An Energy Efficient Routing
Protocol for Cluster-Based
Wireless Sensor Networks
Using Ant Colony Optimization
Ali-Asghar Salehpour, Babak
Mirmobin, Ali Afzali-Kusha, Siamak
Mohammadi
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Outline
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Introduction
Clustering Algorithms
ACO-Based Routing in WSN
Proposed Algorithm
Results and Discussion
Conclusion
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Introduction
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Intra-cluster, cluster members send data
directly to their cluster head.
Inter-cluster, the cluster heads use ant colony
optimization (ACO) algorithm to find a route
to the base station.
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Introduction
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Each cluster is managed by a chosen ClusterHead (CH).
Cluster members send data packets to the
cluster heads which communicate with each
other and send the aggregated packet to the
Base Station (BS).
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Introduction
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The clustering techniques can considerably
reduce the energy consumption.
Use the ant colony optimization (ACO) to find
the optimal route from the cluster heads to the
base station.
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Clustering Algorithms
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In a routing algorithm called LEACH (LowEnergy Adaptive Clustering Hierarchy).
The operation of LEACH is separated into
rounds.
Each round consists of two phases of
clustering and message transmission.
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Clustering Algorithms
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Each non cluster head node sends and receives
data only during its allocated transmission slot.
The cluster head sends the aggregated and
compressed data to the base station.
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Clustering Algorithms
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In HEED (Hybrid Energy-Efficient Distributed
Clustering), the clustering process requires a
number of iterations.
A node becomes a cluster head with a certain
probability which considers a mixture of
energy and communication cost.
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Clustering Algorithms
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All other nodes, which are not cluster head,
select the cluster head which has the lowest
intra-cluster communication cost and directly
communicate with it.
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ACO-Based Routing in WSNS
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The most recognized ACO-based routing
algorithm, AntNet, uses backward and forward
agents or “ants” that explore routing
possibilities throughout the network.
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ACO-Based Routing in WSNS
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At every intermediate node i, an ant chooses
its next hop j toward its destination if it has not
previously visited the next hop.
The next hop is selected based on a
probabilistic decision rule as
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ACO-Based Routing in WSNS
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This enables an ant to make a decision based
on the energy level of the neighbor nodes.
When the forward agent arrives at its
destination node, a backward ant (agent) is
created and the memory of the forward ant is
transferred to the backward ant.
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ACO-Based Routing in WSNS
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The backward ant deposits a quantity of
pheromone on each node given by
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These pheromone values are saved in the node
memory to be used in future decision making
for the next hop by this node.
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ACO-Based Routing in WSNS
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The operation of pheromone evaporation is
used to avoid unlimited accumulation of the
pheromone trails and enables the algorithm to
“forget” previously done bad decisions.
The operation is performed in similar intervals
using
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Proposed Algorithm
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At intervals of definite time (round), first
clustering is done using LEACH and then each
cluster member sends its data to its own CH
directly.
After gathering the data of the members, the
CH sends the gathered data to the BS through
neighbor nodes using ACO.
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Proposed Algorithm
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The proposed approach has three following
steps:
1.
2.
3.
Selection of CH’s and the members of each
cluster.
TDMA scheduling where each CH decides when
each node is to send its data, using TDMA.
Route setup where each node finds the optimal
route to base through CH’s.
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Proposed Algorithm
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After gathering the data of its own members,
each CH adds some parameters to the data for
making a frame (forward ant).
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Proposed Algorithm
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Proposed Algorithm
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After receiving the data by BS, it should
update the pheromone value of the path nodes.
This is performed by the acknowledge frame
transmitted via the backward ants.
If the source node does not receive the
acknowledge frame, after finishing the timeout, the transferred data is sent through another
path.
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Result and Discussion
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The reference network used in our simulations
had 500 nodes with a diameter of 1000 meters.
Each node had 2 joules of initial energy.
The packet size was 2000 bits and five percent
of the nodes were selected as cluster heads.
The base station was chosen randomly in the
network.
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Result and Discussion
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We assume that the energy loss due to the
channel transmission is proportional to the
distance to the power of two.
To transmit a k-bit message to a distance of d,
the dissipated energy is obtained
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Result and Discussion
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Similarly, the dissipated energy to receive a kbit message is given by
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Conclusion
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We proposed a routing algorithm for the
cluster-based large scale wireless sensor
networks using the ant colony optimization.
The simulation results showed a higher system
lifetime and load balancing for the proposed
routing algorithm compared to these routing
algorithms.
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Thank you for your
listening
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