A Novel Approach for Enhancing Routing in Wireless Sensor Networks using ACO Algorithm

Wireless Sensors Network (WSN) is an emergent technology that aims to offer innovative capacities. In the last decade, the use of these networks increased in various fields like military, science, and health due to their fast and inexpressive deployment and installation. However, the limited sensor battery lifetime poses many technical challenges and affects essential services like routing. This issue is a hot topic of search, many researchers have proposed various routing protocols aimed at reducing the energy consumption in WSNs. The focus of this work is to investigate the effectiveness of integrating ACO algorithm with routing protocols in WSNs. Moreover, it presents a novel approach inspired by ant colony optimization (ACO) to be deployed as a new routing protocol that addresses key challenges in wireless sensor networks. The proposed protocol can significantly minimize nodes energy consumption, enhance the network lifetime, reduce latency, and expect performance in various scenarios

Optimized Cluster-Based Dynamic Energy-Aware Routing Protocol for Wireless Sensor Networks in Agriculture Precision

[EN] Wireless sensor networks (WSNs) are becoming one of the demanding platforms, where sensor nodes are sensing and monitoring the physical or environmental conditions and transmit the data to the base station via multihop routing. Agriculture sector also adopted these networks to promote innovations for environmental friendly farming methods, lower the management cost, and achieve scientific cultivation. Due to limited capabilities, the sensor nodes have suffered with energy issues and complex routing processes and lead to data transmission failure and delay in the sensor-based agriculture fields. Due to these limitations, the sensor nodes near the base station are always relaying on it and cause extra burden on base station or going into useless state. To address these issues, this study proposes a Gateway Clustering Energy-Efficient Centroid- (GCEEC-) based routing protocol where cluster head is selected from the centroid position and gateway nodes are selected from each cluster. Gateway node reduces the data load from cluster head nodes and forwards the data towards the base station. Simulation has performed to evaluate the proposed protocol with state-of-the-art protocols. The experimental results indicated the better performance of proposed protocol and provide more feasible WSN-based monitoring for temperature, humidity, and illumination in agriculture sector.This work has also been partially supported by the European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) project ERANETMED3-227 SMARTWATIR.Qureshi, KN.; Bashir, MU.; Lloret, J.; León Fernández, A. (2020). Optimized Cluster-Based Dynamic Energy-Aware Routing Protocol for Wireless Sensor Networks in Agriculture Precision. Journal of Sensors. 2020:1-19. https://doi.org/10.1155/2020/9040395S1192020Sneha, K., Kamath, R., Balachandra, M., & Prabhu, S. (2019). New Gossiping Protocol for Routing Data in Sensor Networks for Precision Agriculture. 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Node Energy Based Approach to Improve Network Lifetime and Throughput in Wireless Sensor Networks

Energy consumption is the one of the most important issue in wireless sensor networks. To improve the network lifetime energy consumption in the network must be less. In this paper, a cluster based approach is proposed to increase the network lifetime and throughput of the heterogeneous wireless sensor networks. The proposed approach combined the direct data transmission to base station with the cluster head transmission of data in wireless sensor networks. The proposed scheme uses the twice energy for advanced nodes in comparison to normal nodes. In the proposed approach, it is observed that results are found good with the use of 10 % of advanced nodes along with normal nodes in the network. However, on further increasing the advanced node deployment beyond deployment 30%, network lifetime and throughput of network start degrading. So, the proposed solution with 10% advanced node may be considered as the best suitable and acceptable solution for better network throughput and life time in WSNs

Energy Consumption Minimization in WSN using BFO

The popularity of Wireless Sensor Networks (WSN) have increased rapidly and tremendously due to the vast potential of the sensor networks to connect the physical world with the virtual world. Since sensor devices rely on battery power and node energy and may be placed in hostile environments, so replacing them becomes a difficult task. Thus, improving the energy of these networks i.e. network lifetime becomes important. The thesis provides methods for clustering and cluster head selection to WSN to improve energy efficiency using fuzzy logic controller. It presents a comparison between the different methods on the basis of the network lifetime. It compares existing ABC optimization method with BFO algorithm for different size of networks and different scenario. It provides cluster head selection method with good performance and reduced computational complexity. In addition it also proposes BFO as an algorithm for clustering of WSN which would result in improved performance with faster convergence

K-means clustering-based WSN protocol for energy efficiency improvement

Since it is very difficult to replace or recharge the batteries of the sensor nodes in the wireless sensor network (WSN), efficient use of the batteries of the sensor nodes is a very important issue. This has a deep relationship with the lifetime of the network. If the node's energy is exhausted, the node is no longer available. If a certain number of nodes (50% or 80%) in a network consumes energy completely, the whole network will not work. Therefore, various protocols have been proposed to maintain the network for a long time by minimizing energy consumption. In recent years, a protocol using a K-means clustering algorithm, one of machine learning techniques, has been proposed. A KCED protocol is proposed in consideration of residual energy of a node, a cluster center, and a distance to a base station in order to improve a problem of a protocol using K-average gung zipper algorithm such as cluster center consideration

