Digital Commons Network^™

Scheduling Multiple Parallel Jobs Online, Kefu Lu

McKelvey School of Engineering Theses & Dissertations

The prevalence of parallel processing has only increased in recent years. Today, most computing machines available on the market shifted from using single processors to possessing a multicore architecture. Naturally, there has been considerable work in developing parallel programming languages and frameworks which programmers can use to leverage the computing power of these machines. These languages allow users to create programs with internal parallelism. The next, and crucial, step is to ensure that the computing system can efficiently execute these parallel jobs. Executing a single parallel job efficiently is a very well-studied problem in parallel computing. In the area of …

Permutation Flow Shop Via Simulated Annealing And Neh, Pooja Bhatt

UNLV Theses, Dissertations, Professional Papers, and Capstones

Permutation Flow Shop Scheduling refers to the process of allocating operations of jobs to machines such that an operation starts to process on machine j only after the processing completes in j-1machine. At a time a machine can process only one operation and similarly a job can have only one operation processed at a time. Finding a schedule that minimizes the overall completion times for Permutation Flow Shop problems is NP-Hard if the number of machines is greater than 2. Sowe concentrates on approaches with approximate solutions that are good enough for the problems. Heuristics is one way to find …

Cloud Job Scheduling Model Based On Improved Plant Growth Algorithm, Li Qiang, Xiaofeng Liu

Journal of System Simulation

Abstract: The performance of cloud job scheduling algorithm has a great importance to the whole cloud system. The key factors that affect cloud operation scheduling are found out, and a resource constraint model is established. The existing simulation plant growth algorithm is improved based on the Logistic model of plant growth law, so that the plant growth way was made to change according to the energy power. The comparison of four different plant models was carried out and their different features were analyzed. Compared with 6 typical cloud job scheduling algorithms, it is concluded that the improved simulation plant growth …

Optimization Of Scheduling Rule Of Unidirectional Material Handling System With Short-Cut, Juntao Li, Kun Xia, Kise Hiroshi

Journal of System Simulation

Abstract: To decrease the interference and improve the performance of a unidirectional circulation-type material handling system on a single loop with a shortcut, the interference and scheduling problem between AGVs are studied. According to the actual situation of material handling system, the interferences of two scheduling rules (random rule and order rule) are analyzed. An optimal scheduling rule under the interference case—exchange order rule is proposed. Different scheduling rules have an influence on the interference between AGVs and then have an important effect on the efficiency of the whole system. Experiment results show that the exchange order (E-Order) rule …

Sky Surveys Scheduling Using Reinforcement Learning, Andres Felipe Alba Hernandez

Graduate Research Theses & Dissertations

Modern cosmic sky surveys (e.g., CMB S4, DES, LSST) collect a complex diversity of astronomical objects. Each of class of objects presents different requirements for observation time and sensitivity. For determining the best sequence of exposures for mapping the sky systematically, conventional scheduling methods do not optimize the use of survey time and resources. Dynamic sky survey scheduling is an NP-hard problem that has been therefore treated primarily with heuristic methods. We present an alternative scheduling method based on reinforcement learning (RL) that aims to optimize the use of telescope resources for scheduling sky surveys.

We present an exploration of …

Pharmaceutical Scheduling Using Simulated Annealing And Steepest Descent Method, Bryant Jamison Spencer

Graduate Theses, Dissertations, and Problem Reports

In the pharmaceutical manufacturing world, a deadline could be the difference between losing a multimillion-dollar contract or extending it. This, among many other reasons, is why good scheduling methods are vital. This problem report addresses Flexible Flowshop (FF) scheduling using Simulated Annealing (SA) in conjunction with the Steepest Descent heuristic (SD).

FF is a generalized version of the flowshop problem, where each product goes through S number of stages, where each stage has M number of machines. As opposed to a normal flowshop problem, all ‘jobs’ do not have to flow in the same sequence from stage to stage. The …

Multi-Robot Coordination And Scheduling For Deactivation & Decommissioning, Sebastian A. Zanlongo

FIU Electronic Theses and Dissertations

Large quantities of high-level radioactive waste were generated during WWII. This waste is being stored in facilities such as double-shell tanks in Washington, and the Waste Isolation Pilot Plant in New Mexico. Due to the dangerous nature of radioactive waste, these facilities must undergo periodic inspections to ensure that leaks are detected quickly. In this work, we provide a set of methodologies to aid in the monitoring and inspection of these hazardous facilities. This allows inspection of dangerous regions without a human operator, and for the inspection of locations where a person would not be physically able to enter.

