Extended analysis of Age of Information threshold violations

Abstract We study a scenario where a monitor is interested in the freshest possible update from a remote sensor. The monitor also seeks to minimize the number of updates that exceed a certain freshness threshold, beyond which, the information is deemed to be too old. Previous work has presented results for First Come First Served (FCFS) systems. However, it has been shown that Last Come First Served (LCFS) with preemption is more effective in terms of average Age of Information (AoI); we therefore study an M/G/1 LCFS system with preemption. The generality of the busy time distribution gives the advantage of applicability on any distribution inside the model. For example, one can use a deterministic distribution to study a TDMA system, a gamma distribution to model a routing network, or a more complicated distribution to study a CSMA access scheme. We find a general procedure to derive the exact expression of the outage update probability — i.e. the portion of time updates have information older than a certain threshold. We compare different busy time distributions to the ones already present in literature for equivalent FCFS systems, showing the benefit of using the former discipline. We further study how the variance of the busy time distribution affects the update outage probability. We find two instances of the busy time distribution, where at low thresholds and low loads, higher variance gives an advantage in terms of update outage probability. First, we compare the M/D/1 LCFS with preemption against the M/ Γ /1 LCFS with preemption and let the variance of the busy time of the latter vary, while maintaining the same average busy time for both systems. We further compare various M/ H 2 /1 LCFS with preemption with different coefficient of variation and same expected value, thus covering a wider spectrum of variation of the busy time.

[1]  James Gross,et al.  On the Distribution of AoI for the GI/GI/1/1 and GI/GI/1/2* Systems: Exact Expressions and Bounds , 2019, IEEE INFOCOM 2019 - IEEE Conference on Computer Communications.

[2]  Eytan Modiano,et al.  When a Heavy Tailed Service Minimizes Age of Information , 2019, 2019 IEEE International Symposium on Information Theory (ISIT).

[3]  Hai Le Vu,et al.  Accurate delay distribution for IEEE 802.11 DCF , 2006, IEEE Communications Letters.

[4]  Yang Yang,et al.  Delay distributions of slotted ALOHA and CSMA , 2003, IEEE Trans. Commun..

[5]  Emre Telatar,et al.  Status updates in a multi-stream M/G/1/1 preemptive queue , 2018, IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[6]  Biplab Sikdar,et al.  A queueing model for finite load IEEE 802.11 random access MAC , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[7]  Roy D. Yates,et al.  Real-time status: How often should one update? , 2012, 2012 Proceedings IEEE INFOCOM.

[8]  Mohamed-Slim Alouini,et al.  New results on the sum of Gamma random variates with application to the performance of wireless communication systems over Nakagami‐m fading channels , 2012, Trans. Emerg. Telecommun. Technol..

[9]  Ram K. Saxena Functional relations involving generalized H-function , 1998 .

[10]  Khaled Ben Letaief,et al.  Age-Upon-Decisions Minimizing Scheduling in Internet of Things: To Be Random or To Be Deterministic? , 2019, IEEE Internet of Things Journal.

[11]  A. Varga,et al.  THE OMNET++ DISCRETE EVENT SIMULATION SYSTEM , 2003 .

[12]  Jaume Barceló,et al.  IEEE 802.11AH: the WiFi approach for M2M communications , 2014, IEEE Wireless Communications.

[13]  Tetsuya Takine,et al.  The stationary distribution of the age of information in FCFS single-server queues , 2017, 2017 IEEE International Symposium on Information Theory (ISIT).

[14]  L. Falk,et al.  DQDB - some new characteristics , 1995 .

[15]  Kristopher L. Kuhlman,et al.  mpmath: a Python library for arbitrary-precision floating-point arithmetic , 2017 .

[16]  James Gross,et al.  Statistical guarantee optimization for age of information for the D/G/1 queue , 2018, IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[17]  Rajai Nasser,et al.  Age of information: The gamma awakening , 2016, 2016 IEEE International Symposium on Information Theory (ISIT).

[18]  Björn Landfeldt,et al.  Analysis of Age of Information Threshold Violations , 2019, MSWiM.

[19]  Hai Le Vu,et al.  MAC Access Delay of IEEE 802.11 DCF , 2007, IEEE Transactions on Wireless Communications.

[20]  Jian Song,et al.  Scheduling to Minimize Age of Synchronization in Wireless Broadcast Networks With Random Updates , 2020, IEEE Transactions on Wireless Communications.

[21]  Sayeed Ghani,et al.  Average end-to-end packet delay performance of IEEE 802.11 with Gamma distributed mean service time intervals , 2010, SoftCOM 2010, 18th International Conference on Software, Telecommunications and Computer Networks.

[22]  Tung-Wei Kuo,et al.  Minimum Age TDMA Scheduling , 2019, IEEE INFOCOM 2019 - IEEE Conference on Computer Communications.

[23]  Vangelis Angelakis,et al.  LUPMAC: A cross-layer MAC technique to improve the age of information over dense WLANs , 2016, 2016 23rd International Conference on Telecommunications (ICT).

[24]  Elif Uysal-Biyikoglu,et al.  Delay and Peak-Age Violation Probability in Short-Packet Transmissions , 2018, 2018 IEEE International Symposium on Information Theory (ISIT).

[25]  Roy D. Yates,et al.  Status updates through queues , 2012, 2012 46th Annual Conference on Information Sciences and Systems (CISS).

[26]  Soung Chang Liew,et al.  Information Update: TDMA or FDMA? , 2019, IEEE Wireless Communications Letters.