1

S& EDG: Scalable and Efficient

Data Gathering Routing Protocol for Underwater

Wireless Sensor Networks

Prepared by:Naveed IlyasMS(EE), CIIT, Islamabad, Pakistan

2

Motivation(1/2)

• Major challenges in UWSNs include:• Low data delivery ratio due to multipath fading and high attenuation• Multiple transmissions and receptions lead to high energy consumption• Multi-hop communication in underwater cause high energy consumption

• AUV aided based routing not considered the following parameters:• Dynamic sojourn interval of AUV• Optimal assignment of member nodes with GN• Scalability of network, which leads to low data delivery ratio and high energy

consumption

3

Motivation(2/2)

• We propose a novel scalable and efficient data gathering scheme for UWSN named as S& EDG• Present a criterion for scalable network, that how energy consumption will be

minimized with high data delivery ratio

• Our protocol will dynamically assign• Sojourn interval to GN on the basis of number of packets received• Number of associated member nodes

4

Overview of S& EDG Protocol

• Sensor nodes randomly deployed at the bottom of ocean

• Predefined elliptical path of AUV

• AUV and sensor nodes know their location through any localization mechanism

• Nodes are varied from 100 to 1000 nodes in a field of 100m*100m to check the performance of our proposed protocol in scalable network

• Selection of GNs on the basis of RSSI value

• Association of member nodes through SPT

5

Protocol Operation(1/6)

• Network establishment to data transmission is divided into two phases:• Setup Phase • Steady state

• Setup Phase• Nodes are randomly deployed at the bottom of ocean.• AUV moves on predefined elliptical trajectory and aware of global knowledge of

network.• AUV transmits ‘hello packet’ packets after a specific interval of time• GNs are selected on the basis of RSSI value of ‘hello packet’ (node with highest RSSI

value of ‘hello packet’ selected as GN).

6

Protocol Operation(2/6)

• Association of member nodes with GN through SPT.• Restricting the number of member nodes with GN in order to reduce extra burden on

it.• Allocation of variable sojourn time to AUV on the basis of number of member nodes

attached with GN

• Deployment of Nodes• Nodes are randomly deployed at the bottom of ocean• ‘X’ number of nodes are randomly deployed in the field of 100*100 m• ‘X’ is varying from 100 to 1000 nodes• Evaluate the performance of our proposed protocol by varying the number of nodes.

7

Protocol Operation(3/6)

• AUV Movement Pattern• Trajectory of AUV is elliptical

• Restriction on Number of Member Nodes• Purpose of this restriction is to reduce the burden on GN• Energy consumption of GNs are minimized which reduces the overall energy

consumption of network.

8

Protocol Operation(4/6)

• Chain Formation• Chain formation is based on the RSSI value of ‘hello packet’ transmitted by AUV• AUV conduct ‘Energy Test’ to check the residual energy of each member node• Member nodes whose residual energy is greater than zero will participate in the chain

formation of SPT• When chain is formed each member node forwards its data until it reaches to GN

• Sojourn Interval of AUV• Duration of AUV stays at any sojourn location meanwhile receiving data from the GN• Sojourn interval depends upon

• Number of packets transmitted• Number of member nodes attached with GN

9

Protocol Operation(5/6)

• Steady State Phase• Member nodes forward their data through shortest path• GNs aggregate the data from member nodes and transmit to passing AUV• GNs are changed if their residual energy reduced from predefined threshold

(threshold for residual energy is 20 joule)• Member nodes associate with new GN through new SPT• Selection of new GN is conveyed to AUV• AUV collects data from new GN

10

Protocol Operation(6/6)

• S& EDG is implemented for scalable network to test:• Throughput• Energy consumption• End-to-end delay• Network lifetime

• S& EDG perform well in all parameters except end-to-end delay

11

Simulation Results (1/5)

• S& EDG perform well in scalable network in terms of throughput as compared to AEERP

• Throughput of S&EDG increase as the number of sensor nodes increases

• Variable sojourn interval for each GN enhanced the data collection

12

Simulation Results (2/5)

• End-to-end delay of S& EDG is maximum as compared to AEERP

• As the number of nodes increase, the sojourn interval also increases, hence end-to-end-delay increases

• Tradeoff between throughput and end-to-end delay in S& EDG

13

Simulation Results (3/5)

• Network lifetime depends upon the energy consumption

• Energy consumption is minimized at GNs

• Our S&EDG protocol perform little bit better then AEERP in terms of network lifetime due to minimum depletion of energy at GNs

14

Simulation Results (4/5)

• S& EDG has low energy consumption in scalable network as compared to AEERP

• Energy consumption is minimized only because of restricting member nodes with GN

15

Simulation Results (5/5)

• Delivery ratio of S& EDG is better then AEERP

• When network density increases, the chances of collision also increase due to multiple transmission and receptions, so in dense network the packet delivery ratio decreases as depicted by figure

• S& EDG perform well when there are optimal number of sensor nodes in the network field

16

Conclusion and Future Work (1/2)

• Presented a scalable scheme for efficient data gathering called S& EDG• In S& EDG, the limited association of member nodes with GN

enhanced• Network lifetime • Balance the energy consumption

• Dynamic sojourn interval of AUV with GN maximized• Throughput• Packet delivery ratio

17

Conclusion and Future Work (1/2)

• Simulation results depicted that, S& EDG perform well as compared to AEERP in scalable network in terms of throughput and energy consumption

• For future work, we will implement our technique on different scenarios• Various trajectories of AUV• We also plan to propose a mathematical model for different trajectories of AUV in

near future.