Self-Organized Proactive Routing Protocol for Non-Uniformly Deployed Underwater Networks

Abstract

Electromagnetic (EM) waves cannot propagate more than few meters in sea water due to the high absorption rate. Acoustic waves are more suitable for underwater communication, but they travel very slowly compared to EM waves. The typical speed of acoustic waves in water is 1500 m/s, whereas speed of EM waves in air is approximately 3 × 10 8 m/s. Therefore, the terrestrial wireless sensor network (WSN) protocols assume that the propagation delay is negligible. Hence, reactive protocols are deemed acceptable for WSNs. Other important issues related to underwater wireless sensor networks (UWSNs) are determining the position of the underwater nodes and keeping a time synchronization among the nodes. Underwater nodes can neither determine their position nor synchronize using Global Navigation Satellite Systems (GNSS) because of the short penetration of EM waves in sea water. The limited mobility of UWSN nodes and variation in the propagation speed of acoustic waves make time synchronization a challenging task for underwater acoustic networks (UASNs). For all these reasons, WSN protocols cannot be readily used in UASNs. In this work, a protocol named SPRINT is designed to achieve high data throughput and low energy operation in the nodes. There is a tradeoff between the throughput and the energy consumption in the wireless networks. Longer links mean higher energy consumption. On the other hand, the number of relay nodes or hops between the source node and the final destination node is a key factor which affects the throughput. Each hop increases the delay in the packet forwarding and, as a result, decreases the throughput. Hence, energy consumption requires the nearest nodes to be chosen as forwarding nodes, whereas the throughput requires the farthest node to be selected to minimize the number of hops. SPRINT is a cross-layer, self-organized, proactive protocol which does not require positioning equipment to determine the location of the node. The routing path from the node to the gateway is formed based on the distance. The data sending node prefers to choose the neighbor node which is closest to it. The distance is measured by the signal strength between the two nodes. the sea (Figure 1). The suspended sensor nodes in 3D networks keep moving in all directions. This movement is limited by the length of the connecting rope or chain. The continuous random movement of the nodes makes the protocols design more challenging in 3D networks.Sensors 2020, 20, x FOR PEER REVIEW 2 of 21 directions. This movement is limited by the length of the connecting rope or chain. The continuous random movement of the nodes makes the protocols design more challenging in 3D networks.

Energy-Efficient Packet Forwarding Scheme Based on Fuzzy Decision-Making in Underwater Sensor Networks

“…The effect of network size (actually, the network density) on the average number of hops is shown in Figure 17 , jointly with the average number of hops of SPRINT protocol taken from [ 4 ]. In comparison of two graphs, it is well evident that average number of hops of the proposed fuzzy scheme is lower than the same figure obtained with SPRINT protocol.…”

“…As already mentioned, the proposed routing algorithm is based on a previous work, the protocol SPRINT [ 4 ], which also addresses the energy consumption issue.…”

“…The proposed protocol is based on SPRINT protocol [ 4 ], which is designed to achieve trade-off between energy consumption and throughput. A packet forwarding node selects one of its neighbors as a relay node.…”

“…Table 4 shows some examples of the results obtained. It is well known that using the fuzzy logic to choose the forwarding node becomes very easy compared to SPRINT [4], which uses the weights method using normalized values to select the forwarding node and RECRP [6], which uses RSSI and Doppler scale shift measurement to estimate distance using optimal min-max method, and next hop selection is based on the information in a routing table that is updated from the beginning to the ending node. In [6], due to regular updates of the routing table, the energy consumption will be increased.…”

“…In this work, the problem of energy efficiency in routing protocols in underwater acoustic communication networks is addressed. A routing algorithm is proposed that improves the energy efficiency of a previous work [ 4 ]. The principle of operation of the new algorithm chooses the forwarding node by fuzzy logic interference.…”