FPOA Implementation for WSN Energy Efficient Routing

In this paper,a soft computing technique Flower Pollination optimization Algorithm(FPOA) for WSN is proposed.The Sensor Network is heterogeneous in nature. Proposed algorithm is designed and implemented in MATLAB.In this technique some nodes send data directly to base station as local pollination and some by Multihop Routing as global pollination. A routing scheme is process which helps in minimizing the energy consumption. We implemented FPOA and compared the results with techniques that are already developed.(Low Energy adaptive clustering hierarchy (LEACH), Stable Election Protocol (SEP) and Zonal-Stable Election Protocol (Z-SEP) Simulation results show that FPOA enhance first node dead time, throughput and overall energy consumes less than existing protocols like LEACH, SEP and Z-SE

A Survey on Energy-Efficient Strategies in Static Wireless Sensor Networks

A comprehensive analysis on the energy-efficient strategy in static Wireless Sensor Networks (WSNs) that are not equipped with any energy harvesting modules is conducted in this article. First, a novel generic mathematical definition of Energy Efficiency (EE) is proposed, which takes the acquisition rate of valid data, the total energy consumption, and the network lifetime of WSNs into consideration simultaneously. To the best of our knowledge, this is the first time that the EE of WSNs is mathematically defined. The energy consumption characteristics of each individual sensor node and the whole network are expounded at length. Accordingly, the concepts concerning EE, namely the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective, are proposed. Subsequently, the relevant energy-efficient strategies proposed from 2002 to 2019 are tracked and reviewed. Specifically, they respectively are classified into five categories: the Energy-Efficient Media Access Control protocol, the Mobile Node Assistance Scheme, the Energy-Efficient Clustering Scheme, the Energy-Efficient Routing Scheme, and the Compressive Sensing--based Scheme. A detailed elaboration on both of the basic principle and the evolution of them is made. Finally, further analysis on the categories is made and the related conclusion is drawn. To be specific, the interdependence among them, the relationships between each of them, and the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective are analyzed in detail. In addition, the specific applicable scenarios for each of them and the relevant statistical analysis are detailed. The proportion and the number of citations for each category are illustrated by the statistical chart. In addition, the existing opportunities and challenges facing WSNs in the context of the new computing paradigm and the feasible direction concerning EE in the future are pointed out

Novel Clustering Techniques in Wireless Sensor Networks – A Survey

A study of Wireless Sensor Networks has been growing tremendously these days. Wireless Sensor Networks play a major role in various fields ranging from smart homes to health care. WSN’s operate independently in remote places. Because of tiny size of the nodes in such type of networks, they have a limited number of resources in terms of energy and power. Basically, sensor networks can be classified into flat and cluster based Wireless Sensor Networks. But, Clustering based Sensor Networks play a major role in reducing the energy consumption in Wireless Sensor Networks. Clustering also focuses on solving the No.s that arise during transmission of data. Clustering will group nodes into clusters and elects Cluster Heads for all clusters in the network. Then the nodes sense data and send that data to cluster head where the aggregation of data will take place. This paper focuses on various novel clustering techniques that improve the network’s lifetime

Survey on Various Aspects of Clustering in Wireless Sensor Networks Employing Classical, Optimization, and Machine Learning Techniques

A wide range of academic scholars, engineers, scientific and technology communities are interested in energy utilization of Wireless Sensor Networks (WSNs). Their extensive research is going on in areas like scalability, coverage, energy efficiency, data communication, connection, load balancing, security, reliability and network lifespan. Individual researchers are searching for affordable methods to enhance the solutions to existing problems that show unique techniques, protocols, concepts, and algorithms in the wanted domain. Review studies typically offer complete, simple access or a solution to these problems. Taking into account this motivating factor and the effect of clustering on the decline of energy, this article focuses on clustering techniques using various wireless sensor networks aspects. The important contribution of this paper is to give a succinct overview of clustering