First, …

Scheduling In Mapreduce Clusters, Chen He

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

MapReduce is a framework proposed by Google for processing huge amounts of data in a distributed environment. The simplicity of the programming model and the fault-tolerance feature of the framework make it very popular in Big Data processing.

As MapReduce clusters get popular, their scheduling becomes increasingly important. On one hand, many MapReduce applications have high performance requirements, for example, on response time and/or throughput. On the other hand, with the increasing size of MapReduce clusters, the energy-efficient scheduling of MapReduce clusters becomes inevitable. These scheduling challenges, however, have not been systematically studied.

The objective of this dissertation is to …

Smartphone-Based Self Rescue System For Disaster Rescue, Xitong Zhou

Theses, Dissertations and Capstones

Recent ubiquitous earthquakes have been leading to mass destruction of electrical power and cellular infrastructures, and deprive the innocent lives across the world. Due to the wide-area earthquake disaster, unavailable power and communication infrastructure, limited man-power and resources, traditional rescue operations and equipment are inefficient and time-consuming, leading to the golden hours missed. With the increasing proliferation of powerful wireless devices, like smartphones, they can be assumed to be abundantly available among the disaster victims and can act as valuable resources to coordinate disaster rescue operations. In this paper, we propose a smartphone-based self-rescue system, also referred to as RescueMe, …

A Framework To Audit Scheduling Events In The Linux Operating System, Edward G. Hudgins

Open Access Theses & Dissertations

Soft real-time systems have responsiveness requirements that are desirable but not critical for operational effectiveness. This Thesis describes a new scheduler logging framework named "Integrated Process Scheduler Archiver" (IPSA) intended to assist with this analysis. Due to human sensitivity to interface delays on gesture-driven devices, mobile devices are a common case of soft-real time systems. Mobile systems generally do not incorporate real-time schedulers, but instead utilize over-provisioning and a variety of scheduling heuristics to generally provide acceptable responsiveness. These devices are highly multi-programmed Energy limitations on mobile limit the extent of overprovisioning, thereby increasing the sensitivity of system behavior to …

Mechanism Design For Strategic Project Scheduling, Pradeep Varakantham, Na Fu

Research Collection School Of Computing and Information Systems

Organizing large scale projects (e.g., Conferences, IT Shows, F1 race) requires precise scheduling of multiple dependent tasks on common resources where multiple selfish entities are competing to execute the individual tasks. In this paper, we consider a well studied and rich scheduling model referred to as RCPSP (Resource Constrained Project Scheduling Problem). The key change to this model that we consider in this paper is the presence of selfish entities competing to perform individual tasks with the aim of maximizing their own utility. Due to the selfish entities in play, the goal of the scheduling problem is no longer only …

Augmenting Decisions Of Taxi Drivers Through Reinforcement Learning For Improving Revenues, Tanvi Verma, Pradeep Varakantham, Sarit Kraus, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Taxis (which include cars working with car aggregation systems such as Uber, Grab, Lyft etc.) have become a critical component in the urban transportation. While most research and applications in the context of taxis have focused on improving performance from a customer perspective, in this paper,we focus on improving performance from a taxi driver perspective. Higher revenues for taxi drivers can help bring more drivers into the system thereby improving availability for customers in dense urban cities.Typically, when there is no customer on board, taxi driverswill cruise around to find customers either directly (on thestreet) or indirectly (due to a …

Building Efficient Large-Scale Big Data Processing Platforms, Jiayin Wang

Graduate Doctoral Dissertations

In the era of big data, many cluster platforms and resource management schemes are created to satisfy the increasing demands on processing a large volume of data. A general setting of big data processing jobs consists of multiple stages, and each stage represents generally defined data operation such as ltering and sorting. To parallelize the job execution in a cluster, each stage includes a number of identical tasks that can be concurrently launched at multiple servers. Practical clusters often involve hundreds or thousands of servers processing a large batch of jobs. Resource management, that manages cluster resource allocation and job …

Minimizing Scheduling Overhead In Lre-Tl Real-Time Multiprocessor Scheduling Algorithm, Hitham Seddig Alhassan Alhussian, Mohamed Nordin Bin Zakaria, Fawnizu Azmadi Bin Hussin