Reducing Power Consumption in Hexagonal Wireless Sensor Networks Using Efficient Routing Protocols

Power consumption and network lifetime are vital issues in wireless sensor network (WSN) design. This motivated us to find innovative mechanisms that help in reducing energy consumption and prolonging the lifetime of such networks. In this paper, we propose a hexagonal model for WSNs to reduce power consumption when sending data from sensor nodes to cluster heads or the sink. Four models are proposed for cluster head positioning and the results were compared with well-known models such as Power Efficient Gathering In Sensor Information Systems (PEGASIS) and Low-Energy Adaptive Clustering Hierarchy (LEACH). The results showed that the proposed models reduced WSN power consumption and network lifetime

ANT colony optimization based optimal path selection and data gathering in WSN

A data aggregation is an essential process in the field of wireless sensor network to deal with base station and sink node. In current data gathering mechanism, the nearest nodes to the sink receives data from all the other nodes and shares it to the sink. The data aggregation process is utilized to increase the capability and efficiency of the existing system. In existing technique, the possibility of data loss is high this may leads to energy loss therefore; the efficiency and performance are damaged. In order to overcome these issues, an effective cluster based data gathering technique is developed. Here the optimal cluster heads are selected which is used for transmission with low energy consumption. The optimal path for mobile sink (MS) is done by Ant Colony Optimization (ACO) algorithm. It provides efficient path along with MS to collect the data along with Cluster centroid. The performance of the proposed method is analyzed in terms of delay, throughput, lifetime, etc.</p

Residual Energy-Aware Clustering Transformation for LEACH Protocol, Journal of Telecommunications and Information Technology, 2021, nr 2

Energy is one of the crucial performance parameters in wireless sensor networks (WSNs). Enhancement of network lifetime is an important consideration as well. Low energy-aware clustering hierarchy (LEACH) is one of the protocols proposed for WSNs. In this paper, a residual energy-aware clustering transformation protocol for LEACH (REACT-LEACH), enhancing performance of LEACH by introducing a clustering mechanism, is proposed. The proposed cluster head (CH) rotation and cluster reformation processes are more effective in REACT-LEACH, as residual energy is considered to be one of the metrics. Performance of REACT-LEACH is validated based on simulation

Development of AODV based static multi-hop linear routing algorithm using 802.11 wireless sensor network for oil and gas pipeline

In recent years, the growing requirement for a static multi-hop wireless sensor network (WSN) has dominated remote supervision of the integrity of oil and gas pipelines. In the pipeline network, the sensing points are linked via wireless nodes connecting inspection points remotely to a centralised monitoring station. The introduction of the WSN to the pipeline network has critical factors leading to the deterioration of the overall network performance corresponding to the density of the network. In the selected application, the midstream of the oil and gas industry, the nodes must be arranged in a linear architecture to cover the length of the pipe. Such geographically diverse network configuration has a major effect on the disintegration of network stability, throughput unfairness, higher latency and energy usage from improper exploitation of network resources due to competitive data transmission, resulting in data snowballing effect on the destination node. Node starvation is also a factor that seriously affects the network performance of a large scale WSN multi- hop linear network. Unbalanced allocation of network resources between source nodes leads to the starvation of the node, which is a comparatively intensified factor overproduced data packets and source node distance from the destination node. Energy improvement in a static multi-hop linear topology is also linked to the lifetime of the network and is essential to the heterogeneous energy consumption nodes in the network. To decipher the mentioned problems, this thesis highlighted the challenges faced during the deployment of WSN in a large-scale network. The objective of this research is to develop a reliable AODV based multi-hop linear routing algorithm in accordance with IEEE 802.11 and to analyse the network performance implementing the proposed technique. This thesis highlighted two proposed routing algorithms namely Ad-hoc On-Demand Distance Vector Even, and Odd (AODVEO) and Ad-hoc On-Demand Distance Vector Triple Interleaving (AODVTRI) benched marked with commercial routing protocols Ad-hoc On-Demand Distance Vector (AODV) as well as Distance Sequence Distance Vector (DSDV). In AODVEO, the load of the traffic is reduced by splitting the traffic into two different routes (1) even-path and (2) odd-path with the consideration of x-axis. On the other hand, in AODVTRI, the traffic is divided into three different routes (1) alpha path, (2) beta path, and (3) charlie path with consideration of x-axis. Results showed that when the proposed technique is compared to the existing routing protocols in different simulation environments in conjunction with IEEE 802.11 standard, AODVEO showed improved network reliability (delivery ratio) as high as 19% and 15% in comparison to AODV and DSDV. In contrast, AODVTRI presented up to 26% and 22% of improvement when compared to AODV and DSDV, respectively. In terms of capacity (throughput) as well as energy, AODVEO showed up to 9 kbps more with 0.038J less energy consumption per packet and up to 13kbps more with 0.095J less energy consumption per packet when compared to AODV and DSDV. AODVTRI, on the other hand, showed up to 18 kbps more throughput with 0.082J less energy per packet when compared to AODV and up to 22kbps more with 0.140J less energy consumption per packet when compared to DSDV