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Age of Information in Random Access Channels 2020 IEEE ISIT, Los Angeles, California, USA Xingran Chen Konstantinos Gatsis Hamed Hassani Shirin Saeedi Bidokhti University of Pennsylvania Background & Motivation Communication networks


  1. Age of Information in Random Access Channels 2020 IEEE ISIT, Los Angeles, California, USA Xingran Chen Konstantinos Gatsis Hamed Hassani Shirin Saeedi Bidokhti University of Pennsylvania

  2. Background & Motivation • Communication networks have witnessed rapid growth in the past few decades cyber-physical systems, the Internet of Things, smart cities, healthcare systems • Reliable and high speed Time-sensitive remote sensing, estimation, control • Transmission policies keeping freshest information — Age of Information markovity of the underlying physical processes [Kadota-Sinha-Biyikoglu-Singh-Modiano-18], [Kadota-Sinha-Modiano-19], [Hsu-Modiano-Duan-19], [Kadota-Modiano-20], [Kaul-Yates-17], [Talak-Karanman-Modiano-18], [Kosta-Pappas-Ephremides-Angelakis-19], [Jiang-Krishnamachari-Zheng-Zhou-Niu-18] [Jiang-Krishnamachari-Zhou-Niu-18], [Yates-Kaul-20] • We design for the first time decentralized age-based transmission policies • Provide analytical results on the age of information

  3. Background & Motivation • Communication networks have witnessed rapid growth in the past few decades cyber-physical systems, the Internet of Things, smart cities, healthcare systems • Reliable and high speed Time-sensitive remote sensing, estimation, control • Transmission policies keeping freshest information — Age of Information markovity of the underlying physical processes [Kadota-Sinha-Biyikoglu-Singh-Modiano-18], [Kadota-Sinha-Modiano-19], [Hsu-Modiano-Duan-19], [Kadota-Modiano-20], [Kaul-Yates-17], [Talak-Karanman-Modiano-18], [Kosta-Pappas-Ephremides-Angelakis-19], [Jiang-Krishnamachari-Zheng-Zhou-Niu-18] [Jiang-Krishnamachari-Zhou-Niu-18], [Yates-Kaul-20] • We design for the first time decentralized age-based transmission policies • Provide analytical results on the age of information

  4. Background & Motivation • Communication networks have witnessed rapid growth in the past few decades cyber-physical systems, the Internet of Things, smart cities, healthcare systems • Reliable and high speed Time-sensitive remote sensing, estimation, control • Transmission policies keeping freshest information — Age of Information markovity of the underlying physical processes [Kadota-Sinha-Biyikoglu-Singh-Modiano-18], [Kadota-Sinha-Modiano-19], [Hsu-Modiano-Duan-19], [Kadota-Modiano-20], [Kaul-Yates-17], [Talak-Karanman-Modiano-18], [Kosta-Pappas-Ephremides-Angelakis-19], [Jiang-Krishnamachari-Zheng-Zhou-Niu-18] [Jiang-Krishnamachari-Zhou-Niu-18], [Yates-Kaul-20] • We design for the first time decentralized age-based transmission policies • Provide analytical results on the age of information

  5. Background & Motivation • Communication networks have witnessed rapid growth in the past few decades cyber-physical systems, the Internet of Things, smart cities, healthcare systems • Reliable and high speed Time-sensitive remote sensing, estimation, control • Transmission policies keeping freshest information — Age of Information markovity of the underlying physical processes [Kadota-Sinha-Biyikoglu-Singh-Modiano-18], [Kadota-Sinha-Modiano-19], [Hsu-Modiano-Duan-19], [Kadota-Modiano-20], [Kaul-Yates-17], [Talak-Karanman-Modiano-18], [Kosta-Pappas-Ephremides-Angelakis-19], [Jiang-Krishnamachari-Zheng-Zhou-Niu-18] [Jiang-Krishnamachari-Zhou-Niu-18], [Yates-Kaul-20] • We design for the first time decentralized age-based transmission policies • Provide analytical results on the age of information

  6. Background & Motivation • Communication networks have witnessed rapid growth in the past few decades cyber-physical systems, the Internet of Things, smart cities, healthcare systems • Reliable and high speed Time-sensitive remote sensing, estimation, control • Transmission policies keeping freshest information — Age of Information markovity of the underlying physical processes [Kadota-Sinha-Biyikoglu-Singh-Modiano-18], [Kadota-Sinha-Modiano-19], [Hsu-Modiano-Duan-19], [Kadota-Modiano-20], [Kaul-Yates-17], [Talak-Karanman-Modiano-18], [Kosta-Pappas-Ephremides-Angelakis-19], [Jiang-Krishnamachari-Zheng-Zhou-Niu-18] [Jiang-Krishnamachari-Zhou-Niu-18], [Yates-Kaul-20] • We design for the first time decentralized age-based transmission policies • Provide analytical results on the age of information

  7. Age of Information (AoI) • A new metric to quantify the freshness of information (2011) [Kaul-Yates-Gruteser 11] • : timestamp of the most recently received update; . u ( t ) h ( t ) = t − u ( t ) • : the receiving time of k th status update t ′ k • status update k th : the generation time of t k T T ∫ 1 • Time average age: lim h ( t ) T →∞ 0