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we present a modification of the local remaining execution-time and local time domain (LRE-TL) real-time multiprocessor scheduling algorithm, aimed at reducing the scheduling overhead in terms of task migrations. LRE-TL achieves optimality by employing the fairness rule at the end of each time slice in a fluid schedule model. LRE-TL makes scheduling decisions using two scheduling events. The bottom (B) event, which occurs when a task consumes its local utilization, has to be preempted in order to resume the execution of another task, if any, or to idle the processor if none exist. The critical (C) event …

A Data-Aware Cognitive Engine For Scheduling Data Intensive Applications In A Grid, Vijaya Nagarajan, Maluk Mohamed Mulk Abdul

Turkish Journal of Electrical Engineering and Computer Sciences

Data-intensive applications produce huge amounts of data that need to be stored, analyzed, and interpreted. A data grid serves as a cost-effective infrastructure for solving these data-intensive applications. Existing scheduling strategies are best suited for handling compute-intensive applications, although they lack in performance while handling data-intensive applications. In this work, a novel mechanism of incorporating cognitive science in a data grid is proposed for scheduling data-intensive workflows. A unique model is derived in which a cognitive engine (CE) is built into the middleware of the data grid. The intelligent agents present in the CE handle the request for data sets …

Decentralized Scheduling For Many-Task Applications In The Hybrid Cloud, Brian Lyle Peterson

LSU Doctoral Dissertations

While Cloud Computing has transformed how we solve many computing tasks, some scientific and many-task applications are not efficiently executed on cloud resources. Decentralized scheduling, as studied in grid computing, can provide a scalable system to organize cloud resources and schedule a variety of work. By measuring simulations of two algorithms, the fully decentralized Organic Grid, and the partially decentralized Air Traffic Controller from IBM, we establish that decentralization is a workable approach, and that there are bottlenecks that can impact partially centralized algorithms. Through measurements in the cloud, we verify that our simulation approach is sound, and assess the …

Orienteering Problem: A Survey Of Recent Variants, Solution Approaches And Applications, Aldy Gunawan, Hoong Chuin Lau, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

The Orienteering Problem (OP) has received a lot of attention in the past few decades. The OP is a routing problem in which the goal is to determine a subset of nodes to visit, and in which order, so that the total collected score is maximized and a given time budget is not exceeded. A number of typical variants has been studied, such as the Team OP, the (Team) OP with Time Windows and the Time Dependent OP. Recently, a number of new variants of the OP was introduced, such as the Stochastic OP, the Generalized OP, the Arc OP, …

Mixed-Criticality Scheduling To Minimize Makespan, Sanjoy K. Baruah, Arvind Easwaran, Zhishan Guo

Computer Science Faculty Research & Creative Works

In the mixed-criticality job model, each job is characterized by two execution time parameters, representing a smaller (less conservative) estimate and a larger (more conservative) estimate on its actual, unknown, execution time. Each job is further classified as being either less critical or more critical. The desired execution semantics are that all jobs should execute correctly provided all jobs complete upon being allowed to execute for up to the smaller of their execution time estimates, whereas if some jobs need to execute beyond their smaller execution time estimates (but not beyond their larger execution time estimates), then only the jobs …

Orienteering Problem: A Survey Of Recent Variants, Solution Approaches And Applications, Aldy Gunawan, Hoong Chuin Lau, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

Duplicate record, see https://ink.library.smu.edu.sg/sis_research/3271. The Orienteering Problem (OP) has received a lot of attention in the past few decades. The OP is a routing problem in which the goal is to determine a subset of nodes to visit, and in which order, so that the total collected score is maximized and a given time budget is not exceeded. A number of typical variants has been studied, such as the Team OP, the (Team) OP with Time Windows and the Time Dependent OP. Recently, a number of new variants of the OP was introduced, such as the Stochastic OP, the …

A Dynamic Run-Profile Energy-Aware Approach For Scheduling Computationally Intensive Bioinformatics Applications, Sachin Pawaskar, Hesham Ali

Computer Science Faculty Proceedings & Presentations

High Performance Computing (HPC) resources are housed in large datacenters, which consume exorbitant amounts of energy and are quickly demanding attention from businesses as they result in high operating costs. On the other hand HPC environments have been very useful to researchers in many emerging areas in life sciences such as Bioinformatics and Medical Informatics. In an earlier work, we introduced a dynamic model for energy aware scheduling (EAS) in a HPC environment; the model is domain agnostic and incorporates both the deadline parameter as well as energy parameters for computationally intensive applications. Our proposed EAS model incorporates 2-phases. In …

