Wireless Sensor Networks (WSNs) are highly integrated technologies applying sensors, microcontrollers and wireless networks technologies. Wireless sensor networks (WSNs) is a promising technology that has a large spectrum of applications such as, battlefield reconnaissance, border protection and security surveillance, preparing forecasts, severe environment detection, volcano monitoring, disaster management. WSNs operate unattended in harsh environments with limited energy supplies that can’t be practically changed or recharged. Thus energy efficiency is a critical design issue which must be addressed.
Clustering plays an effective role in judicious use of dwindling energy resources of the deployed sensor nodes. Nodes are grouped into clusters and a specific designated node, called the cluster head is responsible for collecting data from the nodes in its cluster, aggregating them and sending to the BS, where data can be retrieved later. Besides energy efficiency, clustering has many other advantages like reduced routing overhead, conservation of communication bandwidth, stabilized network topology, network stability etc
In this research, we study the energy efficiency of two clustering algorithms, S-Web and LEACH and compare them for network lifetime. Simulation results show that the S-Web clustering mechanism achieves a noticeable improvement in the network lifetime.
Contents
Abstract
Acknowledgement
Glossary
CHAPTER 1 INTRODUCTION
CHAPTER 2 LITERATURE SURVEY
2.1 Clustering ad hoc networks
2.2 Advantages of Clustering
2.3 Challenges for Clustering Algorithms
- Limited Energy:
- Constrained resources:
- Secure Communication:
- Cluster formation and CH selection:
- Load balancing:
- Minimal cluster count:
- Synchronization:
- Data Aggregation:
- Fault-tolerance:
- Quality of Service (QoS):
2.4 Clustering Schemes for Sensor Networks
2.4.1 Optimizing Cluster Organization
2.4.2 Averaging Power Consumption
2.4.3 Scheduling Active and Non-Active Nodes
2.5 Clustering Algorithms
2.5.1 Low-Energy Adaptive Clustering Hierarchy (LEACH):
2.5.2 Sensor Web or S-WEB:
2.5.3 Energy Efficient Clustering Scheme (EECS):
2.5.4 Hybrid Energy Efficient Distributed Clustering (HEED):
2.5.5 Energy-efficient unequal clustering (EEUC):
2.5.6 Power-efficient and adaptive clustering hierarchy (PEACH):
CHAPTER 3 Problem Definition and Implementation
3.1 Problem Definition
3.2 Implementation
CHAPTER 4 Results
4.1 First scenario (Normal Node to Normal Node)
4.2 Second scenario (Normal Node to Cluster Head)
4.3 Third scenario (Cluster Head to Normal Node)
4.4 Fourth scenario (Cluster Head to Cluster Head)
4.5 Fifth scenario (Random)
CHAPTER 5 Conclusion and Future Work
References
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