Performance Analysis of Multi-Hop Routing Protocol With Optimized Grid-Based Clustering for Wireless Sensor Network

Wireless sensor networks (WSNs) consist of several sensor nodes (SNs) that are powered by battery, so their lifetime is limited, which ultimately affects the lifespan and hence performance of the overall networks. Till now many techniques have been developed to solve this problem of WSN. Clustering is among the effective technique used for increasing the network lifespan. In this chapter, analysis of multi-hop routing protocol based on grid clustering with different selection criteria is presented. For analysis, the network is divided into equal-sized grids where each grid corresponds to a cluster and is assigned with a grid head (GH) responsible for collecting data from each SN belonging to respective grid and transferring it to the base station (BS) using multi-hop routing. The performance of the network has been analyzed for different position of BS, different number of grids, and different number of SNs.

The Efficient Managemnet of Renewable Energy Resources for Vanet-Cloud Communication

Vehicular ad hoc networks (VANET) are networks that interconnect road and vehicles. The mobile nodes are used to connect themselves in self-organized manner. VANET is valuable that gives better performance and assures safe transportation system in prospect. Few of them are covered that helps in knowing the best protocol to be used in particular work. Initially, renewable energy is considered to be those sources that are derived either directly or indirectly from solar energy. Due to emission of harmful gases, in VANET, use of renewable resources come in existence. In another section of the chapter, various energy issues in VANET have been highlighted and added the concept of VANET-CLOUD. As cloud computing technologies have potential to improve the travelling experience and safety of roads by giving provision of various solutions like traffic lights synchronization, alternative routes, etc., VANET-CLOUD has been added at the end of the chapter.

Salp

The formation of the unequal clusters of the sensor nodes is a burning research issue in wireless sensor networks (WSN). Energy-hole and non-uniform load assignment are two major issues in most of the existing node clustering schemes. This affects the network lifetime of WSN. Salp optimization-based algorithm is used to solve these problems. The proposed algorithm is used for cluster head selection. The performance of the proposed scheme is compared with the two-node clustering scheme in the term of residual energy, energy consumption, and network lifetime. The results show the proposed scheme outperforms the existing protocols in term of network lifetime under different network configurations.

Energy-Efficient Routing for WSNs

A wireless sensor network (WSN) is a gathering of sensor hubs that powerfully self-sort themselves into a wireless system without the use of any previous framework. One of the serious issues in WSNs is the energy consumption, whereby the system lifetime is subject to this factor. Energy-efficient routing is viewed as the most testing errand. Sensor organizes for the most part work in perplexing and dynamic situations and directing winds up repetitive assignment to keep up as the system measure increments. This chapter portrays the structure of wireless sensor network the analysis and study of different research works identified with energy-efficient routing in wireless sensor networks. Along these lines, to beat all the routing issues, the pattern has moved to biological-based algorithms like swarm intelligence-based strategies. Ant colony optimization-based routing protocols have shown outstanding outcomes as far as execution when connected to WSN routing.

A Study on Energy-Efficient Wireless Sensor Network Protocols

Many original ideologies are being applied as solutions to the problems of wireless sensor networks with the rigorous experimentation and advancement in technology and research. This chapter reviews various energy-efficient routing algorithms, classifying them based on methodology applied. The classification is based on design approach used to solve the basic problem arising in construction of transmission path between source and base station (BS) with minimum energy consumption. The pros and cons of routing algorithms for WSN are analyzed. The parameters to be considered in evaluation of all routing protocols are summarized.

Optimization of Energy Efficiency in Wireless Sensor Networks and Internet of Things

Energy consumption is a constraint in the design architecture of wireless sensor networks (WSNs) and internet of things (IoT). In order to overcome this constraint, many techniques have been proposed to enhance energy efficiency in WSNs. In existing works, several innovative techniques for the physical, the link, and the network layer of OSI model are implemented. Energy consumption in the WSNs is to find the best compromise of energy consumption between the various tasks performed by the objects, the detection, the processing, and the data communication tasks. It is this last task that consumes more energy. As a result, the main objective for the WSNs and the IoT is to minimize the energy consumed during this task. One of the most used solutions is to propose efficient routing techniques in terms of energy consumption. In this chapter, the authors present a review of related works on energy efficiency in WSNs and IoT. The network layer routing protocols are the main concerns in this chapter. The interest is focused on the issue of designing data routing techniques in WSNs and IoT.

Nature-Inspired-Based PTS for PAPR Reduction in OFDM Systems

OFDM is widely used in high data rate applications due to its ability to mitigate frequency selectivity. However, OFDM suffers from high PAPR problem. This degrades the system performance. PTS is a promising PAPR reduction technique. However, its computational complexity is large; to reduce it, different suboptimal solution (heuristics) were presented in literature. Heuristics PTS algorithms can be categorized into descent-heuristics and metaheuristics. In this chapter, descent-heuristics-based PTS and metaheuristics-based PTS are compared. Results showed that RS-PTS is the best one among descent-heuristics algorithms. Metaheuristics algorithms can also be classified into single solution-based methods and nature-inspired methods. Among metaheuristics algorithms, two natural inspired algorithms and one single solution-based methods, namely PSO, ABC, and SA, were selected to be compared with descent-heuristics algorithms. Results showed that PTS based on nature-inspired methods is better than PTS based on descent heuristics and PTS based on single-solution metaheuristics method.

Two-Sided Assembly Line Balancing Optimization With Spider Monkey Optimization

Growing interests from customers in customized products and increasing competition among peers necessitate companies to configure and balance their manufacturing systems more effectively than ever before. Two-sided assembly lines are usually constructed to produce large-sized high-volume products such as buses, trucks, automobiles, and some domestic products. Since the problem is well known as NP-hard problem, a mathematical model is solved by an exact solution-based approach and spider monkey optimization (SMO) algorithm that is inspired by the intelligent foraging behavior of fission-fusion social structure-based animals. In this chapter, the proposed mathematical model is applied to solve benchmark problems of two-sided assembly line balancing problem to minimize the number of mated stations and idle time. The experimental results show that spider monkey optimizations provide better results.

Impact of Nature-Inspired Algorithms on Localization Algorithms in Wireless Sensor Networks

In wireless sensor networks, localization is one of the essential requirements. Most applications are of no use, if location information is not available. Based on cost, localization algorithms can be divided into two categories, namely range-based and range-free. Range-free are cost-effective, but they lack accuracy. In this chapter, the role of nature-inspired algorithms in enhancing the accuracy of range-free algorithms has been investigated. Inferences drawn from exhaustive literature survey of recent research in this area establishes the importance of these algorithms in sensor localization.