Comparison and Analysis on AI Based Data Aggregation Techniques in Wireless Networks

In modern era WSN, data aggregation technique is the challenging area for researchers from long time. Numbers of researchers have proposed neural network (NN) and fuzzy logic based data aggregation methods in Wireless Environment. The main objective of this paper is to analyse the existing work on artificial intelligence (AI) based data aggregation techniques in WSNs. An attempt has been made to identify the strength and weakness of AI based techniques.In addition to this, a modified protocol is designed and developed.And its implementation also compared with other existing approaches ACO and PSO. Proposed approach is better in terms of network lifetime and throughput of the networks. In future an attempt can be made to overcome the existing challenges during data aggregation in WSN using different AI and Meta heuristic based techniques

Hybrid Swarm Intelligence Energy Efficient Clustered Routing Algorithm for Wireless Sensor Networks

Currently, wireless sensor networks (WSNs) are used in many applications, namely, environment monitoring, disaster management, industrial automation, and medical electronics. Sensor nodes carry many limitations like low battery life, small memory space, and limited computing capability. To create a wireless sensor network more energy efficient, swarm intelligence technique has been applied to resolve many optimization issues in WSNs. In many existing clustering techniques an artificial bee colony (ABC) algorithm is utilized to collect information from the field periodically. Nevertheless, in the event based applications, an ant colony optimization (ACO) is a good solution to enhance the network lifespan. In this paper, we combine both algorithms (i.e., ABC and ACO) and propose a new hybrid ABCACO algorithm to solve a Nondeterministic Polynomial (NP) hard and finite problem of WSNs. ABCACO algorithm is divided into three main parts: (i) selection of optimal number of subregions and further subregion parts, (ii) cluster head selection using ABC algorithm, and (iii) efficient data transmission using ACO algorithm. We use a hierarchical clustering technique for data transmission; the data is transmitted from member nodes to the subcluster heads and then from subcluster heads to the elected cluster heads based on some threshold value. Cluster heads use an ACO algorithm to discover the best route for data transmission to the base station (BS). The proposed approach is very useful in designing the framework for forest fire detection and monitoring. The simulation results show that the ABCACO algorithm enhances the stability period by 60% and also improves the goodput by 31% against LEACH and WSNCABC, respectively

Enhanced ant colony system for reducing packet loss in wireless sensor network

Routing packets from source nodes to destination nodes in Wireless Sensor Network (WSN) is complicated due to the heterogeneous nature and distribution of sensor nodes. Packet loss problem in WSN may occur when the sensor node carrying more packets than its capacity. This can affect throughput, energy consumption and success rate of the WSN system. This paper proposes an improved Ant Colony Optimization (ACO) algorithm for packet routing to solve packet loss problem in wireless sensor network. The proposed algorithm is inspired from a variant of ACO which is Ant Colony System (ACS) that consists of local and global pheromone updates to enhance routing path exploration and exploitation. Experimental results showed that the proposed algorithm improved the performance of the proposed ACS algorithm in terms of reducing packet loss and increasing the energy efficiency of sensor nodes

Systems and algorithms for wireless sensor networks based on animal and natural behavior

In last decade, there have been many research works about wireless sensor networks (WSNs) focused on improving the network performance as well as increasing the energy efficiency and communications effectiveness. Many of these new mechanisms have been implemented using the behaviors of certain animals, such as ants, bees, or schools of fish.These systems are called bioinspired systems and are used to improve aspects such as handling large-scale networks, provide dynamic nature, and avoid resource constraints, heterogeneity, unattended operation, or robustness, amongmanyothers.Therefore, thispaper aims to studybioinspired mechanisms in the field ofWSN, providing the concepts of these behavior patterns in which these new approaches are based. The paper will explain existing bioinspired systems in WSNs and analyze their impact on WSNs and their evolution. In addition, we will conduct a comprehensive review of recently proposed bioinspired systems, protocols, and mechanisms. 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Ant colony optimization approaches in wireless sensor network: Performance evaluation

Wireless Sensor Network (WSN) has been widely implemented in large sectors such as military, habitat, business, industrial, health and environment. WSN is part of a distributed system where elements such as routing, load balancing, energy efficiency, node localization, time synchronization, data aggregation and security need to be addressed to improve its efficiency, robustness, extendibility, applicability and reliability. Despite multiple approaches proposed to improve all these aspects, there is still room for improvement in order to enhance the capability of WSN in terms of routing and energy efficiency. Ant Colony Optimization (ACO) is one of the approaches used to extend WSN capabilities because its heuristic nature is very suitable with distributed and dynamic environments. This study covers the common WSN aspects and performance evaluation criteria in addition to the list of previous studies that have used ACO approaches in WSN

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

Structure and topology of transcriptional regulatory networks and their applications in bio-inspired networking

Biological networks carry out vital functions necessary for sustenance despite environmental adversities. Transcriptional Regulatory Network (TRN) is one such biological network that is formed due to the interaction between proteins, called Transcription Factors (TFs), and segments of DNA, called genes. TRNs are known to exhibit functional robustness in the face of perturbation or mutation: a property that is proven to be a result of its underlying network topology. In this thesis, we first propose a three-tier topological characterization of TRN to analyze the interplay between the significant graph-theoretic properties of TRNs such as scale-free out-degree distribution, low graph density, small world property and the abundance of subgraphs called motifs. Specifically, we pinpoint the role of a certain three-node motif, called Feed Forward Loop (FFL) motif in topological robustness as well as information spread in TRNs. With the understanding of the TRN topology, we explore its potential use in design of fault-tolerant communication topologies. To this end, we first propose an edge rewiring mechanism that remedies the vulnerability of TRNs to the failure of well-connected nodes, called hubs, while preserving its other significant graph-theoretic properties. We apply the rewired TRN topologies in the design of wireless sensor networks that are less vulnerable to targeted node failure. Similarly, we apply the TRN topology to address the issues of robustness and energy-efficiency in the following networking paradigms: robust yet energy-efficient delay tolerant network for post disaster scenarios, energy-efficient data-collection framework for smart city applications and a data transfer framework deployed over a fog computing platform for collaborative sensing --Abstract, page iii