The most challenging part of scheduling in real time systems is to achieve successful completion of a job before its deadline. Mainly two categories of algorithms i.e. static and dynamic tried to achieve this but both categories failed either in under-loaded condition or in over-loaded condition. Dynamic algorithms achieve optimum results in under-loaded condition but fail to achieve the same in over-loaded condition. On the other side static algorithms do not achieve optimum performance in underloaded condition but perform well in over-loaded condition. So our idea behind designing new scheduling algorithm is to achieve optimum performance in under-loaded condition and to achieve high performance in over-loaded condition. To achieve this we schedule jobs according to dynamic scheduling algorithm LLF (Least Laxity First) when system is under-loaded and when system becomes overloaded we schedule jobs according to static algorithm DM (Deadline Monotonic). In this paper we have proposed a LLF_DM algorithm which achieves optimum performance in under-loaded condition and achieves very high performance in over loaded condition.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.