This section focuses on identifying some of the specific approaches in WSNs that are mainly concerned with energy efficiency, faulttolerance, data availability, and multiple base station.
2.1 Fault Tolerance Review:
Researchers in [13] have identified and classified faults in the WSNs into various types as shown in figure-1. Each stage in WSNs has some types of faults which affect the performance of the WSNs. A component faultlike -sensor nodes and base station, or Network Fault like –intermediate nodes failure,affects overall network performance.
A Robust Mutual Authentication Protocol for WSN with Multiple Base-stations [14]:
A robust and effective multiple base station protocol is proposed in the existing work. This protocol alsoaddresses the various security issues in WSNs and analysis has been carried out with respect to the security aspect. Authentication is one of the major securityparametersthat need to be considered for most applications. Figure 2 shows the network topology with multiple base stations.These multiple base stations will optimize the energy consumption of the sensor nodes by reducing the transmission distance.
Fault-Tolerant optimized Multipath routing in WSN [15]:
This reference addresses one of the major limitations of the sensor nodes, which is battery limitation. Here power optimization is focusedon the implementation of clustering techniques with multipath routing. This is based on the LEACH Clustering with multi-path routing. This is implemented considering various parameters like – link quality, delay, and distance within the cluster and outside the cluster.
Energy-efficient and fault-tolerant drone base station [16]:
A heterogeneous fault-tolerant algorithm is proposed considering high-end sensor nodes with more battery capacity. In which the high energy or advanced sensor nodes act as a gateway for collecting the information from normal nodes. Data transmission is carried out in a multipath routing way to ensure fault tolerance within the network. Apart from the heterogenous nodes, this reference focused on addressing the issues with the static base station. To ensure the energy efficiency of the network and reduce the energy consumed for data transfer by sensor nodes a drone is used as basestation. This drone base station effectively tries to aggregate the information from sensors thereby making the network energy efficient.
An Optimal Base Stations Positioning for theInternet of Things Devices [17]:
This paper focused on addressing the challenges in multi-hop data transmission. The main problem identified here is nodes that are near to base station dissipate more energy to transfer the data with unnecessary data transmission using multi-hop.
To overcome this issue and make the network more energy efficient usage ofmultiple base stations and the positioning of each base station in an appropriate location is proposed in this existing work.
FEHCA:A Fault-Tolerant Energy-Efficient Hierarchical Clustering[18]:
In this various issue in hierarchical clustering is identified and addressed with a new solution. Instead of electing the cluster head randomly, a uniform and density-based cluster head are elected. This ensures the uniform distribution of energy over the network and thereby enhances the overall network performance.
Clustering of WSN based on PSOwith fault tolerance and efficient multidirectional routing [19]:
To optimize the energy dissipation in the network particle swarm optimization approach is used in this paper. This clustering approach comes with a master cluster head and a surrogate cluster head. The clustering with this approach works in multidirectional routing. The role of the surrogate cluster head is to act as a temporary cluster head when there is any fault with the actual cluster head.
Towards Clustering Technique for a Fault Tolerance Mobile Agent [20]:
To overcome the energy-related performance issues in WSNs a mobile agent-based clustering is proposed in this method. Using the mobile agent nodes can communicate to the base station with optimized energy dissipation. This mobile agent is assumed to be very effective to ensure the optimal energy utilization of the sensor nodes in the network.
Fault Tolerance in WSN Through Uniform Load Distribution Function [21]
A uniform cluster formation approach is used here to overcome the various energy dissipation issues in the WSNs routing algorithm. The uniform way of selecting clusters and members will be effective and distribute the load effectively within the cluster and network. This uniform load distribution ensuresequal energy dissipation from all the nodes and also avoids fault tolerance in the network.
Intelligent Fault-Tolerance Data Routing Scheme for IoT-Enabled WSNs [22]:
An IoT-based application requirement of WSNs is discussed in this paper highlighting the application features and issues of WSNs in IoT. IoT works with real-time data collection and application information any fault or link failure in the network will fail applications. A reinforcement learning-based algorithm is used here to identify the faulty nodes in the network. Finally, this is evaluated for detecting false alarms, accuracy, throughput, and lifetime of the network.