An Efficient Cluster-based Routing Protocol for Improvement Delay in Mobile Ad-hoc Networks

Cluster-based routing in Mobile Ad-Hoc Networks is considered one of the convenient methods of routing. The existence of Cluster Head (CH) in a group of nodes for data forwarding improves the performance of routing in terms of routing overhead and power consumption. In this paper, a clustering algorithm using hierarchical routing for mobile ad hoc networks is proposed. In the proposed method, first, clusters are formed by the FLOC clustering method with low overlapping. Then, according to the most important network criteria, including hop count, noise ratio, distance, remaining energy, and link expiration time, head clusters are selected based on the weighting algorithm. To transfer data in the proposed method, two types of communication are used, e.g., inter-cluster communication and intra-cluster communication in which the shortest path to the target cluster is selected. The proposed P-METHOD technique is based on hierarchy and clustering as well as using a weighted algorithm that reduces delay in data transmission on the network. Moreover, P-METHOD is evaluated here via extensive simulations carried out in NS-2. The simulation results indicate that the MANET network performance metrics are improved in terms of average throughput, Packet Delivery Ratio (PDR), delay, residual energy, and lifetime.

Optimal Cluster Head Positioning Algorithm for Wireless Sensor Networks

Wireless sensor networks (WSNs) are increasingly gaining popularity, especially with the advent of many artificial intelligence (AI) driven applications and expert systems. Such applications require specific relevant sensors’ data to be stored, processed, analyzed, and input to the expert systems. Obviously, sensor nodes (SNs) have limited energy and computation capabilities and are normally deployed remotely over an area of interest (AoI). Therefore, proposing efficient protocols for sensing and sending data is paramount to WSNs operation. Nodes’ clustering is a widely used technique in WSNs, where the sensor nodes are grouped into clusters. Each cluster has a cluster head (CH) that is used to gather captured data of sensor nodes and forward it to a remote sink node for further processing and decision-making. In this paper, an optimization algorithm for adjusting the CH location with respect to the nodes within the cluster is proposed. This algorithm aims at finding the optimal CH location that minimizes the total sum of the nodes’ path-loss incurred within the intra-cluster communication links between the sensor nodes and the CH. Once the optimal CH is identified, the CH moves to the optimal location. This suggestion of CH re-positioning is frequently repeated for new geometric position. Excitingly, the algorithm is extended to consider the inter-cluster communication between CH nodes belonging to different clusters and distributed over a spiral trajectory. These CH nodes form a multi-hop communication link that convey the captured data of the clusters’ nodes to the sink destination node. The performance of the proposed CH positioning algorithm for the single and multi-clusters has been evaluated and compared with other related studies. The results showed the effectiveness of the proposed CH positioning algorithm.

LEACH-VD

Wireless sensor networks act as an important role in the wireless communication area because of its properties, its intelligence, cheaper costs, and its smaller size. Multiple nodes are required for coperative communication, the low energy adaptive clustering hierarchy and LEACH-Vector Quantization are used for cluster and active cluster headformation. Further, Dijkstra Algorithm is used to find the shortest path between the active CHs and high-energy utilization, respectively. The main issue of inter-cluster communication is carried out in earlier work using LEACH and LEACH-V protocols. The chapter illustrates the LEACH-Vector Quantization Dijkstra protocol for shortest path active CH communication in a cooperative communication network. In the application point of view, LEACH-VD performs the lowest energy path. LEACH-V provides the intra-cluster communication between the cluster head, and using Dijkstra Algorithm, the minimum distance is calculated connecting the active cluster heads, which creates the shortest path results using an energy-efficient technique.

Balanced and Semi-Distributed Clustering Protocol for Wireless Sensor Networks

In Wireless Sensor Networks (WSNs), energy saving is one of the most essential issues in designing because of the significant restricted power resources of the Sensor Nodes (SNs). Moreover, these nodes are deployed in remote or hostile environments. Clustering techniques gained widespread acceptance due to its characteristic of less energy exhaustion. Intra-cluster communication cost (Intra-cluster term), Inter-cluster communication cost (Inter-cluster term), and Cluster Size (CS) have a great effect on balancing and conserving energy within each cluster in the network. In fact, topology control help in balancing the communication load and preserve the energy of the nodes by reducing both terms and determining the optimal CS. Hence, it would majorly influence improving the lifetime of the network. In order to achieve this, Balanced and Semi-Distributed Clustering Protocol (BSDCP) is proposed, which is suitable for long-scale transmission in WSNs. It uses topology control to manage the convergent sensors within the sensing area and control on CS. Thus, the Intra-cluster term is minimized. Moreover, instead of using Direct Transmission (DT) to send data of Cluster Head (CH) to Base Station (BS), BSDCP uses Multi-Hop (MH) communication between high residual energy Cluster Heads (CHs) and try to reach BS with minimum energy cost. Hence, the Inter-cluster term is reduced. In addition, the Dijkstra algorithm is employed as an effective tool to search for the least cost path efficiently. The simulation results show the significant improvement of our proposal compared to other clustering protocols, and it has a more extended network lifetime and stability period.