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Dynamic wireless sensor networks / Sharief M.A. Oteafy, Hossam S. Hassanein.

By: Oteafy, Sharief M. A.
Contributor(s): Hassanein, Hossam S.
Material type: materialTypeLabelBookSeries: FOCUS Series: Publisher: Hoboken : Wiley, 2014Description: 1 online resource (145 pages).Content type: text Media type: computer Carrier type: online resourceISBN: 9781118761977; 1118761979; 9781118762042; 1118762045; 9781848215313; 1848215312; 9781322060620; 1322060622.Subject(s): Wireless sensor networks | Technology and engineering -- Sensors | Technology and engineering -- Telecommunications | Wireless communication systems | Wireless sensor networks | TECHNOLOGY & ENGINEERING -- Technical & Manufacturing Industries & Trades | Wireless sensor networksGenre/Form: Electronic books.Additional physical formats: Print version:: Dynamic Wireless Sensor Networks.DDC classification: 681.2 Online resources: Wiley Online Library
Contents:
Cover; Title Page; Copyright; Contents; Preface; List of Acronyms; List of Notations; Chapter 1: Evolution of Wireless Sensor Networks; 1.1. The progression of wireless sensor networks; 1.2. Remote sensing: in retrospect; 1.3. Inherited designs and protocols from MANets; 1.4. Book outline; 1.5. Summary; 1.6. Bibliography; Chapter 2: Shifting to Dynamic WSN Paradigms; 2.1. The hurdle of static operation; 2.2. Versatile operating systems; 2.3. Dynamic reprogramming; 2.4. The rise of service-oriented WSNs; 2.5. Crowd sensing; 2.6. Bibliography.
Chapter 3: Resilience and Post-Deployment Maintenance3.1. Impact of harsh environments on network design; 3.2. High failure proneness (of nodes and communication); 3.2.1. Detection; 3.2.2. Classification; 3.2.3. Location and zoning; 3.2.4. Isolation; 3.2.5. Maintenance; 3.3. Post-deployment maintenance; 3.4. Re-deployment; 3.5. Self-re-distributing SNs and mobility; 3.5.1. Sink mobility; 3.5.2. Node mobility; 3.6. Bibliography; Chapter 4: Current Hindrances in WSNs; 4.1. Lack of consensus; 4.2. Resource underutilization in the black-box paradigm; 4.3. Redundant deployments.
4.4. Single-application paradigm4.5. Redundancy to boost resilience; 4.6. IPv6 and enabling internet connectivity; 4.7. Bibliography; Chapter 5: Cloud-Centric WSNs; 5.1. Introduction; 5.2. The evolution of cloud-centric architectures; 5.2.1. The cloud variants; 5.2.2. LowPAN and stub nets; 5.3. SOA and SODA; 5.4. Hindrances in adopting cloud-centric WSNs; 5.4.1. Spatial limitations; 5.4.2. Temporal limitations; 5.4.3. Data representation SLAs; 5.4.4. Impact on resilience; 5.4.5. Energy efficiency at steak; 5.4.6. Functional decomposition discrepancies/redesign; 5.4.7. Breaching anonymity.
5.4.8. Traffic bottlenecks and query diffusion5.5. Future directions; 5.6. Bibliography; Chapter 6: The Resource-Reuse WSN Paradigm; 6.1. Contributions of the RR-WSN paradigm; 6.1.1. Revamping the view (of WSNs); 6.1.2. WSN resource reutilization; 6.1.3. Multi-application overlay; 6.1.4. Utilizing non-WSN abundant resources; 6.1.5. Enabling large-scale deployment; 6.1.6. Synergy for realizing the Internet of things; 6.2. RR-WSN: system model; 6.2.1. Network design; 6.2.2. Resource attributes; 6.2.2.1. Functional capability; 6.2.2.2. Levels of operation; 6.2.2.3. Power consumption.
6.2.2.4. Location6.2.2.5. Duty cycling; 6.2.2.6. Region of fidelity; 6.2.3. Representing applications; 6.3. Bibliography; Chapter 7: Component-Based WSNs: A Resilient Architecture; 7.1. Component-based DWSN architecture; 7.1.1. Network model; 7.1.2. Dynamic core nodes (DCN); 7.1.3. Wireless dynamic components (WDC); 7.1.4. Remote wake-up; 7.2. WDSN in operation: the synergy of dynamic sensing; 7.2.1. Operation of DWSN; 7.2.2. DCN in operation; 7.2.3. WDC in operation; 7.3. Resilience model; 7.4. Bibliography; Chapter 8: Dynamic WSNs -- Utilizing Ubiquitous Resources.
Summary: In this title, the authors leap into a novel paradigm of scalability and cost-effectiveness, on the basis of resource reuse. In a world with much abundance of wirelessly accessible devices, WSN deployments should capitalize on the resources already available in the region of deployment, and only augment it with the components required to meet new application requirements. However, if the required resources already exist in that region, WSN deployment converges to an assignment and scheduling scheme to accommodate for the new application given the existing resources.
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Print version record.

