Recent　efforts　in　network　measurement　place　measurement　tasks　on　programmable　switches　to　measure　high-speed　traffic.　These　tasks　extract　flow　data,　i.e.,　events,　from　packets　and　send　events　to　the　control　plane.　However,　the　tasks　may　generate　massive　events　in　a　short　time.　In　this　context,　the　links　transferring　events　to　the　control　plane　and　the　control　plane　servers　that　handle　events　may　be　overloaded,　i.e.,　control　plane　overload.　None　of　existing　solutions　can　eliminate　control　plane　overload.　In　this　paper,　we　propose　MTP,　a　framework　that　eliminates　control　plane　overload　via　careful　measurement　task　placement.　Our　key　idea　is　to　allocate　enough　resources　for　each　task　during　task　placement　to　avoid　control　plane　overload　at　runtime.　For　each　task,　MTP　estimates　its　maximum　possible　rate　of　sending　events　to　the　control　plane.　Then　its　optimization　framework　addresses　the　resource　restrictions　of　both　switches　and　the　control　plane.　The　experiments　on　Tofino　switches　indicate　that　MTP　outperforms　existing　solutions　with　higher　accuracy　in　several　use　cases.　©　2022　IEEE.