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Stochastic Petri Nets for Wireless Networks electronic resource by Lei Lei, Chuang Lin, Zhangdui Zhong.

By: Lei, Lei [author.]Contributor(s): Lin, Chuang [author.] | Zhong, Zhangdui [author.] | SpringerLink (Online service)Material type: TextTextSeries: SpringerBriefs in Electrical and Computer EngineeringPublication details: Cham : Springer International Publishing : Imprint: Springer, 2015Description: XIV, 101 p. 26 illus. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783319168838Subject(s): Computer Science | Computer communication systems | computers | electrical engineering | Computer Science | Computer Communication Networks | Communications Engineering, Networks | Information Systems and Communication ServiceDDC classification: 004.6 LOC classification: TK5105.5-5105.9Online resources: Click here to access online
Contents:
Introduction -- Stochastic Petri Nets -- Performance Analysis of Opportunistic Schedulers using SPNs -- Performance Analysis of Device-to-Device Communications with Dynamics Interference using SPNs -- Packet Level Wireless Channel Model for OFDM System using SHLPNs -- Conclusions and Outlook.
In: Springer eBooksSummary: This SpringerBrief presents research in the application of Stochastic Petri Nets (SPN) to the performance evaluation of wireless networks under bursty traffic. It covers typical Quality-of-Service performance metrics such as mean throughput, average delay and packet dropping probability. Along with an introduction of SPN basics, the authors introduce the key motivation and challenges of using SPN to analyze the resource sharing performance in wireless networks. The authors explain two powerful modeling techniques that treat the well-known state space explosion problem: model decomposition and iteration, and model aggregation using stochastic high-level petri nets. The first technique assists in performance analysis of opportunistic scheduling, Device-to-Device communications with full frequency reuse and partial frequency reuse. The second technique is used to formulate a wireless channel mode for cross-layer performance analysis in OFDM system. Stochastic Petri Nets for Wireless Networks reveals useful insights for the design of radio resource management algorithms and a new line of thinking for the performance evaluation of future wireless networks. This material is valuable as a reference for researchers and professionals working in wireless networks and for advanced-level students studying wireless technologies in electrical engineering or computer science.
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Introduction -- Stochastic Petri Nets -- Performance Analysis of Opportunistic Schedulers using SPNs -- Performance Analysis of Device-to-Device Communications with Dynamics Interference using SPNs -- Packet Level Wireless Channel Model for OFDM System using SHLPNs -- Conclusions and Outlook.

This SpringerBrief presents research in the application of Stochastic Petri Nets (SPN) to the performance evaluation of wireless networks under bursty traffic. It covers typical Quality-of-Service performance metrics such as mean throughput, average delay and packet dropping probability. Along with an introduction of SPN basics, the authors introduce the key motivation and challenges of using SPN to analyze the resource sharing performance in wireless networks. The authors explain two powerful modeling techniques that treat the well-known state space explosion problem: model decomposition and iteration, and model aggregation using stochastic high-level petri nets. The first technique assists in performance analysis of opportunistic scheduling, Device-to-Device communications with full frequency reuse and partial frequency reuse. The second technique is used to formulate a wireless channel mode for cross-layer performance analysis in OFDM system. Stochastic Petri Nets for Wireless Networks reveals useful insights for the design of radio resource management algorithms and a new line of thinking for the performance evaluation of future wireless networks. This material is valuable as a reference for researchers and professionals working in wireless networks and for advanced-level students studying wireless technologies in electrical engineering or computer science.

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