IJCSNS International Journal of Computer Science and Network Security, VOL.18 No.12, December 2018

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Manuscript received December 5, 2018 Manuscript revised December 20, 2018

EBRA: Energy Balanced Routing Algorithm for Underwater Wireless Sensor Network

Mukhtiar Ahmed1, Rajab Malookani2, Mujeeb ur Rehman3, Nadeem Naeem4, Sajida Parveen5

Quaid-e-Awam University of Engineering, Science and Technology Nawabshah, Sindh, Pakistan1,2,4,5 Shah Abdul Latif University Khairpur Mirs, Sindh, Pakistan3

Summary Seabed is full of the application based information, which needs to explore for commercial purpose because at the bottom of the sea, the gold, silver, diamond, coal mines and valuable information is placed. To explore that information to the sea surface needs the designing of the routing protocols. The majority number of the routing protocols are designed for such kind of information retrieval but these routing protocols still faces some majority number of the challenges like: route broken issue between nodes due to the water pressure, depth controlling issue from sea surface to seabed, uncontrollable node mobility, water current issue, deployment issue and battery prolong issue. To maintain the link issue between nodes, control the depth of water, and prolong the battery power of nodes Energy Balance Routing Algorithm (EBRA) is proposed. In EBRA the water depth is controlled by formation of multiple layers from sea surface to seabed. To balance the battery power of nodes EBRA uses the powerful static relay nodes which have more power as compare to other sea water nodes. To control the node mobility the deployment of ordinary nodes at seabed level through multipath with Path Weight mechanism has been adapted for EBRA. The simulator NS2.30 with AquaSim is used for performance analysis. The EBRA is compared with EE-DBR and EMGGR and simulation response of EBRA is better than EE-DBR and EMGGR. Key words: Propagation_delay; link_quality; node_movement, Energy_ balanced; Consumption.

1. Introduction

Now a days Underwater Wireless Sensor Network (UWSN) is more popular area for researchers due to its majority number of applications like: tactical surveillance, disaster prevention, oceanography data collection, assisted navigation and maritime rescue [1-5]. Most of the current routing protocols refer the terrestrial wireless sensor network but underwater environment degrades such type of the networks [6-9]. Underwater environment supports the acoustic channel for data forwarding [10-12]. The sensor node for existing routing protocols consumes the more energy due to improper data forwarding mechanism; the battery replacement in underwater harsh environment is one of the complicated tasks because sensor node is born with limited battery power. To uphold the network

lifetime and balance the battery power of the ordinary sensor nodes in underwater environment with consideration of acoustic channel parameters the design of balanced energy consumption routing protocol is important. The energy consumption of sensor node may be affected due to transmission loss, path loss, data load, and transmission distance. This paper focuses the design of Energy Balanced Routing Algorithm (EBRA) for underwater wireless sensor network which performs the following tasks:

i. Multipath between bottom source nodes and relay nodes reduces the energy consumption.

ii. Selection of powerful relay node balances the battery life of the ordinary sensor nodes.

iii. Energy efficient route selection mechanism keeps the balanced energy consumption for the entire network.

iv. Use of relay nodes and sink nodes keep the better performance of the entire network during sparse of nodes.

2. Literature Review

Underwater environment cannot support the fixed topological structure due to its environmental conditions [13-15]. Majority of the researchers have designed the dynamic node mobility routing protocols but due to node movement the energy level of the sensor may drop abruptly [1, 10, 12, 16, 17]. To maintain the energy level of ordinary sensor node in underwater is a challenging issue. This section focuses the energy problems with existing routing protocols. In [18] the Depth Based Routing (DBR) protocol is proposed. DBR is based on depth addressing mechanism from source to sink node. In DBR the multiple copies of the same data packets are shared between sensor nodes and the limited battery power of sensor nodes will die earlier due to duplication of shared packets [19, 20]. It is also observed that in DBR when network become sparse the ratio of dropping packets also affects the battery life of the sensor node.

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In [21] the Directional Depth Based Routing (D-DBR) is proposed which is based on ToA ranging technique with geometrical model. It is observed that when network becomes sparse the majority of the nodes drops the data packets and will die earlier. In [21] an Energy Efficient Depth Based routing protocol is proposed which is the second version of D-DBR ; authors have used the same technique as used in D-DBR for packets forwarding; but it is also failure when network becomes sparse. In [10] the Energy-efficient Multipath Grid Based Geographic Routing (EMGGR) protocol is proposed. EMGGR is based on logical grids with xyz addressing mechanism. The virtual cell development mechanism is adapted to relay the data packets. It is observed that complicated grid formation mechanism affects the energy level of the sensor nodes because sensor nodes drop the packets due to the increasing distance in between source and virtual cell. Proposed EBRA resolves the problems of existing routing protocols with selection of efficient path development in between source and relay nodes and the use of the powerful relay nodes prolongs the battery life of the ordinary sensor nodes.

