Efficient & Reliable Algorithm for Route Selection in A Wireless Sensor Networks

The routing schemes in Wireless Sensor Network (WSN) systems are performed among the groups of different clusters. The node works for data aggregation from the source nodes and they also perform data dissemination and network management and events sensing and information collecting in the neighbourhood. Many clustering topologies have been proposed in recent years to localize the route within the cluster itself. In this work, it has been reviewed and compared these topologies to find out the network mechanism which is easier to manage and scalable for getting high quality response with respect to dynamics of the environment.

An Overview of Machine Learning-Based Energy-Efficient Routing Algorithms in Wireless Sensor Networks

Machine learning (ML) technology has shown its unique advantages in many fields and has excellent performance in many applications, such as image recognition, speech recognition, recommendation systems, and natural language processing. Recently, the applicability of ML in wireless sensor networks (WSNs) has attracted much attention. As resources are limited in WSNs, identifying how to improve resource utilization and achieve power-efficient load balancing is becoming a critical issue in WSNs. Traditional green routing algorithms aim to achieve this by reducing energy consumption and prolonging network lifetime through optimized routing schemes in WSNs. However, there are usually problems such as poor flexibility, a single consideration factor, and a reliance on accurate mathematical models. ML techniques can quickly adapt to environmental changes and integrate multiple factors for routing decisions, which provides new ideas for intelligent energy-efficient routing algorithms in WSNs. In this paper, we survey and propose a theoretical hypothetic model formulation of ML as an effective method for creating a power-efficient green routing model that can overcome the limitations of traditional green routing methods. In addition, the study also provides an overview of past, present, and future progress in green routing schemes in WSNs. The contents of this paper will appeal to a wide range of audiences interested in ML-based WSNs.

Energy-Efficient and Reliable Face-Routing Scheme in Wireless Networks

Face-routing is one of the reliable recovery schemes when geographic routing fails to transmit data packets. Although studies on face-routing can overcome the failure of the data transmission, they lead to much energy consumption due to frequent data transmissions between adjacent nodes for carrying out the rule of face-routing. To avoid the frequent data transmissions, several face-routing schemes have been recently proposed to transmit data packets to the farthest-neighbor node. However, they happen with many data retransmissions because the farthest-neighbor node has a relatively low transmission success ratio. To solve this problem, we propose a new face-routing scheme that determines the most appropriate neighbor node to balance the trade-off between energy efficiency and transmission reliability with two viewpoints. The first viewpoint focuses on how to increase the distance progress of the data delivery in one-hop range to enhance energy efficiency. After that, the second viewpoint focuses on how to increase the success ratio of the data delivery to enhance the transmission reliability. As a result of the simulation, it was confirmed that the proposed method achieves better performance in terms of energy efficiency than existing face-routing research, and it is better than recent face-routing research in terms of reliability and retransmission.

Energy-Efficient Hybrid Hierarchical Routing scheme for overall Efficiency in WSN

Wireless Sensor Network are spatially distributed sensors intended to monitor different physiological conditions. Sensing and communicating data from one place to another consumes more energy, therefore the management of sensor energy is a very important factor. Energy utilization, synchronization, and a lifetime of the network are the main criteria in WSN. More energy is utilized by sensors that are distant from the base station. The gateway nodes are deployed to collect and relay information from nodes to the base station to resolve this problem. To decrease energy consumption, gateway nodes are deployed in the network. In this paper, a hybrid approach is used to increase the overall efficiency of the network in WSNs with time synchronization which increases the throughput of the network. The efficiency of proposed protocol based network has shown improvements in network lifetime, residual energy, data packets, and the throughput of the network. The performance of WSN of the proposed scheme is compared to other classical routing schemes and the proposed algorithm has proved its merit.

Self-Pruning based Probabilistic Approach to Minimize Redundancy Overhead for Performance Improvement in MANET

The Broadcast storm problem causes severe interference, intense collision and channel contention, which greatly degrades the QoS performance metrics of the routing protocols. So, we suggest a neighbourhood coverage knowledge probabilistic broadcasting model (NCKPB) integrating with AODV protocol with knowledge on 2-hop neighbourhood coverage; a connectivity function to control a node’s forwarding probability of retransmission to alleviate significant overhead redundancy. Our objective is to minimize the broadcast RREQ overhead while ensuring fair retransmission bandwidth. We considered two more important measures called Saved Rebroadcast and Reachability. The outcomes of NCKPB, Fixed probability (FP) and Flooding (FL) routing schemes are examined under three major operating conditions, such as node density, mobility and traffic load. The NS-2 results demonstrate the efficacy of the proposed NCKPB model by illustrating its performance superiority over all key metrics such as redundancy overhead, end to end latency, throughput, reachability, saved rebroadcast and collision contrast to FP and FL.

Optical Packet and Burst-Switched Networks

In order to address poor bandwidth-utilization in circuit-switched WRONs, various techniques for optical packet-switching (OPS) have been explored, but needing complex technologies, such as real-time header extraction/insertion, packet alignment, etc. An intermediate solution between the WRONs and OPS networks – the optical burst-switched (OBS) network – has been explored, where several packets are clubbed together at ingress nodes to form optical bursts, which are transmitted with the headers sent as control packets ahead of each bursts. With this prior resource-reservation scheme at en-route nodes before burst arrivals, OBS networks overcome the challenges of OPS networks, while improving bandwidth utilization as compared to WRONs. We first present the node architectures, followed by header-processing schemes and switch designs for OPS networks. Next we present the basic concepts of OBS networking and describe the necessary network protocols, including burst assembly scheme, just enough time (JET) signaling, resource-reservation and routing schemes. (145 words)

A Connectivity-Based Clustering Scheme for Intelligent Vehicles

The reliability, scalability, and stability of routing schemes are open challenges in highly evolving vehicular ad hoc networks (VANETs). Cluster-based routing is an efficient solution to cope with the dynamic and inconsistent structure of VANETs. In this paper, we propose a cluster-based routing scheme (hereinafter referred to as connectivity-based clustering), where link connectivity is used as a metric for cluster formation and cluster head (CH) selection. Link connectivity is a function of vehicle density and transmission range in the proposed connectivity-based clustering scheme. Moreover, we used a heuristic approach of spectral clustering for the optimal number of cluster formation. Lastly, an appropriate vehicle is selected as a CH based on the maximum Eigen-centrality score. The simulation results show that the suggested connectivity-based clustering scheme performs well in the optimal number of cluster selections, strongly connected (STC) route selection, and route request messages (RRMs) in the discovery of a particular path to the destination. Thus, we conclude that link connectivity and the heuristic approach of spectral clustering are valuable additions to existing routing schemes for high evolving networks.

Energy-efficient routing in the proximity of a complicated hole in wireless sensor networks

A quest for geographic routing schemes of wireless sensor networks when sensor nodes are deployed in areas with obstacles has resulted in numerous ingenious proposals and techniques. However, there is a lack of solutions for complicated cases wherein the source or the sink nodes are located close to a specific hole, especially in cavern-like regions of large complex-shaped holes. In this paper, we propose a geographic routing scheme to deal with the existence of complicated-shape holes in an effective manner. Our proposed routing scheme achieves routes around holes with the (1+$$\epsilon$$ ϵ )-stretch. Experimental results show that our routing scheme yields the highest load balancing and the most extended network lifetime compared to other well-known routing algorithms as well.