SO-SNAP for Energy-Efficient Data Aggregation in Wireless Sensor Networks
Language: English
Published by Beakers Bay, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 37.18
Quantity: 2 available
Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - Wireless sensor networks (WSNs) have become an essential enabling technology for modern monitoring and data collection across environmental observation, industrial automation, smart agriculture, healthcare, infrastructure monitoring, and Internet of Things (IoT) applications. Because sensor nodes typically operate with limited processing capability, constrained memory, and finite battery power, energy-efficient communication and data aggregation remain fundamental challenges in extending network lifetime while maintaining reliable performance.SO-SNAP for Energy-Efficient Data Aggregation in Wireless Sensor Networks presents a focused exploration of energy-aware data aggregation strategies within wireless sensor networks, emphasizing the role of the SO-SNAP approach in improving communication efficiency and reducing unnecessary energy consumption. The book examines the principles of data collection, aggregation techniques, routing considerations, and network organization that influence the overall performance and longevity of distributed sensor systems.Beginning with the fundamentals of wireless sensor network architecture, the discussion introduces the characteristics of sensor nodes, wireless communication, topology design, clustering concepts, and energy consumption models. It then explores how efficient aggregation mechanisms help minimize redundant transmissions, optimize bandwidth utilization, reduce communication overhead, and improve overall network scalability.The book also considers the practical challenges associated with resource-constrained wireless sensor networks, including limited battery capacity, communication reliability, node deployment, scalability, and network lifetime. It discusses the importance of selecting appropriate aggregation methods that balance energy efficiency with data accuracy and communication performance while supporting distributed sensing environments.Readers are introduced to the broader context of energy-aware networking, where routing strategies, cluster organization, aggregation scheduling, and network management collectively contribute to efficient operation. The SO-SNAP methodology is presented within this context as a representative approach to improving data aggregation efficiency while addressing the operational constraints commonly encountered in wireless sensor networks.Throughout the text, technical concepts are explained using clear engineering terminology appropriate for students, researchers, and professionals working in wireless communication, embedded systems, sensor technologies, computer networks, and Internet of Things applications. The material provides readers with a structured understanding of how energy-efficient aggregation techniques contribute to sustainable network operation and improved resource utilization. …
Seller Inventory # 9798349529962
- Title
- SO-SNAP for Energy-Efficient Data Aggregation in Wireless Sensor Networks
- Author
- Cian John
- Publisher
- Beakers Bay
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 13
- 9798349529962
- Item weight
- 228 grams
- Dimensions
- 229x152x8 mm
Wireless sensor networks (WSNs) have become an essential enabling technology for modern monitoring and data collection across environmental observation, industrial automation, smart agriculture, healthcare, infrastructure monitoring, and Internet of Things (IoT) applications. Because sensor nodes typically operate with limited processing capability, constrained memory, and finite battery power, energy-efficient communication and data aggregation remain fundamental challenges in extending network lifetime while maintaining reliable performance.
SO-SNAP for Energy-Efficient Data Aggregation in Wireless Sensor Networks presents a focused exploration of energy-aware data aggregation strategies within wireless sensor networks, emphasizing the role of the SO-SNAP approach in improving communication efficiency and reducing unnecessary energy consumption. The book examines the principles of data collection, aggregation techniques, routing considerations, and network organization that influence the overall performance and longevity of distributed sensor systems.
Beginning with the fundamentals of wireless sensor network architecture, the discussion introduces the characteristics of sensor nodes, wireless communication, topology design, clustering concepts, and energy consumption models. It then explores how efficient aggregation mechanisms help minimize redundant transmissions, optimize bandwidth utilization, reduce communication overhead, and improve overall network scalability.
The book also considers the practical challenges associated with resource-constrained wireless sensor networks, including limited battery capacity, communication reliability, node deployment, scalability, and network lifetime. It discusses the importance of selecting appropriate aggregation methods that balance energy efficiency with data accuracy and communication performance while supporting distributed sensing environments.
Readers are introduced to the broader context of energy-aware networking, where routing strategies, cluster organization, aggregation scheduling, and network management collectively contribute to efficient operation. The SO-SNAP methodology is presented within this context as a representative approach to improving data aggregation efficiency while addressing the operational constraints commonly encountered in wireless sensor networks.
Throughout the text, technical concepts are explained using clear engineering terminology appropriate for students, researchers, and professionals working in wireless communication, embedded systems, sensor technologies, computer networks, and Internet of Things applications. The material provides readers with a structured understanding of how energy-efficient aggregation techniques contribute to sustainable network operation and improved resource utilization.
"Synopsis" may belong to another edition of this title.
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