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Data Dissemination and Gathering

implosion

November 1, 2016
Published By : Pratik Kataria
Categorised in:

Dissemination = The act of spreading something, spreading, distribution.

Gathering = Assemble or collect

Data Dissemination

Process of Distribution of data.
Information flow from one sensor node to another.
The originator of data is known as Source Node and Receiver of the data is called Sink node or Gateway.
The Sink registers its interest to receive the data from source. The Source reports the data information to the Sink. The information thus reported is called event.

Process of Data Dissemination

The node that is interested in some events, like temperature or air humidity, broadcasts its interests to its neighbors periodically. Interests are then propagated through the whole sensor network.
Nodes that have requested data, send back data after receiving the request.
Intermediate nodes in the sensor network also keep a cache of received interests and data.

Data Dissemination Methods

  • Flooding
  • Gossiping
  • SPIN

Flooding

Each node which receives a packet (queries/data) broadcasts it if the maximum hop-count of the packet is not reached and the node itself is not the destination of the packet.

Advantage

  • No costly topology maintenance or route discovery

Disadvantages

  • Implosion
  • Overlapping
  • Resource Blindness

Implosion : This is the situation When duplicate messages are send to the same node. This occurs when a node receives copies of the same messages from many of its neighbors

implosion

Overlap : Overlap is another problem which occurs when using flooding. If two nodes share the same observation region both nodes will witness an event at the same time and transmit details of this event.

overlap

Resource blindness : the flooding protocol does not consider the available energy at the nodes and results in many redundant transmissions. Hence, it reduces the network lifetime.

Gossiping

gossiping

Modified version of flooding
The nodes do not broadcast a packet, but send it to a randomly selected neighbor.
Avoid the problem of implosion by making one copy of each message at any node
It takes a long time for message to propagate throughout the network.
The hop count can become quite large due to the protocols random nature

Sensor Protocols for Information via Negotiation

SPIN use negotiation and resource adaptation to address the disadvantage of flooding and Use meta-data instead of raw data.
Reduce overlap and implosion, and prolong network lifetime.
SPIN-1 has three types of messages: ADV, REQ, and DATA.
SPIN-2 using an energy threshold to reduce participation. A node may join in the ADV-REQ-DATA handshake only if it has sufficient resource above a threshold.

SPIN nodes negotiate with each other before transmitting data. Negotiation helps ensure that only useful information
will be transferred. To negotiate successfully, however, nodes must be able to describe or name the data they observe. We refer to the descriptors used in SPIN negotiations as meta-data.

Resource adaptive = They can poll their system resources to find out
how much energy is available to them. They can also calculate
the cost, in terms of energy, of performing computations
and sending and receiving data over the network.

spin-1

spin-2

spin-3

Data Gathering

The objective of the data gathering problem is to transmit the sensed data from each sensor node to a BS.

The goal of algorithm which implement data gathering is

  • Maximize the lifetime of network
  • Minimum energy should be consumed
  • The transmission occur with minimum delay
Data Dissemination Data Gathering
Any node can request the data along with base station. All data is transmitted to the base station
Data is always transmitted on demand Data can be transmitted periodically

Data Gathering Approaches

  • Direct Transmission
  • Power-Efficient Gathering for Sensor Information Systems
  • Binary Scheme

Direct Transmission

All sensor nodes transmit their data directly to the BS.
It cost expensive when the sensor nodes are very far from the BS.
Nodes must take turns while transmitting to the BS to avoid collision, so the media access delay is also large. Hence, this scheme performs poorly with respect to the energy x delay metric.

direct-transmission

Power-Efficient Gathering for Sensor Information Systems

PEGASIS based on the assumption that all sensor nodes know the location of every other node.
Any node has the required transmission range to reach the BS in one hop, when it is selected as a leader.
The goal of PEGASIS are as following:

Minimize the distance over which each node transmit

 

Minimize the broadcasting overhead

 

Minimize the number of messages that need to besent to the BS

 

Distribute the energy consumption equally across all nodes

To construct a chain of sensor nodes, starting from the node farthest from the BS. At each step, the nearest neighbor which has not been visited is added to the chain.

This algorithm uses greedy algorithm for chain construction. Before first round of communication chain formation is done

During formation of chain care must be taken so that nodes already in chain should not revisited

It is reconstructed when nodes die out.

At every node, data fusion or aggregation is carried out.

A node which is designated as the leader finally transmits one message to the BS.

Leadership is transferred in sequential order.

The delay involved in messages reaching the BS is O(N)

pegasis

Binary Scheme

This is a chain-based scheme like PEGASIS, which classifies nodes into different levels.
This scheme is possible when nodes communicate using CDMA, so that transmissions of each level can take place simultaneously.
The delay is O(log2N)

binary-scheme

Advantages
Low delay of only O(log2N), where the N is the amount of nodes.

Disadvantages
Non equal distribution of energy consumption, nodes that are active on several levels consume more energy than nodes that are only active at the first level. This might lead to the situation where some of sensor nodes die earlier than others.
Transmission distances may become long in high levels, which leads to a high power consumption

Pratik Kataria is a budding programmer, web designer and developer.