With the recent adoption of edge computing, I nternet of T hings ( IoT ) devices collaborate at the network edge to facilitate edge-native applications. In this setting, IoT devices are typically encapsulated as IoT services to encode their functionalities, and their collaboration is achieved through IoT service composition. Due to the continuous resource occupancy, release, and consumption of IoT devices at runtime, a composition, which is functionally compatible and non-functionally optimal at this moment, may not hold in the forthcoming time durations, when certain IoT services may significantly downgrade in their Q uality-of- S ervices ( QoS ). To guarantee the compatibility of compositions with QoS variations, this article proposes an adaptive composition mechanism leveraging C omputation T ree L ogic ( CTL ) specifications. Specifically, we formalize the composition as a temporal task, and convert it to CTL formulae with the abstractions of required functionalities and composite structures. Functional compatibility is formally interpreted by CTL semantics during the execution of compositions. Besides, we construct a QoS D ependency G raph ( QoSDG ) to capture QoS variations, and achieve adaptive composition with dynamic QoS satisfactions. Extensive experiments are conducted upon publicly-available datasets, and comparison results demonstrate that our technique outperforms the state-of-the-art counterparts in heterogenous scenarios with higher QoS dependencies ranging from 0.3<inline-formula><tex-math notation="LaTeX">\%</tex-math> <mml:math><mml:mo>%</mml:mo></mml:math><inline-graphic xlink:href="zhou-ieq1-3184013.gif"/> </inline-formula> to 27.8<inline-formula><tex-math notation="LaTeX">\%</tex-math> <mml:math><mml:mo>%</mml:mo></mml:math><inline-graphic xlink:href="zhou-ieq2-3184013.gif"/> </inline-formula>.