3. EBRA Operation

Fig.1, focuses architecture of EBRA. In network architecture sink nodes are placed on water surface and connected with onshore data centre. RF signalling is used to connect the sink nodes between each other and in same way with onshore centre for data sharing purpose. Static relay nodes are positioned on different layers. Source nodes are positioned at the seabed level and ordinary nodes are positioned in between layer-7 relay nodes and source nodes. Source nodes are liable to collect the application based data from the seabed and forward to the layer-7 relay nodes. The multipath route develop mechanism is adapted in between source nodes and bottom layer relay nodes through ordinary sensor nodes.

Fig. 1 EBRA Network architecture

In EBRA the energy aware routing mechanism is proposed in between relay nodes and source nodes. If source nodes have data packets and want to forward towards relay nodes then source node will look the residual energy level of nodes and hop counts. The source nodes and intermediate nodes are responsible to select the route for data forwarding with higher residual energy and shortest distance (hop counts) which improves the overall performance of the network. We have modified the Equation (1) for EBRA as mentioned in [22]. Equation (1) calculates the Path_Weight (PW) as mentioned below:

𝑃𝑃𝑃𝑃 = 𝐸𝐸 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝐸𝐸𝐸𝐸𝑅𝑅𝐸𝐸𝐸𝐸𝐸𝐸 + 𝐻𝐻 ℎ𝑜𝑜𝑜𝑜 𝑐𝑐𝑜𝑜𝑅𝑅𝐸𝐸𝑡𝑡 (1) The parameter 𝐸𝐸 indicates the residual energy, and 𝐻𝐻 indicates the hop count. The selected parameters are uniform in proportion with equal impact in route selection. The parameters can be varied according to the application requirement. In route selection mechanism for data forwarding the set of nodes that optimized the PW will enhance the data delivery ratio. The node selection criteria are based on residual energy threshold; if the threshold is greater than 20% that node will be selected for path development. With 20% of threshold, less number of nodes will be selected for data forwarding mechanism. The data forwarding mechanism is based on Route Request (RREQ) and Route Reply (RREP); when source node forwards the RREQ to the neighbour node; every node will embed the link quality, residual energy, and hop count to the RREQ format. If the residual energy threshold is above the 20% then that node will forward the RREP to source or forwarder node. If threshold level of the node is below the threshold of 20% then that will drop the RREQ. When multiple RREPs received by source node; the source node will decide for the optimal path through PW. We have modified the Algorithm 1 and Algorithm 2 as defined by Ahmed, et al. [22]. Algorithm 1 focuses RREQ mechanism for EBRA scheme and Algorithm 2 focuses the RREP mechanism. Algorithm 1: Energy Efficient Data Forwarding Route Request

(RREQ) 1. Initialization of Route Request (RREQ) 2. Let RREQnet denotes the network diameter 3. Let Np denotes the previous node 4. Let Nc denotes the current node 5. Let Eth denotes the Energy threshold 6. _______________________________________________ 7. if route is not available for destination node then 8. call procedure Forward call RREQ 9. else 10. return 11. endif 12. Procedure Forward call RREQ 13. while RREQnet > 0 do 14. Forward RREQ to the next neighbor node 15. Np ← Nc

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16. Nc ← R current node 17. if Energy of Nc < Eth then drop the RREQ 18. terminate 19. endif 20. if Nc = destination node then call procedure

RREP 21. return 22. endif 23. RREQnet ← RREQnet - 1 24. end while 25. end procedure Algorithm 2: Energy Efficient Data Forwarding Route Reply

(RREP) 1. Initialization of Route Reply (RREP) 2. Let RREPnet denotes the network diameter 3. Let Np denotes the previous node 4. Let Nc denotes the current node 5. Let RREPenergy denotes Route Reply for residual energy 6. Let RREPhop denotes Route Reply for hop count 7. Let lth denotes link quality threshold 8. _______________________________________________ 9. Procedure RREQ 10. while RREPnet > 0 do 11. unicast RREP to the next neighbor node 12. Np ← Nc 13. Nc ← current node 14. if link quality of Nc < lth then 15. drop RREP 16. Terminate 17. endif 18. if Nc = destination node then 19. Path_Weight (PW) = Q× RREPlq + E× RREPenergy

