Accurately measured jets are mandatory for precision measurements of the Standard Model of particle physics as well as for searches for new physics.
The increased instantaneous luminosity and center-of-mass energy at LHC Run 2 pose challenges for pileup mitigation and the measurement of jet characteristics.
This thesis concentrates on using Z + jets events to calibrate the energy scale of jets recorded by the CMS detector in 2018.
Furthermore, it proposes a new procedure for determining the jet momentum resolution using Z + jets events.
This procedure is expected to allow cross-checking complementary measurement approaches and increasing the accuracy of the jet momentum resolution at the CMS experiment.
Data-intensive end-user analyses in High Energy Physics such as the presented calibration of jets put enormous challenges on the computing infrastructure since requiring high data throughput.
Besides the particle physics analysis, this thesis also focuses on accelerating data processing within a distributed computing infrastructure via a coordinated distributed caching approach.
Coordinated placement of critical data within distributed caches and matching workflows to the most suitable host in terms of cached data allows for optimizing processing efficiency.
Improving the processing of data-intensive workflows aims at shortening turnaround cycles and thus deriving physics results, e.g. the jet calibration results, faster.