Analytical modeling of wireless communication systems
Wireless networks represent an inexpensive and convenient way to connect to the Internet. However, despite their applications across several technologies, one challenge still remains: to understand the behavior of wireless sensor networks and assess their performance in large-scale scenarios. When a...
| Otros Autores: | , , |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
London, England ; Hoboken, New Jersey :
ISTE
2016.
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| Edición: | 1st edition |
| Colección: | Stochastic Models in Computer Science and Telecommunication Networks Set ;
Number 1 |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009631526306719 |
Tabla de Contenidos:
- Cover; Title Page; Copyright; Contents; Preface; Introduction; List of Acronyms; PART 1: Sensor Networks; PART 2: Vehicular Networks; PART 3: Cellular Networks; Bibliography; Index; Other titles from ISTE in Networks and Telecommunications; EULA; 1: Fluid Models and Energy Issues; 2: Hybrid Automata for Transient Delay Analysis; 3: Safety Message Broadcasting; 4: Modeling Information Sharing; 5: Multi-RAT Algorithms; 1.1. The fluid-based approach; 1.2. Network scenario; 1.3. The sensor network model; 1.4. Results; 2.1. Event detection in WSNs; 2.2. Model for single-hop network topologies
- 2.3. Solution technique2.4. Model for multi-hop network topologies; 2.5. Model validation and exploitation results; 2.6. Discussion; 3.1. System description; 3.2. Dissemination of safety messages; 3.3. Assumptions and notations; 3.4. Model outline; 3.5. Computation of the block probability; 3.6. Computation of the probability of first reception; 3.7. Performance evaluation; 4.1. System scenario; 4.2. Modeling information exchange in IVN; 4.3. Computation of the probability of successful information retrieval; 4.4. Model validation and exploitation; 5.1. RAT network; 5.2. Network model
- 5.3. Model solution5.4. Performance evaluation; 1.1.1. Sensor density and traffic generation; 1.1.2. Data routing; 1.1.3. Local and relay traffic rates; 1.1.4. Channel contention and data transmission; 1.1.5. Mean packet delivery delay; 1.1.6. Sensor active/sleep behavior; 1.3.1. A minimum energy routing strategy: computing u(r'|r); 1.3.2. Channel contention and data transmission: computing s(r) and PR(r); 1.3.3. Mean packet delivery delay: computing q(r); 1.4.1. Model validation; 1.4.2. Model exploitation; 1.4.3. Model solution complexity and accuracy; 2.1.1. The 802.15.4 MAC protocol
- 2.2.1. Single message transfer2.2.2. Multiple message transfers; 2.3.1. Time discretization; 2.3.2. Transient solution; 2.3.3. Performance metrics computation; 3.2.1. The spatial differentiation approach; 3.2.2. The safety application; 3.6.1. A Gaussian approximation to the transient system behavior; 3.7.1. The impact of power capture; 3.7.2. The case of occupation probability ρ = 1; 3.7.3. The case of homogeneous occupation probability ρ < 1; 3.7.4. The case of inhomogeneous occupation probability; 3.7.5. The impact of the forwarding policy; 4.2.1. Model description; 5.1.1. Scenario
- 5.1.2. RAT selection strategy5.2.1. Functional rates; 5.3.1. Analytical approach; 5.3.2. Computation of performance metrics; 5.4.1. Setting and results; 1.3.1.1. Computing єm(r, r')|; 1.3.1.2. Computing FkmE(e|r); 1.3.1.3. Computation of the minimum energy path (equation [1.9]); 1.3.1.4. Computing FmE(e|r); 1.3.1.5. Computing ps; r(r'|e); 1.3.1.6. Computing u(r'|r); 1.3.2.1. Computation of the mean number of transmissions freezing the backoff counter; 1.3.3.1. Computing q(r) for always active sensors; 1.3.3.2. Computing q(r) for active and sleeping sensors; 5.1.1.1. Network scenario
- 5.2.1.1. Rates derivation