+ H× RREPhop 20. if PW < PW of previous RREP for the same

destination node then 21. update PW for same destination node 22. endif 23. terminate 24. endif 25. update RREPlq 26. update RREPenergy 27. RREPhop = RREPhop + 1 //update RREPhop 28. RREPnet = RREPnet + 1 29. end while 30. end procedure In EBRA scheme, the route selection mechanism is defined through a following example. The values are assigned to every link with its residual energy, and hop count from source to courier node. The residual energy threshold is set on 46 joules and above of total energy level of 70 joules, and the hop count is based on the number of hops from source to courier.

Mechanism of EBRA is described in following steps:

Step-1: First the source node will check the entry of courier node to its local routing table if it exits and qualifies the link quality and residual energy according to

its threshold values then it will forward the data packets directly. If courier node not exist then source node forwards the RREQ from source to its next hop neighbour nodes after qualifying the threshold level of residual energy. In Fig. 2 the RREQ message is forwarded to the N, J, and K neighbour nodes. Step-2: If node N, J, and K receive the RREQ then nodes N, J, and K will check the threshold level of residual energy. If nodes N, J, and K receive the same packets and the residual energy is below the threshold level then these nodes will drop the RREQ. Otherwise node N, J, and K check the route for the courier node in their local routing table. If route exist then RREP forwarded to the source node through reverse route. If the route is not exist in the local routing table of the N, J, and K them RREQ further forwarded to the next hop nodes whose residual energy level is not less than threshold level. The RREQ and RREP are illustrated with dotted lines in Fig. 2.

Fig. 2 RREQ and RREP mechanism from source to courier node

Step-3: When RREQ is received from all the nodes through different routes to the courier node; the courier node will unicast the RREP in reverse direction through all the nodes on their subsequent path to the source node. Step-4: Source node calculates the optimal path through PW according to Equation (1). The set of PW path is given below:

i. Source → N→ E → A → Courier = 60.05 ii. Source → K→ B → Courier = 43.09 iii. Source → J→ P → C → Courier = 58.49 iv. Source → K→ P → C → Courier = 56.75 v. Source → K→ E → A → Courier = 57.99 vi. Source → K→ B → A → Courier = 57.96 vii. Source → K→ B → C → Courier = 60.05

From above set of PW of: Source → K→ B → Courier is 43.09 is the lower value among all the set of paths; so source node will select this optimal path for packets forwarding to the courier node. Fig. 3 shows through the thick line from source to courier node.

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Fig. 3 Optimal route from source to courier node

4. Performance Analysis

This section refers the energy consumptions of EBRA on different node mobility patterns, energy consumptions on relay nodes, and energy consumption on different sink nodes. For performance analysis the NS2 simulator has been used. NS2 simulation parameters are given in Table 1.

Table 1. NS2 performance parameters. Parameters Rating

Network Size 1500m x 1500m No. of Nodes 350

Surface to bottom layer distance 250m Data Packet size 64 byte

Initial Energy 50 J MAC Protocol [23] 802.11-DYNAV

Routing Pipe in VBF 100 m Energy consumption for transmitting 2w

Energy consumption for receiving 0.75w Energy consumption for idle listening 8mw

Energy Threshold 20% of initial Transmission range 100 m to 150 m

Surface sink distance difference 100 m Number of layers 7

Number of relay nodes 49 Simulation time 1000 sec

EBRA Energy Consumption on node mobility

In Fig. 4, the energy consumption is measured on static node, node with movement of 2 m/sec, and node with movement of 3 m/sec. It is observed that node mobility has no staid effect on energy consumption, because there are minor changes on the results as compare to static node. The movement of node can show the much more variations in sparse area. The behaviour of node movement is considered towards the relay nodes and relay nodes are fixed on the different layers, so in this scenario the movement of node can be considered as vertical. In EBRA the route selection mechanism is based on the PW as mentioned in Equation (1), the RREQ and RREP mechanism refers the PW. EBRA scheme denies the location information based routing tables; so obviously the node mobility cannot affect much more on energy consumption.