Strategic Planning For Setting Up Base Stations In Emergency Medical Systems, Supriyo Ghosh, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Emergency Medical Systems (EMSs) are an important component of public health-care services. Improving infrastructure for EMS and specifically the construction of base stations at the ”right” locations to reduce response times is the main focus of this paper. This is a computationally challenging task because of the: (a) exponentially large action space arising from having to consider combinations of potential base locations, which themselves can be significant; and (b) direct impact on the performance of the ambulance allocation problem, where we decide allocation of ambulances to bases. We present an incremental greedy approach to discover the placement of bases that …

The Asynchronous T-Step Approximation For Scheduling Batch Flow Systems, David R. Grimsman

Theses and Dissertations

Heap models in the max-plus algebra are interesting dynamical systems that can be used to model a variety of tetris-like systems, such as batch flow shops for manufacturing models. Each heap in the model can be identified with a single product to manufacture. The objective is to manufacture a group of products in such an order so as to minimize the total manufacturing time. Because this scheduling problem reduces to a variation of the Traveling Salesman Problem (known to be NP-complete), the optimal solution is computationally infeasible for many real-world systems. Thus, a feasible approximation method is needed. This work …

Dual Formulations For Optimizing Dec-Pomdp Controllers, Akshat Kumar, Hala Mostafa, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Decentralized POMDP is an expressive model for multi-agent planning. Finite-state controllers (FSCs)---often used to represent policies for infinite-horizon problems---offer a compact, simple-to-execute policy representation. We exploit novel connections between optimizing decentralized FSCs and the dual linear program for MDPs. Consequently, we describe a dual mixed integer linear program (MIP) for optimizing deterministic FSCs. We exploit the Dec-POMDP structure to devise a compact MIP and formulate constraints that result in policies executable in partially-observable decentralized settings. We show analytically that the dual formulation can also be exploited within the expectation maximization (EM) framework to optimize stochastic FSCs. The resulting EM algorithm …

Efficient Execution Of Top-K Closeness Centrality Queries, Paul W. Olsen

Legacy Theses & Dissertations (2009 - 2024)

Many of today's applications can benefit from the discovery of the most central entities in real-world networks.

Single Machine Scheduling With Job-Dependent Machine Deterioration, Wenchang Luo, Xu Yao, Weitian Tong, Guohui Lin

Department of Computer Science Faculty Publications

We consider the single machine scheduling problem with job-dependent machine deterioration. In the problem, we are given a single machine with an initial non-negative maintenance level, and a set of jobs each with a non-preemptive processing time and a machine deterioration. Such a machine deterioration quantifies the decrement in the machine maintenance level after processing the job. To avoid machine breakdown, one should guarantee a non-negative maintenance level at any time point; and whenever necessary, a maintenance activity must be allocated for restoring the machine maintenance level. The goal of the problem is to schedule the jobs and the maintenance …

Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Shih-Fen Cheng

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …

Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Shih-Fen Cheng

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …

Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Shih-Fen CHENG

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …

Online Dormitory Reservation System, Adithya Mothe, Koushik Kumar Suragoni, Ramya Vakity

All Capstone Projects

This project is Online Dorms Systems which allows users to book their room in the dorm from anywhere; this is an automated system where the user can search the availability of rooms in the dorm.

The search can be done based on the dates. The rooms that available are come with the status available, it will display all the rooms available as of that particular search date. Once the room has been booked the user can cancel the reservation within 48 hours. And there is concept of user login. As the user creates his own account with his email id, …

Moneyware: Simulating Software Portfolio Quality Management, Robert David Beverly

Masters Theses & Specialist Projects

In this research we introduce MoneyWare, a simulator designed to explore and ultimately to provide guidance on simulating software portfolio quality management. The name “MoneyWare” is inspired by the movie Moneyball. It chronicled a baseball team which used more descriptive statistics to achieve a higher quality ball club with limited resources. MoneyWare is inspired by the observation that the problem of software development is somewhat analogous. Management is faced with an incoming stream of tasks for development. The tasks vary in terms of size, priority, risk, and date needed. But, in any case, the demands come to more than the …