Geographic multipath routing based on geospatial division in duty-cycled underwater wireless sensor networks. (January 2016) - Jiang, Jinfang; Han, Guangjie; Guo, Hui; Shu, Lei; Rodrigues, Joel J.P.C
Abstract: In Underwater Wireless Sensor Networks (UWSNs), the geographic routing is a preferred choice for data transmission due to the unique characteristics of underwater environment such as the three dimensional topology, the limited bandwidth and power resources. This paper focuses on underwater routing protocols in the network layer, where underwater sensor nodes can collaborate with each other to transfer data information. The three dimensional underwater network is first divided into small cube spaces, thus data packets are supposed to be collaboratively transmitted by unit of small cubes logically. By taking complex properties of underwater medium into consideration such as three dimensional topology, high propagation delay and path loss of acoustic channel, we propose two novel multi-path strategies called Greedy Geographic Forwarding based on Geospatial Division (GGFGD) and Geographic Forwarding based on Geospatial Division (GFGD). The proposed two algorithms mainly consist of two phases, choosing the next target small cube, and choosing the next hop node in the target small cube. Furthermore, all the sensor nodes in the network are duty-cycled in the MAC layer. Finally, performance analysis is derived, and simulation results illustrate the performance improvement in finding route paths, optimal length of found paths. In addition, energy consumption of route finding is reduced and propagation delay of data transmission is decreased. Abstract : Highlights: In this paper, two geographic multipath routing algorithms named GGFGD and GFGD were proposed. First, the network is logically divided into Small Cube (SC) spaces. Then, based on the SCs and the relative position of sensor nodes, some target SCs are selected. Only the neighbor nodes in the selected target SCs are used for data directional transmission. Moreover, we take sleep schedule into account, which helps to save energy consumption and prolong network lifetime.