Status updates over unreliable multiaccess channels

Applications like environmental sensing, and health and activity sensing, are supported by networks of devices (nodes) that send periodic packet transmissions over the wireless channel to a sink node. We look at simple abstractions that capture the following commonalities of such networks (a) the nodes send periodically sensed information that is temporal and must be delivered in a timely manner, (b) they share a multiple access channel and (c) channels between the nodes and the sink are unreliable (packets may be received in error) and differ in quality. We consider scheduled access and slotted ALOHA-like random access. Under scheduled access, nodes take turns and get feedback on whether a transmitted packet was received successfully by the sink. During its turn, a node may transmit more than once to counter channel uncertainty. For slotted ALOHA-like access, each node attempts transmission in every slot with a certain probability. For these access mechanisms we derive the age of information (AoI), which is a timeliness metric, and arrive at conditions that optimize AoI at the sink. We also analyze the case of symmetric updating, in which updates from different nodes must have the same AoI. We show that ALOHA-like access, while simple, leads to AoI that is worse by a factor of about 2e, in comparison to scheduled access.

[1]  Anthony Ephremides,et al.  Effect of Message Transmission Path Diversity on Status Age , 2016, IEEE Transactions on Information Theory.

[2]  Sanjit Krishnan Kaul,et al.  Minimizing age of information in vehicular networks , 2011, 2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[3]  Roy D. Yates,et al.  Real-time status updating: Multiple sources , 2012, 2012 IEEE International Symposium on Information Theory Proceedings.

[4]  Roy D. Yates,et al.  Lazy is timely: Status updates by an energy harvesting source , 2015, 2015 IEEE International Symposium on Information Theory (ISIT).

[5]  Eytan Modiano,et al.  Optimizing age-of-information in a multi-class queueing system , 2015, 2015 IEEE International Symposium on Information Theory (ISIT).

[6]  Marian Codreanu,et al.  On the Age of Information in Status Update Systems With Packet Management , 2015, IEEE Transactions on Information Theory.

[7]  Eytan Modiano,et al.  Minimizing the Age of Information in broadcast wireless networks , 2016, 2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[8]  Qing He,et al.  On optimal link scheduling with min-max peak age of information in wireless systems , 2016, 2016 IEEE International Conference on Communications (ICC).

[9]  Roy D. Yates,et al.  Update or wait: How to keep your data fresh , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.

[10]  Kun Chen,et al.  Age-of-information in the presence of error , 2016, 2016 IEEE International Symposium on Information Theory (ISIT).

[11]  Anthony Ephremides,et al.  Age of information under random updates , 2013, 2013 IEEE International Symposium on Information Theory.

[12]  Anthony Ephremides,et al.  Effect of message transmission diversity on status age , 2014, 2014 IEEE International Symposium on Information Theory.

[13]  Elif Uysal-Biyikoglu,et al.  Age of information under energy replenishment constraints , 2015, 2015 Information Theory and Applications Workshop (ITA).

[14]  Marian Codreanu,et al.  Age of information with packet management , 2014, 2014 IEEE International Symposium on Information Theory.