The phrase "application lifetime" is correct and usable in written English.
It can be used to refer to the duration or period during which an application is active or in use, often in the context of software development or lifecycle management.
Example: "Understanding the application lifetime is crucial for effective resource management and planning updates."
Alternatives: "application duration" or "software lifecycle".
Harvesting the environmental energy to power wireless nodes is a promising method to address the conflict between node's limited energy and application lifetime requirements.
A component targeting sensor virtualization, which is programmable at runtime and is able to execute different adaptation schemes that may change during the application lifetime, is presented in [9].
We match the scenarios to the most appropriate existing wireless technology that is expected to sustain scalability in the number of nodes or increased data rates for the expected application lifetime.
It explores that with careful operating system (OS) design with respect to scheduling and dynamic voltage scaling, the deadline guarantees for wireless multimedia applications as well as energy efficiency of mobile nodes to extend the application lifetime can be achieved.
I recommend that Acquavella et al. (2004) consider revising their analyses by correcting properly for incomplete urine collection, correcting for the initial condition of prior glyphosate exposure, and adjusting for the experience of the applicator (lifetime number of application days) as an explanatory variable.
In comparison to standard applications, lifetimes of lead acid batteries in photovoltaic (PV) systems are shorter than one might expect.
This study shows that it is feasible to identify who are the worse off empirically by the application of lifetime QALYs and proportional shortfalls.
Finally some applications to lifetime prediction under variable amplitude fatigue loading are presented.
Applications to lifetime prediction of structural components, as well as toughness and durability of materials are discussed.
For example, more recently, Cruz et al. (2016) proposed the log-odd log-logistic Weibull regression model with censored data, Lanjoni et al. (2016) defined an extended Burr XII regression model and Ortega et al. (2016) introduced the odd Birnbaum-Saunders regression model with applications to lifetime data.
With large scale battery systems being more and more used in demanding applications regarding lifetime, performance and safety, it is of great importance to utilize not only cells with a high cyclic and calendric lifetime but also to optimize the whole system architecture.
