Comparing Lottery and EEVDF Scheduling Algorithm for Real-time Applications
نویسندگان
چکیده
In this paper, we study two proportional-share resource management algorithms, Lottery Scheduling and Earliest Eligible Virtual Deadline First (EEVDF), and compare their performances in scheduling real time jobs having specific deadlines. Lottery scheduling is not used to schedule real time jobs; we test whether we can use it for this purpose by designing the ticket allocation policy according to real-time constraints. On the other hand, EEVDF is designed to support real time jobs. But there is no quantitative evaluation of EEVDF for scheduling real time jobs in the literature, so we evaluate its performance for real time jobs. We evaluate the performance of these two algorithms by implementing them in Java and simulating with synthetic jobs having real time deadlines and compare the performance of the lottery scheduling with that of EEVDF. From the results of the evaluations, we find that lottery scheduling performs competitively with EEVDF scheduling when the real time jobs have large periodic deadlines.
منابع مشابه
Pareto-based Multi-criteria Evolutionary Algorithm for Parallel Machines Scheduling Problem with Sequence-dependent Setup Times
This paper addresses an unrelated multi-machine scheduling problem with sequence-dependent setup time, release date and processing set restriction to minimize the sum of weighted earliness/tardiness penalties and the sum of completion times, which is known to be NP-hard. A Mixed Integer Programming (MIP) model is proposed to formulate the considered multi-criteria problem. Also, to solve the mo...
متن کاملAn Efficient Genetic Algorithm for Task Scheduling on Heterogeneous Computing Systems Based on TRIZ
An efficient assignment and scheduling of tasks is one of the key elements in effective utilization of heterogeneous multiprocessor systems. The task scheduling problem has been proven to be NP-hard is the reason why we used meta-heuristic methods for finding a suboptimal schedule. In this paper we proposed a new approach using TRIZ (specially 40 inventive principles). The basic idea of thi...
متن کاملAn Efficient Genetic Algorithm for Task Scheduling on Heterogeneous Computing Systems Based on TRIZ
An efficient assignment and scheduling of tasks is one of the key elements in effective utilization of heterogeneous multiprocessor systems. The task scheduling problem has been proven to be NP-hard is the reason why we used meta-heuristic methods for finding a suboptimal schedule. In this paper we proposed a new approach using TRIZ (specially 40 inventive principles). The basic idea of thi...
متن کاملA New Hybrid Meta-Heuristics Approach to Solve the Parallel Machine Scheduling Problem Considering Human Resiliency Engineering
This paper proposes a mixed integer programming model to solve a non-identical parallel machine (NIPM) scheduling with sequence-dependent set-up times and human resiliency engineering. The presented mathematical model is formulated to consider human factors including Learning, Teamwork and Awareness. Moreover, processing time of jobs are assumed to be non-deterministic and dependent to their st...
متن کاملAn Effective Task Scheduling Framework for Cloud Computing using NSGA-II
Cloud computing is a model for convenient on-demand user’s access to changeable and configurable computing resources such as networks, servers, storage, applications, and services with minimal management of resources and service provider interaction. Task scheduling is regarded as a fundamental issue in cloud computing which aims at distributing the load on the different resources of a distribu...
متن کامل