Cover; Title Page; Copyright; Contents; Preface; List of Acronyms; List of Notations; Chapter 1: Evolution of Wireless Sensor Networks; 1.1. The progression of wireless sensor networks; 1.2. Remote sensing: in retrospect; 1.3. Inherited designs and protocols from MANets; 1.4. Book outline; 1.5. Summary; 1.6. Bibliography; Chapter 2: Shifting to Dynamic WSN Paradigms; 2.1. The hurdle of static operation; 2.2. Versatile operating systems; 2.3. Dynamic reprogramming; 2.4. The rise of service-oriented WSNs; 2.5. Crowd sensing; 2.6. Bibliography.

Chapter 3: Resilience and Post-Deployment Maintenance3.1. Impact of harsh environments on network design; 3.2. High failure proneness (of nodes and communication); 3.2.1. Detection; 3.2.2. Classification; 3.2.3. Location and zoning; 3.2.4. Isolation; 3.2.5. Maintenance; 3.3. Post-deployment maintenance; 3.4. Re-deployment; 3.5. Self-re-distributing SNs and mobility; 3.5.1. Sink mobility; 3.5.2. Node mobility; 3.6. Bibliography; Chapter 4: Current Hindrances in WSNs; 4.1. Lack of consensus; 4.2. Resource underutilization in the black-box paradigm; 4.3. Redundant deployments.

4.4. Single-application paradigm4.5. Redundancy to boost resilience; 4.6. IPv6 and enabling internet connectivity; 4.7. Bibliography; Chapter 5: Cloud-Centric WSNs; 5.1. Introduction; 5.2. The evolution of cloud-centric architectures; 5.2.1. The cloud variants; 5.2.2. LowPAN and stub nets; 5.3. SOA and SODA; 5.4. Hindrances in adopting cloud-centric WSNs; 5.4.1. Spatial limitations; 5.4.2. Temporal limitations; 5.4.3. Data representation SLAs; 5.4.4. Impact on resilience; 5.4.5. Energy efficiency at steak; 5.4.6. Functional decomposition discrepancies/redesign; 5.4.7. Breaching anonymity.

5.4.8. Traffic bottlenecks and query diffusion5.5. Future directions; 5.6. Bibliography; Chapter 6: The Resource-Reuse WSN Paradigm; 6.1. Contributions of the RR-WSN paradigm; 6.1.1. Revamping the view (of WSNs); 6.1.2. WSN resource reutilization; 6.1.3. Multi-application overlay; 6.1.4. Utilizing non-WSN abundant resources; 6.1.5. Enabling large-scale deployment; 6.1.6. Synergy for realizing the Internet of things; 6.2. RR-WSN: system model; 6.2.1. Network design; 6.2.2. Resource attributes; 6.2.2.1. Functional capability; 6.2.2.2. Levels of operation; 6.2.2.3. Power consumption.

6.2.2.4. Location6.2.2.5. Duty cycling; 6.2.2.6. Region of fidelity; 6.2.3. Representing applications; 6.3. Bibliography; Chapter 7: Component-Based WSNs: A Resilient Architecture; 7.1. Component-based DWSN architecture; 7.1.1. Network model; 7.1.2. Dynamic core nodes (DCN); 7.1.3. Wireless dynamic components (WDC); 7.1.4. Remote wake-up; 7.2. WDSN in operation: the synergy of dynamic sensing; 7.2.1. Operation of DWSN; 7.2.2. DCN in operation; 7.2.3. WDC in operation; 7.3. Resilience model; 7.4. Bibliography; Chapter 8: Dynamic WSNs -- Utilizing Ubiquitous Resources.

8.1. System model and assumptions.

In this title, the authors leap into a novel paradigm of scalability and cost-effectiveness, on the basis of resource reuse. In a world with much abundance of wirelessly accessible devices, WSN deployments should capitalize on the resources already available in the region of deployment, and only augment it with the components required to meet new application requirements. However, if the required resources already exist in that region, WSN deployment converges to an assignment and scheduling scheme to accommodate for the new application given the existing resources.

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