Fig. 4 No. of nodes versus Energy Consumptions with node mobility

EBRA Energy Consumptions on relay nodes

In Fig. 5, the energy consumptions with respect to number of nodes is measured on Courier node 1, Courier node 3, and Courier node 7 (bottom layer relay nodes). The presence of the relay nodes enhances the battery life of the ordinary sensor nodes. EBRA refers the multipath development mechanism from courier to source nodes through ordinary sensor nodes. The bottom layer fixed relay nodes are responsible to forward the data packets to the other relay nodes which are deployed on different layers from top to bottom. Here the bottom layer relay nodes forward the data packets to the top level relay nodes. In Fig. 5 the energy consumption is reduced when the number of relay nodes increases. When there are seven relay nodes the energy consumption is reduced as compare to courier node 1 and courier node 2. The simulation taste case is based on cumulative response of 7 relay nodes on bottom layer.

EBRA Energy Consumption on sink nodes

In Fig. 6 the energy consumption for EBRA is measured on sink 1, sink 3, and sink 7; the sink nodes are deployed on the water surface. It is observed that when the number of sink nodes increases the energy consumption reduces.

Fig. 5 No. of nodes versus Energy Consumptions with different relay nodes

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EBRA refers the multi-sink deployment mechanism on the water surface and the multipath mechanism at the bottom level of water with usage of relay nodes, sensor nodes, and source nodes. It is observed that when the data packets received on the water surface sink nodes the cumulative response of the energy consumption is measured on 7 numbers of sinks that is reduces as compare to cumulative response on 3 numbers of sink nodes and 1 number of sink node.

Fig. 6 No. of nodes versus Energy Consumptions with different sink nodes

Comparison of EBRA with other Routing Protocols

In this section the performance analysis of EBRA for energy consumption and data delivery is compared with the Energy-efficient Multipath Grid-based Geographic Routing (EMGGR) and Energy Efficient Depth Based Routing (EE-DBR).

EBRA comparison with EMGGR

In Fig. 7, the energy consumption of EBRA and EMGGR is shown, the average cumulative energy consumption of EBRA is reduced than EMGGR because in EBRA the powerful fixed relay nodes enhance the battery life of the ordinary sensor nodes. The mechanism for node selection is also based on the PW and the calculation of PW considers the residual energy of the sensor node with its threshold value greater than 20% of the initial energy. The PW also considers the link quality and hop count mechanism. The three factors involved in route selection mechanism in EBRA reduce the average energy consumption of the entire network. In EMGGR the formation of virtual cells and selection of the gateway node is time consuming and it is also observed that when gateway node move away from the selected path the packets loss rate will be increased and ordinary node will drop the data packets continuously and will die earlier. In EMGGR it is also observed that when the number of nodes increases the performance of EMGGR remains worst. The

energy consumption of EMGGR is not better in performance in dense and as well as in sparse areas.

Fig. 7 Energy Consumption for EBRA versus EMGGR

EBRA comparison with EE-DBR

In this section the comparison between EBRA and EE-DBR for energy consumption is shown. Fig. 8 focuses the number of nodes versus energy consumption for EBRA and EE-DBR. The energy consumption of EBRA is lower than EE-DBR because the use of powerful relay nodes and PW route selection mechanism enhances the lifetime of the ordinary sensor nodes. EBRA consumes the less energy as compare to EE-DBR because EBRA is based on optimal route selection with PW. On other hand the EE-DBR scheme is based on ToA technique; which is suitable only for air medium; in underwater environment the performance of ToA technique is very slow due to the acoustic channel behaviour. The increasing and decreasing of distance due to water pressure with node mobility effects the ToA. When distance increases the sensor node will utilize the maximum power of its battery and will consume the high energy.

Fig. 8 Energy Consumption EBRA versus EE-DBR

5. Conclusion

EBRA is based on the selection of the energy efficient route between source nodes and relay nodes. The route selection mechanism is based on residual energy and minimum hop count; the addition of these two parameters makes the Path_Weight (PW). The RREQ and RREP are

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based on the PW. RREQ and RREP algorithms show the complete mechanism for the route selection and data forwarding. The route selection mechanism is also explained in the example which shows the selection of the optimal route. The analysis of the EBRA shows energy consumption of the EBRA on relay nodes, on different speed of nodes, and on sink nodes deployed on the water surface. The comparison of EBRA with EMGGR and EE-DBR is shown with energy consumption. The energy consumption of the EBRA is lower than EMGGR and EE-DBR because in EBRA the powerful relay nodes enhance the battery life of the ordinary sensor nodes. References [1] P. V. Amoli, "An Overview on Current Researches on

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