Exponential Algorithms for Scheduling Problems

This report focuses on the challenging issue of designing exponential algorithms for scheduling problems. Despite a growing literature dealing with such algorithms for other combinatorial optimization problems, it is still a recent research area in scheduling theory and few results are known. An exponential algorithm solves optimaly an NP-hard optimization problem with a worst-case time, or space, complexity that can be established and, which is lower than the one of a brute-force search. By the way, an exponential algorithm provides information about the complexity in the worst-case of solving a given NP-hard problem. In this report, we provide a survey of the few results known on schduling problems as well as some techniques for deriving exponential algorithms. In a second part we focus on some basic scheduling problems for which we propose exponential algorithms

Optimized Round Robin CPU Scheduling Algorithm

One of the fundamental function of an operating system is scheduling. There are 2 types of uni-processor operating system in general. Those are uni-programming and multi-programming. Uni-programming operating system execute only single job at a time while multiprogramming operating system is capable of executing multiple jobs concurrently. Resource utilization is the basic aim of multiprogramming operating system. There are many scheduling algorithms available for multi-programming operating system. But our work focuses on design and development aspect of new and novel scheduling algorithm for multi-programming operating system in the view of optimization. We developed a tool which gives output in the form of experimental results with respect to some standard and new scheduling algorithms e.g. First come first serve, shortest job first, round robin, optimal and a novel cpu scheduling algorithm etc

A Survey of Scheduling in 5G URLLC and Outlook for Emerging 6G Systems

Future wireless communication is expected to be a paradigm shift from three basic service requirements of 5th Generation (5G) including enhanced Mobile Broadband (eMBB), Ultra Reliable and Low Latency communication (URLLC) and the massive Machine Type Communication (mMTC). Integration of the three heterogeneous services into a single system is a challenging task. The integration includes several design issues including scheduling network resources with various services. Specially, scheduling the URLLC packets with eMBB and mMTC packets need more attention as it is a promising service of 5G and beyond systems. It needs to meet stringent Quality of Service (QoS) requirements and is used in time-critical applications. Thus through understanding of packet scheduling issues in existing system and potential future challenges is necessary. This paper surveys the potential works that addresses the packet scheduling algorithms for 5G and beyond systems in recent years. It provides state of the art review covering three main perspectives such as decentralised, centralised and joint scheduling techniques. The conventional decentralised algorithms are discussed first followed by the centralised algorithms with specific focus on single and multi-connected network perspective. Joint scheduling algorithms are also discussed in details. In order to provide an in-depth understanding of the key scheduling approaches, the performances of some prominent scheduling algorithms are evaluated and analysed. This paper also provides an insight into the potential challenges and future research directions from the scheduling perspective

Future applications of artificial intelligence to Mission Control Centers

Future applications of artificial intelligence to Mission Control Centers are presented in the form of the viewgraphs. The following subject areas are covered: basic objectives of the NASA-wide AI program; inhouse research program; constraint-based scheduling; learning and performance improvement for scheduling; GEMPLAN multi-agent planner; planning, scheduling, and control; Bayesian learning; efficient learning algorithms; ICARUS (an integrated architecture for learning); design knowledge acquisition and retention; computer-integrated documentation; and some speculation on future applications

Preemptive scheduling with position costs

This paper is devoted to basic scheduling problems in which the scheduling cost of a job is not a function of its completion time. Instead, the cost is derived from the integration of a cost function over the time intervals on which the job is processed. This criterion is specially meaningful when job preemption is allowed. Polynomial algorithms are presented to solve some special cases including a one-machine problem with a common due date and a two-machine problem with linear nondecreasing cost functions

Least space-time first scheduling algorithm : scheduling complex tasks with hard deadline on parallel machines

Both time constraints and logical correctness are essential to real-time systems and failure to specify and observe a time constraint may result in disaster. Two orthogonal issues arise in the design and analysis of real-time systems: one is the specification of the system, and the semantic model describing the properties of real-time programs; the other is the scheduling and allocation of resources that may be shared by real-time program modules. The problem of scheduling tasks with precedence and timing constraints onto a set of processors in a way that minimizes maximum tardiness is here considered. A new scheduling heuristic, Least Space Time First (LSTF), is proposed for this NP-Complete problem. Basic properties of LSTF are explored; for example, it is shown that (1) LSTF dominates Earliest-Deadline-First (EDF) for scheduling a set of tasks on a single processor (i.e., if a set of tasks are schedulable under EDF, they are also schedulable under LSTF); and (2) LSTF is more effective than EDF for scheduling a set of independent simple tasks on multiple processors. Within an idealized framework, theoretical bounds on maximum tardiness for scheduling algorithms in general, and tighter bounds for LSTF in particular, are proven for worst case behavior. Furthermore, simulation benchmarks are developed, comparing the performance of LSTF with other scheduling disciplines for average case behavior. Several techniques are introduced to integrate overhead (for example, scheduler and context switch) and more realistic assumptions (such as inter-processor communication cost) in various execution models. A workload generator and symbolic simulator have been implemented for comparing the performance of LSTF (and a variant -- LSTF+) with that of several standard scheduling algorithms. LSTF\u27s execution model, basic theories, and overhead considerations have been defined and developed. Based upon the evidence, it is proposed that LSTF is a good and practical scheduling algorithm for building predictable, analyzable, and reliable complex real-time systems. There remain some open issues to be explored, such as relaxing some current restrictions, discovering more properties and theorems of LSTF under different models, etc. We strongly believe that LSTF can be a practical scheduling algorithm in the near future

Aplikasi Gantt Chart Pada Algoritma Penjadualan Proses

Operating system is a compulsory subject taken in the Information Technology Student FTIK - USM . In the discussion of the material management process of the operating systems course , there are some scheduling algorithm which processes need to be understood and any existing process scheduling algorithm presented in the form of Grantt Charts . Because of the difficulties experienced by students in understanding the process of scheduling algorithms by an Operating System become researchers inspiration to conduct this study to make an application Grantt Chart.. This study uses a waterfall system development , where the flow will follow the research the phase in waterfall . This application will be built using Visual Basic 6 . The purpose of this research is to produce an application of learning are presented in graphical form to facilitate students in understanding the material scheduling process performed by an operating system so that students can also understand how a computer can do multiple processes simultaneously

Task Scheduling in Networks

Scheduling a set of tasks on a set of machines so as to yield an efficient schedule is a basic problem in computer science and operations research. Most of the research on this problem incorporates the potentially unrealistic assumption that communication between the different machines is instantaneous. In this paper we remove this assumption and study the problem of network scheduling, where each job originates at some node of a network, and in order to be processed at another node must take the time to travel through the network to that node. Our main contribution is to give approximation algorithms and hardness proofs for fully general forms of the fundamental problems in network scheduling. We consider two basic scheduling objectives: minimizing the makespan and minimizing the average completion time. For the makespan, we prove small constant factor hardness-to-approximate and approximation results. For the average completion time, we give a log-squared approximation algorithm for the most general form of the problem. The techniques used in this approximation are fairly general and have several other applications. For example, we give the first nontrivial approximation algorithm to minimize the average weighted completion time of a set of jobs on related or unrelated machines, with or without a network