  8. Age of Information (AoI) • A new metric to quantify the freshness of information (2011) [Kaul-Yates-Gruteser 11] • : timestamp of the most recently received update; . u ( t ) h ( t ) = t − u ( t ) • : the receiving time of k th status update t ′ k • status update k th : the generation time of t k T T ∫ 1 • Time average age: lim h ( t ) T →∞ 0

  9. Age of Information (AoI) • A new metric to quantify the freshness of information (2011) [Kaul-Yates-Gruteser 11] • : timestamp of the most recently received update; . u ( t ) h ( t ) = t − u ( t ) • : the receiving time of k th status update t ′ k • status update k th : the generation time of t k T T ∫ 1 • Time average age: lim h ( t ) T →∞ 0

  10. Age of Information (AoI) • A new metric to quantify the freshness of information (2011) [Kaul-Yates-Gruteser 11] • : timestamp of the most recently received update; . u ( t ) h ( t ) = t − u ( t ) • : the receiving time of k th status update t ′ k • status update k th : the generation time of t k T T ∫ 1 • Time average age: lim h ( t ) T →∞ 0

  11. Age of Information (AoI) • A new metric to quantify the freshness of information (2011) [Kaul-Yates-Gruteser 11] • : timestamp of the most recently received update; . u ( t ) h ( t ) = t − u ( t ) • : the receiving time of k th status update t ′ k • status update k th : the generation time of t k T T ∫ 1 • Time average age: lim h ( t ) T →∞ 0

  12. System Model sensor i • statistically identical source nodes M arrival rate θ • Slotted time • Stochastic arrival/generation process θ • Collision channel, collision feedback • One unit transmission delay • Find transmission policy that minimizes Normalized Expected Weighted Sum π M K 1 ∑ ∑ AoI (NEWSAoI) h π lim i ( k ) KM 2 K →∞ i =1 k =1

  13. System Model sensor i • statistically identical source nodes M arrival rate θ • Slotted time • Stochastic arrival/generation process θ • Collision channel, collision feedback • One unit transmission delay • Find transmission policy that minimizes Normalized Expected Weighted Sum π M K 1 ∑ ∑ AoI (NEWSAoI) h π lim i ( k ) KM 2 K →∞ i =1 k =1

  14. System Model sensor i • statistically identical source nodes M arrival rate θ • Slotted time • Stochastic arrival/generation process θ • Collision channel, collision feedback • One unit transmission delay • Find transmission policy that minimizes Normalized Expected Weighted Sum π M K 1 ∑ ∑ AoI (NEWSAoI) h π lim i ( k ) KM 2 K →∞ i =1 k =1

  15. System Model sensor i • statistically identical source nodes M arrival rate θ • Slotted time • Stochastic arrival/generation process θ • Collision channel, collision feedback • One unit transmission delay • Find transmission policy that minimizes Normalized Expected Weighted Sum π M K 1 ∑ ∑ AoI (NEWSAoI) h π lim i ( k ) KM 2 K →∞ i =1 k =1

  16. System Model sensor i • statistically identical source nodes M arrival rate θ • Slotted time • Stochastic arrival/generation process θ • Collision channel, collision feedback • One unit transmission delay • Find transmission policy that minimizes Normalized Expected Weighted Sum π M K 1 ∑ ∑ AoI (NEWSAoI) h π lim i ( k ) KM 2 K →∞ i =1 k =1

  17. System Model sensor i • statistically identical source nodes M arrival rate θ • Slotted time • Stochastic arrival/generation process θ • Collision channel, collision feedback • One unit transmission delay • Find transmission policy that minimizes Normalized Expected Weighted Sum π M K 1 ∑ ∑ AoI (NEWSAoI) h π lim i ( k ) KM 2 K →∞ i =1 k =1

  18. Evolution of Age w i ( k + 1) = { no new packet arrives w i ( k ) + 1 Source AoI a new packet arrives 0 h i ( k + 1) = { a packet is delivered w i ( k ) + 1 Destination AoI no packet is delivered h i ( k ) + 1

  19. Lower Bound Theorem: For any transmission policy, NEWSAoI is lowered bounded by NEWSAoI ≥ 1 1) small arrival rates M θ 1 + 1 2) NEWSAoI ≥ large arrival rates 2 C RA 2 M where denote the sum-capacity of the underlying random access channel C RA • RA with feedback C RA ≤ 0.568 ( M → ∞ ) [Tasybakov-Likhanov] Probl. Peredachi Inf , vol. 23 • RA with CSMA C RA ≤ 1 C RA ≤ 1 • RA without feedback ( M → ∞ ) e

  20. Lower Bound Theorem: For any transmission policy, NEWSAoI is lowered bounded by NEWSAoI ≥ 1 1) small arrival rates M θ 1 + 1 2) NEWSAoI ≥ large arrival rates 2 C RA 2 M where denote the sum-capacity of the underlying random access channel C RA • RA with feedback C RA ≤ 0.568 ( M → ∞ ) [Tasybakov-Likhanov] Probl. Peredachi Inf , vol. 23 • RA with CSMA C RA ≤ 1 C RA ≤ 1 • RA without feedback ( M → ∞ ) e

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