Energy-Efficient Routing Algorithm Based on Small-World Characteristics

Water quality sensor networks are widely used in water resource monitoring.However,due to the fact that the energy of these networks cannot be supplemented in time,it is necessary to study effective routing protocols to extend their lifecycle.To address the problem of limited resources,a routing optimization algorithm based on a small-world network model is proposed.In this paper,a small-world network model is introduced for water quality sensor networks,in which the short average path and large clustering coefficient of the model are used to construct a super link.A short average path can reduce the network’s energy consumption,and a large coefficient can improve its fault-tolerance ability.However,the energy consumption of the relay nodes near the heterogeneous node is too great,and as such the energy threshold and non-uniform clustering are constructed to improve the lifecycle of the network.Simulation results show that,compared with the low-energy adaptive clustering hierarchy routing algorithm and the best sink location clustering heterogeneous network routing algorithm,the proposed improved routing model can effectively enhance the energy-utilization.The lifecycle of the network can be extended and the data transmission amount can be greatly increased.

Energy-Efficient Deployment of Water Quality Sensor Networks

Water quality sensor networks are promising tools for the exploration of oceans.Some key areas need to be monitored effectively.Water quality sensors are deployed randomly or uniformly,however,and understanding how to deploy sensor nodes reasonably and realize effective monitoring of key areas on the basis of monitoring the whole area is an urgent problem to be solved.Additionally,energy is limited in water quality sensor networks.When moving sensor nodes,we should extend the life cycle of the sensor networks as much as possible.In this study,sensor nodes in non-key monitored areas are moved to key areas.First,we used the concentric circle method to determine the mobile sensor nodes and the target locations.Then,we determined the relationship between the mobile sensor nodes and the target locations according to the energy matrix.Finally,we calculated the shortest moving path according to the Floyd algorithm,which realizes the redeployment of the key monitored area.The simulation results showed that,compared with the method of direct movement,the proposed method can effectively reduce the energy consumption and save the network adjustment time based on the effective coverage of key areas.

Optimal Deployment of Heterogeneous Nodes to Enhance Network Invulnerability

Wireless sensor networks(WSN)can be used in many fields.In wireless sensor networks,sensor nodes transmit data in multi hop mode.The large number of hops required by data transmission will lead to unbalanced energy consumption and large data transmission delay of the whole network,which greatly affects the invulnerability of the network.Therefore,an optimal deployment of heterogeneous nodes(ODHN)algorithm is proposed to enhance the invulnerability of the wireless sensor networks.The algorithm combines the advantages of DEEC(design of distributed energy efficient clustering)clustering algorithm and BAS(beetle antenna search)optimization algorithm to find the globally optimal deployment locations of heterogeneous nodes.Then,establish a shortcut to communicate with sink nodes through heterogeneous nodes.Besides,considering the practical deployment operation,we set the threshold of the mobile location of heterogeneous nodes,which greatly simplifies the deployment difficulty.Simulation results show that compared with traditional routing protocols,the proposed algorithm can make the network load more evenly,and effectively improve energy-utilization and the fault tolerance of the whole network,which can greatly improve the invulnerability of the wireless sensor networks.

Coverage Control for Underwater Sensor Networks Based on Residual Energy Probability

Underwater sensor networks have important application value in the fields of water environment data collection,marine environment monitoring and so on.It has some characteristics such as low available bandwidth,large propagation delays and limited energy,which bring new challenges to the current researches.The research on coverage control of underwater sensor networks is the basis of other related researches.A good sensor node coverage control method can effectively improve the quality of water environment monitoring.Aiming at the problem of high dynamics and uncertainty of monitoring targets,the random events level are divided into serious events and general events.The sensors are set to sense different levels of events and make different responses.Then,an event-driven optimization algorithm for determining sensor target location based on self-organization map is proposed.Aiming at the problem of limited energy of underwater sensor nodes,considering the moving distance,coverage redundancy and residual energy of sensor nodes,an underwater sensor movement control algorithm based on residual energy probability is proposed.The simulation results show that compared with the simple movement algorithm,the proposed algorithm can effectively improve the coverage and life cycle of the sensor networks,and realize real-time monitoring of the water environment.

Network Invulnerability Enhancement Algorithm Based on WSN Closeness Centrality

Wireless Sensor Network(WSN)is an important part of the Internet of Things(IoT),which are used for information exchange and communication between smart objects.In practical applications,WSN lifecycle can be influenced by the unbalanced distribution of node centrality and excessive energy consumption,etc.In order to overcome these problems,a heterogeneous wireless sensor network model with small world characteristics is constructed to balance the centrality and enhance the invulnerability of the network.Also,a new WSN centrality measurement method and a new invulnerability measurement model are proposed based on the WSN data transmission characteristics.Simulation results show that the life cycle and data transmission volume of the network can be improved with a lower network construction cost,and the invulnerability of the network is effectively enhanced.

Reliable flight performance assessment of multirotor based on interacting multiple model particle filter and health degree

Multirotor has been applied to many military and civilian mission scenarios. From the perspective of reliability, it is difficult to ensure that multirotors do not generate hardware and software failures or performance anomalies during the flight process. These failures and anomalies may result in mission interruptions, crashes, and even threats to the lives and property of human beings.Thus, the study of flight reliability problems of multirotors is conductive to the development of the drone industry and has theoretical significance and engineering value. This paper proposes a reliable flight performance assessment method of multirotors based on an Interacting Multiple Model Particle Filter(IMMPF) algorithm and health degree as the performance indicator. First, the multirotor is modeled by the Stochastic Hybrid System(SHS) model, and the problem of reliable flight performance assessment is formulated. In order to solve the problem, the IMMPF algorithm is presented to estimate the real-time probability distribution of hybrid state of the established SHS-based multirotor model, since it can decrease estimation errors compared with the standard interacting multiple model algorithm based on extended Kalman filter. Then, the reliable flight performance is assessed with health degree based on the estimation result. Finally, a case study of a multirotor suffering from sensor anomalies is presented to validate the effectiveness of the proposed method.