TY - GEN
T1 - Performance analysis of energy harvesting sensors with time-correlated energy supply
AU - Michelusi, Nicolo
AU - Stamatiou, Kostas
AU - Zorzi, Michele
PY - 2012
Y1 - 2012
N2 - Sensors powered by energy harvesting devices (EHD) are increasingly being deployed in practice, due to the demonstrated advantage of long-term, autonomous operation, without the need for battery replacement. This paper is concerned with the following fundamental problem: how should the harvested energy be managed to ensure optimal performance, if the statistical properties of the ambient energy supply are known? To formulate the problem mathematically, we consider an EHD-powered sensor which senses data of varying importance and model the availability of ambient energy by a two-state Markov chain ('GOOD' and 'BAD'). Assuming that data transmission incurs an energy cost, our objective is to identify low-complexity transmission policies, which achieve good performance in terms of average long-term importance of the transmitted data. We derive the performance of a Balanced Policy (BP), which adapts the transmission probability to the ambient energy supply, so as to balance energy harvesting and consumption, and demonstrate that it performs within 5% of the globally optimal policy. Moreover, a BP which avoids energy overflow by always transmitting when the sensor battery is fully charged is shown to perform within 4% of the optimum. Finally, we identify a key performance parameter of the system, the relative battery capacity, defined as the ratio of the battery capacity to the expected duration of the BAD harvesting period.
AB - Sensors powered by energy harvesting devices (EHD) are increasingly being deployed in practice, due to the demonstrated advantage of long-term, autonomous operation, without the need for battery replacement. This paper is concerned with the following fundamental problem: how should the harvested energy be managed to ensure optimal performance, if the statistical properties of the ambient energy supply are known? To formulate the problem mathematically, we consider an EHD-powered sensor which senses data of varying importance and model the availability of ambient energy by a two-state Markov chain ('GOOD' and 'BAD'). Assuming that data transmission incurs an energy cost, our objective is to identify low-complexity transmission policies, which achieve good performance in terms of average long-term importance of the transmitted data. We derive the performance of a Balanced Policy (BP), which adapts the transmission probability to the ambient energy supply, so as to balance energy harvesting and consumption, and demonstrate that it performs within 5% of the globally optimal policy. Moreover, a BP which avoids energy overflow by always transmitting when the sensor battery is fully charged is shown to perform within 4% of the optimum. Finally, we identify a key performance parameter of the system, the relative battery capacity, defined as the ratio of the battery capacity to the expected duration of the BAD harvesting period.
UR - http://www.scopus.com/inward/record.url?scp=84875695296&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84875695296&partnerID=8YFLogxK
U2 - 10.1109/Allerton.2012.6483305
DO - 10.1109/Allerton.2012.6483305
M3 - Conference contribution
AN - SCOPUS:84875695296
SN - 9781467345385
T3 - 2012 50th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2012
SP - 839
EP - 846
BT - 2012 50th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2012
T2 - 2012 50th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2012
Y2 - 1 October 2012 through 5 October 2012
ER -