An energy aware scheme for layered chain in underwater wireless sensor networks using genetic algorithm

Extending the network lifetime is a very challenging problem that needs to be taken into account during routing data in wireless sensor networks in general and particularly in underwater wireless sensor networks (UWSN). For this purpose, the present paper proposes a multilayer chain based on genetic algorithm routing (MCGA) for routing data from nodes to the sink. This algorithm consists to create a limited number of local chains constructed by using genetic algorithm in order to obtain the shortest path between nodes; furthermore, a leader node (LN) is elected in each chain followed by constructing a global chain containing LNs. The selection of the LN in the closest chain to the sink is as follows: Initially, the closest node to sink is elected LN in this latter because all nodes have initially the same energy value; then the future selection of the LN is based on the residual energy of the nodes. LNs in the other chains are selected based on the proximity to the previous LNs. Data transmission is performed in two steps: intra-chain transmission and inter-chain transmission. Furthermore, MCGA is simulated for different scenarios of mobility and density of nodes in the networks. The performance evaluation of the proposed technique shows a considerable reduction in terms of energy consumption and network lifespan

Dynamic mobile anchor path planning for underwater wireless sensor networks

In an underwater wireless sensor network (UWSN), the location of the sensor nodes plays a significant role in the localization process. The location information is obtained by using the known positions of anchor nodes. For underwater environments, instead of using various static anchor nodes, mobile anchor nodes are more efficient and cost-effective to cover the monitoring area. Nevertheless, the utilization of these mobile anchors requires adequate path planning strategy. Mzost of the path planning algorithms do not consider irregular deployment, caused by the effects of water currents. Consequently, this leads towards the inefficient energy consumption by mobile anchors due to unnecessary transmission of beacon messages at unnecessary areas. Therefore, an efficient dynamic mobile path planning (EDMPP) algorithm to tackle the irregular deployment and non-collinear virtual beacon point placement, targeting the underwater environment settings is presented in this paper. In addition, EDMPP controls the redundant beacon message deployment and overlapping, for beacon message distribution in mobile assistant localization. The simulation results show that the performance of the EDMPP is improved by increasing the localization accuracy and decreasing the energy consumption with optimum path length

The VF-PSO optimization algorithm for coverage and deployment of underwater wireless sensor network

Coverage is a factor to reflect the network service quality of the Underwater Wireless Sensor Network (UWSN). Existing UWSN has problems of void-hole and low coverage, which is reducing UWSN lifetime and ability to monitor deployment areas. To improve network coverage and network lifetime, a coverage optimization method based on virtual force and particle swarm optimization (VF-PSO) is proposed in this article. By action of virtual force, the underwater mobile nodes would move to a better position to improve network coverage in this method. For the VF-PSO algorithm, the virtual force can guide the optimization of particles and accelerate the convergence of particles to the global optimal solution. This algorithm could not only optimize the movement trend of nodes to maximize the coverage ratio but also adjust the node distance threshold to reduce the network coverage redundancy. Simulation presents that compared with other typical algorithms, VF-PSO can improve the network connectivity and coverage of the UWSN area, and effectively avoid the network void-hole problem