Energy-Efficient Clustering and Coordinated Communication in Wireless Sensor Networks using Modified LEACH Algorithm

Problem Definition

Wireless sensor networks play a crucial role in collecting and transmitting data from sensor nodes to a mobile sink. Despite the numerous studies conducted to improve routing criteria, there are still limitations and challenges that exist within this domain. One commonly employed approach divides the process into three phases, focusing on factors such as distance, residual energy parameters, and utilization of chains for data transmission. However, a significant limitation of this approach is the unequal distribution of nodes within the region, which can impact the efficiency and effectiveness of data transmission. Additionally, the criteria for selecting cluster heads (CH) are limited to only distance and residual energy parameters, overlooking other potential factors that could optimize routing strategies.

Addressing these limitations and problems within wireless sensor networks is essential for enhancing the overall performance and reliability of data transmission in this domain.

Objective

The objective of the proposed work is to develop an energy-efficient routing protocol for wireless sensor networks. This protocol will focus on selecting cluster heads based on multiple factors such as residual energy, distance between nodes, and uniform distribution of sensor nodes within clusters. By reducing energy consumption and introducing coordinated nodes in each cluster, the protocol aims to improve the overall efficiency and effectiveness of routing in wireless sensor networks. The goal is to optimize energy consumption, enhance data transmission reliability, and address current limitations in existing routing approaches through a comprehensive and balanced routing process.

Proposed Work

In order to address the limitations identified in the existing literature on wireless sensor networks routing, the proposed work aims to develop an energy-efficient routing protocol. This protocol will consider multiple factors for cluster head (CH) selection and ensure uniform distribution of sensor nodes within clusters. By incorporating residual energy, distance between nodes, and the presence of remaining nodes in the selection process, the protocol will aim to reduce energy consumption within the network. Moreover, the proposed method will introduce coordinated nodes in each cluster to eliminate the energy-intensive chain-based communication system. Through this approach, the project seeks to enhance the overall efficiency and effectiveness of routing in wireless sensor networks.

The rationale behind the proposed approach lies in the need to optimize energy consumption and improve the reliability of data transmission in wireless sensor networks. By focusing on factors such as residual energy, distance, and cluster distribution, the protocol aims to achieve a more balanced and energy-efficient routing process. The decision to incorporate coordinated nodes within clusters is based on the desire to eliminate the limitations associated with chain-based communication and enhance the overall performance of the network. By comparing the results of the proposed model with existing work in terms of metrics such as dead nodes, alive nodes, and energy consumption, the project aims to demonstrate the effectiveness of the proposed routing protocol in addressing the identified research gap.

Application Area for Industry

The proposed solutions in this project can be applied in various industrial sectors such as manufacturing, agriculture, and environmental monitoring. In manufacturing, the implementation of wireless sensor networks with evenly distributed nodes and optimized cluster head selection can improve the efficiency of monitoring processes and reduce energy consumption. In agriculture, these solutions can help in remote monitoring of crops and soil conditions, leading to better resource management and increased productivity. In environmental monitoring, the use of coordinated nodes in clusters can enhance data collection and analysis, aiding in early detection of environmental threats and facilitating timely responses. The challenges that industries face, such as uneven distribution of sensor nodes, inefficient energy utilization, and complex communication systems, can be addressed by the proposed solutions.

By ensuring uniform distribution of nodes, optimizing cluster head selection based on multiple parameters, and eliminating chain-based communication systems, industries can benefit from improved network performance, increased reliability, and reduced energy consumption. Ultimately, implementing these solutions can lead to better decision-making, enhanced operational efficiency, and cost savings for industries across various sectors.

Application Area for Academics

The proposed project can significantly enrich academic research, education, and training by introducing a novel method for improving the efficiency of wireless sensor networks (WSN) in transmitting data to mobile sinks. This project can serve as a valuable resource for researchers, MTech students, and PHD scholars in the field of WSN and related domains. One of the key strengths of this project is its relevance in pursuing innovative research methods, simulations, and data analysis within educational settings. By introducing a new approach to selecting cluster heads based on factors such as residual energy, distance between nodes, and remaining nodes, the project offers a fresh perspective on optimizing routing criteria and energy efficiency in WSN. The use of the Modified LEACH algorithm in this project opens up opportunities for further exploration and experimentation in the field of WSN.

Researchers and students can leverage the code and literature of this project to conduct comparative studies, analyze the impact of different parameters on network performance, and explore potential extensions or modifications to the proposed method. Additionally, the project's emphasis on energy conservation through the introduction of coordinated nodes in each cluster offers valuable insights for designing more sustainable and efficient WSN solutions. By comparing the results of this model with existing work in terms of dead nodes, alive nodes, and energy consumption, researchers can gain valuable insights into the effectiveness of the proposed method. In conclusion, the proposed project holds great potential for advancing research in the domain of wireless sensor networks and related areas. It can serve as a valuable resource for academia, providing a platform for experimentation, analysis, and innovation in WSN technology.

The future scope of this project may involve further optimization of the proposed method, exploring its scalability to larger networks, and investigating its applicability in real-world scenarios.

Algorithms Used

The Modified LEACH algorithm is used in this project to efficiently manage the energy consumption in wireless sensor networks (WSN). The algorithm assigns cluster heads based on factors such as residual energy, distance between nodes, and remaining nodes in the network. Additionally, a coordinated node is introduced in each cluster to optimize communication and reduce energy consumption. By implementing this algorithm, the project aims to improve the network's overall performance by increasing the number of alive nodes, reducing the number of dead nodes, and enhancing energy efficiency. The results of the modified LEACH algorithm are compared with existing methods to demonstrate its effectiveness in achieving the project's objectives.

Keywords

wireless sensor networks, load balancing, cluster head selection, coordination nodes, network optimization, energy efficiency, data aggregation, routing protocols, clustering algorithms, network performance, distributed systems, resource allocation, quality of service, network scalability, sensor node coordination, routing criteria, mobile sink, sensor nodes, residual energy, novel method, dead nodes, alive nodes, energy consumption, transmission routes, efficient approach, chain based system, uniform distribution, cluster formation, route optimization, sensor node placement, communication efficiency

SEO Tags

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