each interest by
  sending re-sending the same interest with
  monotonically increasing timestamp attribute for
  reliability purposes

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Directed Diffusion

• Interests and Gradients
• Every node maintains an interest cache where each
  item in the cache corresponds to a distinct
  interest (different type, interval attributes
  with disjoint rect attributes)
• Interest entries in the cache do not contain
  information about the sink
• In some cases, definition of distinct interests
  allows interest aggregation
• The interest entry contains several gradient
  fields, up to one per neighbor
• When a node receives an interest, it determines
  if the interest exists in the cache
• If no matching exist, the node creates an
  interest entry
• This entry has single gradient towards the
  neighbor from which the interest was received
  with specified data rate
• Individual neighbors can be distinguished by
  locally unique identifiers
• If the interest entry exists, but no gradient for
  the sender of interest
• Node adds a gradient with the specified value
• Updates the entrys timestamp and duration fields

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Directed Diffusion

• Interests and Gradients
• If there exists both entry and a gradient,
• The node updates the entrys timestamp and
  duration fields
• When a gradient expires, it is removed from its
  interest entry
• When all gradients for an interest entry have
  expired, the interest entry is removed from the
  cache
• After receiving an interest, a node may re-send
  the interest to subset of its neighbors
• To the neighbors, it may seem that interest
  originated from the sending node even though it
  may have been generated a distant sink. This
  represents a local interaction
• This way, interest diffuse throughout the network
  and not each interest have been sent to all the
  neighbors if a node sent matching interest
  recently
• Gradient specifies data rate (value) and a
  direction in directed diffusion, whereas the
  values can be used to probabilistically forward
  data in different paths in other sensor networks

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Directed Diffusion

• Data propagation
• Data message is unicast individually to the
  relevant neighbors
• A node receiving a data message from its
  neighbors checks to see if matching interest
  entry in its cache exists according the matching
  rules described
• If no match exist, the data message is dropped
• If match exists, the node checks its data cache
  associated with the matching interest entry
• If a received data message has a matching data
  cache entry, the data message is dropped
• Otherwise, the received message is added to the
  data cache and the data message is re-sent to the
  neighbors
• Data cache keeps track of the recently seen data
  items, preventing loops
• By checking the data cache, a node can determine
  the data rate of the received events

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Directed Diffusion

• Reinforcement
• After the sink starts receiving low data rate
  events, it reinforces one neighbor in order to
  draw down higher quality (higher data rate)
  events
• This is achieved by data driven local rules
• To enforce a neighbor, the sink may re-send the
  original interest with higher data rate
• When the data rate is higher than before, the
  node node must also reinforce at least one
  neighbor
• Reinforcement can be carried out from neighbors
  to other neighbors in a particular path (i.e., if
  a path when a path delivers an event faster than
  others, sink attempts to use this path to draw
  down high quality data)
• In Summary, reinforce one path, or part of it,
  based on observed losses, delay variances, and so
  on
• Negative reinforce certain paths because resource
  levels are low

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Directed Diffusion
Figure adapted from Intanagonwiwat 2000
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Directed Diffusion

• Advantages
• Data-centric dissemination
• Robust multi-path delivery
• Reinforcement-based adaptation to the empirically
  best network path
• Energy savings with in-network data aggregation
  and caching
• Gives designers the freedom to attach different
  semantics to gradient values
• Reinforcement can be triggered not only by
  sources but also by intermediate nodes

• Disadvantages
• It may consume memory since all the attribute
  list is being sent

• Suggestions/Improvements/Future Work
• Exploration of possible naming schemes

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References

• Heinzelman 2002 W. Heinzelman, A.P.
  Chandrakasan and H. Balakrishnan, An
  Application-Specific Protocol Architecture for
  Wireless Microsensor Networks, IEEE Transactions
  on Wireless Communications, Vol. 1, No. 4,
  October 2002, pp. 660-670.
• Heinzelman 2000 W. Heinzelman, A.P.
  Chandrakasan and H. Balakrishnan,
  Energy-Efficient Communication Protocol for
  Wireless Microsensor Networks, IEEE Proceedings
  of the Hawaii International Conference on System
  Sciences, January 4-7, 2000, Maui, Hawaii.
• Intanagonwiwat 2000 C. Intanagonwiwat, R.
  Govindan and D. Estrin, Directed Diffusion A
  Scalable and Robust Communication Paradigm for
  Sensor Networks, In Proceedings of the Sixth
  Annual International Conference on Mobile
  Computing and Networks (MobiCOM 2000), August
  2000, Boston, Massachusetts
•  Kulik 2002 J. Kulik, W. Heinzelman and H.
  Balakrishnan, Negotiation-Based Protocols for
  Disseminating Information in Wireless Sensor
  Networks, Wireless Networks 8, 2002, pp. 169-185.
•