Energy-Efficient Clustering of UAVs with Crow Search Interaction

Kumar, Kundan; Goswami, Meghna; Arya, Rajeev

doi:10.2139/ssrn.3658897

Cited by 3 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The proposed investigation employs the same energy modeling approach as the one mentioned. An l-bit data packet's transmission effort, as performed by each node, may be written as: 𝐸 𝑇𝑋 𝑛 (𝑙, 𝑑) = { 𝑙𝐸 𝑒𝑙𝑒𝑐 + 𝑙𝜖 𝑓𝑠 𝑑 2 , 𝑑 ≤ 𝑑 𝑡ℎ 𝑙𝐸 𝑒𝑙𝑒𝑐 + 𝑙𝜖 𝑚𝑝 𝑑 4 , 𝑑 > 𝑑 𝑡ℎ (5) Thus, Eelec characterizes the power used during a single bit's transmission or reception, 𝜖𝑓𝑠 & mp represents the power used in multi-path and free space environments, & d represents E.d. among the CM also its allocated receiver.…”

Section: ) Energy Consumption Modelmentioning

confidence: 99%

See 1 more Smart Citation

A Hybrid MFCM-PSO Approach for Tree-Based Multi-Hop Routing Using Modified Fuzzy C-Means in Wireless Sensor Network

Sikarwar,

Tomar

2023

IEEE Access

View full text Add to dashboard Cite

A wireless sensor network (WSN) collects data from various monitoring systems using small sensor nodes (SNs). The WSN analyses and sends found data to the BS. SNs have a short lifespan, therefore the sensor network must gather and transmit data efficiently. Energy efficiency is the main difficulty in sensor network organisation. Sensor nodes require energy efficiency due to their high cost and limited capacity. This limitation significantly compromises the longevity of the network. The anticipated demands on a node's battery determine its lifespan. Sensor networks must be resilient to sensor node lifetime reduction. Energyefficient routing algorithms may increase the lifetime of multihop networks by selecting the most energyefficient approach. Unfortunately, the present technique has performance issues. Modified Fuzzy C-Means with Particle Swarm Optimization (MFCM-PSO) is a novel hybrid clustering method that combines fuzzy cmeans with PSO to address the shortcomings of existing methods that use FCM to determine cluster centres and then optimise them using PSO. The PSO helps choose optimum no. of clusters and CHs (Cluster Heads). This method uses 100 and 200 sensor nodes. We devised a hierarchical packet routing technique by introducing the concepts of Direct Cluster Head (DCH) and PCH (Parent Cluster Head), that are chosen based on distinct FF (Fitness Functions) and act as relays for a limited number of other CHs, saving network energy. The simulation results represents that the proposed MFCM-PSO method superior performance base EEHCHR on scenario-1, with 28% for FND (First Node Dead), 23% for HND (Half Node Dead), and 19% for LND (Last Node Dead), and on scenario-2, 8% for FND, 23% for HND, and assumed 36% for LND since no node dies up to 1500 rounds. Thus, the simulation results suggest that the MFCM-PSO method improves coverage, network energy, and lifetime efficiency over the EEHCHR method.

show abstract

Section: ) Energy Consumption Modelmentioning

confidence: 99%

“…The CH is the BS to which all sensor nodes in a particular cluster report through wireless connections [4]. CHs are the nodes in a network that are in charge of sending data back to the BS [5]. Clustering is often characterized by the division of an area into smaller sub-areas and the designation of a BS (CH) for each sub-area.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid MFCM-PSO Approach for Tree-Based Multi-Hop Routing Using Modified Fuzzy C-Means in Wireless Sensor Network

Sikarwar,

Tomar

2023

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Each sensor node in the cluster is wirelessly connected to the Cluster Head (CH), which is in turn wirelessly connected to the Base Station (BS) through wireless inter-cluster communication and the CH as well as between the BS and the CH [5]. Each cluster contains CHs that collect data from other nodes in the cluster and transmit it to the base station directly or indirectly via other nodes [6].…”

Section: Introductionmentioning

confidence: 99%

A Systematic Review on the Energy Efficiency of Dynamic Clustering in a Heterogeneous Environment of Wireless Sensor Networks (WSNs)

2022

View full text Add to dashboard Cite

There are a variety of applications for wireless sensor networks (WSNs), such as military, health monitoring systems, natural disasters, smartphones, and other surveillance systems. While the primary purpose of sensor nodes is to collect unattended data in hostile environments, many are placed in large numbers and operate independently. Due to limited capabilities, power is often limited. Therefore, these nodes are grouped into clusters to increase communication efficiency. In WSNs, two different routing protocols are possible: apartment and hierarchical or clustering protocols. Due to their significant role in minimizing energy consumption, hierarchical methods have become very popular in clustering. In cluster-based methods, nodes are organized into clusters, and the sensor node with the most resources is appointed as the cluster head (CH). In this paper, we present a Systematic Literature Review (SLR) explaining the difficulties in developing cluster-based methods, critical factors for clustering, and hierarchical clustering protocols. The most important factor of a routing protocol for WSN is the energy consumption and lifetime of a network. Focusing on energy consumption, different cluster-based methods were analyzed to determine which technology should be deployed by analyzing specific criteria to support the selection process. Additionally, the pros and cons of different protocols are listed with their relevance in specific scenarios. To identify these protocols, a systematic literature review was conducted using research studies published from 2010 to 2021, with 30 papers analyzed in the final phase. Based on the results of this SLR, several issues need to be further investigated with respect to the interaction of the potential technology with the Internet of Things (IoT) and Vehicular Ad-Hoc Networks (VANETs).

show abstract

An enhanced AHP-TOPSIS-based clustering algorithm for high-quality live video streaming in flying ad hoc networks

2021

View full text Add to dashboard Cite

Energy-Efficient Clustering of UAVs with Crow Search Interaction

Cited by 3 publications

References 0 publications

A Hybrid MFCM-PSO Approach for Tree-Based Multi-Hop Routing Using Modified Fuzzy C-Means in Wireless Sensor Network

A Hybrid MFCM-PSO Approach for Tree-Based Multi-Hop Routing Using Modified Fuzzy C-Means in Wireless Sensor Network

A Systematic Review on the Energy Efficiency of Dynamic Clustering in a Heterogeneous Environment of Wireless Sensor Networks (WSNs)

An enhanced AHP-TOPSIS-based clustering algorithm for high-quality live video streaming in flying ad hoc networks

Contact Info

Product

Resources

About