  In various service-oriented applications such as distributed autonomous
delivery, healthcare, tourism, transportation, and many others, where service
agents need to perform serial and time-bounded tasks to achieve their goals,
quality of service must constantly be assured. In addition to safety
requirements, such agents also need to fulfill performance requirements in
order to satisfy their quality of service. This paper proposes the novel
quality-aware time window temporal logic (QTWTL) by extending the traditional
time window temporal logic (TWTL) with two operators for counting and
aggregation operations. We also propose offline runtime monitoring algorithms
for the performance monitoring of QTWTL specifications. To analyze the
feasibility and efficiency of our proposed approach, we generate a large number
of traces using the New York City Taxi and Limousine Commission Trip Record
data, formalize their performance requirements using QTWTL, and monitor them
using the proposed algorithms. The obtained results show that the monitoring
algorithm has a linear space and time complexity with respect to the number of
traces monitored.