Distributed Clustering Based on Node Density and Distance in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are special type of network with sensing and monitoring the physical parameters with the property of autonomous in nature. To implement this autonomy and network management the common method used is hierarchical clustering. Hierarchical clustering helps for ease access to data collection and forwarding the same to the base station. The proposed Distributed Self-organizing Load Balancing Clustering Algorithm (DSLBCA) for WSNs designed considering the parameters of neighbor distance, residual energy, and node density.  The validity of the DSLBCA has been shown by comparing the network lifetime and energy dissipation with Low Energy Adaptive Clustering Hierarchy (LEACH), and Hybrid Energy Efficient Distributed Clustering (HEED). The proposed algorithm shows improved result in enhancing the life time of the network in both stationary and mobile environment

Cluster-based Routing Protocols for Energy-Efficiency in Wireless Sensor Networks

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Clustering objectives in wireless sensor networks: A survey and research direction analysis

Wireless Sensor Networks (WSNs) typically include thousands of resource-constrained sensors to monitor their surroundings, collect data, and transfer it to remote servers for further processing. Although WSNs are considered highly flexible ad-hoc networks, network management has been a fundamental challenge in these types of net- works given the deployment size and the associated quality concerns such as resource management, scalability, and reliability. Topology management is considered a viable technique to address these concerns. Clustering is the most well-known topology management method in WSNs, grouping nodes to manage them and/or executing various tasks in a distributed manner, such as resource management. Although clustering techniques are mainly known to improve energy consumption, there are various quality-driven objectives that can be realized through clustering. In this paper, we review comprehensively existing WSN clustering techniques, their objectives and the network properties supported by those techniques. After refining more than 500 clustering techniques, we extract about 215 of them as the most important ones, which we further review, catergorize and classify based on clustering objectives and also the network properties such as mobility and heterogeneity. In addition, statistics are provided based on the chosen metrics, providing highly useful insights into the design of clustering techniques in WSNs.publishedVersio

A Survey: Hierarchal Routing Protocol in Wireless Sensor Networks

The wireless sensor networks (WSNs) has been grown immensely in the past few decades. Researcher had proposed a number of routing protocols for WSN. WSN has two type of architecture layered and cluster architecture. We classify various clustering approaches based on different criterion in section [3]. Hierarchical Clustering protocols discussed in section [4] have extensively been used to achieve network scalability, energy efficiency and network lifetime. In this paper we discuss the challenges in design of WSN, advantages and objectives of clustering, various clustering approaches. We present a detailed survey on proposed clustering routing protocol in WSN literature

Overlapping layers for prolonging network life time in multi-hop wireless sensor networks

Wireless sensor networks have been proposed as a practical solution for a wide range of applications due to their benefits of low cost, rapid deployment, self-organization capability, and cooperative data-processing. Many applications, such as military surveillance and habitat monitoring, require the deployment of large-scale sensor networks. A highly scalable and fault-tolerant network architecture, the Progressive Multi-hop Rotational Clustered (PMRC) structure has been proposed, which is suitable for constructing large-scale wireless sensor networks. However, similar to other multi-hop structures, the PMRC structure also suffers from the bottleneck problem; This thesis is focused on solving the bottleneck problem existing in the PMRC structure. First, the Overlapping Neighbor Layers (ONL) scheme is proposed to balance the energy consumption among cluster heads at different layers. Further, the Minimum Overlapping Neighbor Layers (MONL) scheme is proposed wherein the overlapped area between neighbor layers is gradually increased through network life time to achieve load balance and energy efficiency in the whole network area. Simulation results show that the MONL scheme significantly prolongs network life time and demonstrates steady performance on sensor networks with uniformly distributed sensor nodes. To further prolong the network life time, traffic-similar sensor nodes distribution combined with the MONL scheme is studied; The proposed overlapped layers schemes are proven to be effective in solving the bottleneck problem and prolonging network life time for PMRC-based networks. They can also be applied for other multi-hop cluster-based sensor networks. The traffic-similar nodes distribution concept can be applied in optimizing sensor network deployment to achieve desired network life time