An Efficient And Scalable Hybrid Task Scheduling Approach For Cloud Environment

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Survey of Different Task Scheduling Algorithms in Cloud

2/10/2018  2.1 Task Scheduling in Cloud Environment The aim of task scheduling algorithms is to allocate the tasks among processors, increasing their resource utilization and decreasing the overall task execution time as well. Scheduling algorithms are classified into

Towards Enabling Mid-Scale Geo-Science Experiments Through

Activity wraps a task / application Input parameter collection and validation Request composition Invocation and monitoring Framework activities Interacts with Sigiri to schedule jobs and monitor the progress Data movement to / from cloud storage (Windows Blob Store or Amazon S3) Visualization 15

HPC Meets Cloud: Opportunities and Challenges in Designing

Cloud Computing focuses on maximizing the effectiveness of the shared resources Virtualization is the key technology for resource sharing in the Cloud Widely adopted in industry computing environment IDC Forecasts Worldwide Public IT Cloud Services Spending to Reach Nearly $108 Billion

Multilayer Hybrid Energy Efficient Approach in Green Cloud

Cloud computing is an important paradigm in Information Knowledge field. The main aim of Green Cloud computing is to reduce the energy consumed by physical resources in data center and save energy and also increases the performance of the system. There are several scheduling algorithms such as Adaptive Min-Min Scheduling Algorithm; Multilevel

Applicability of the Willow Architecture for Cloud Management

Cloud environment, we first determine the unique features of Cloud computing as compared to Grid computing. We derive three potential architectures based on this analysis: infrastructure-level, user-level, and a hybrid of the two. We analyze the pros and cons of each approach. 3.1 Characteristics of

Intelligent business process management for the enterprise

approach to deliver reliale and high-performing Linux, hybrid cloud, container, and ubernetes technologies. Red at helps customers integrate new and existing T applications, develop cloud-native applications, standardize on our industry-leading operating system, and automate, secure, and manage complex environments. Award-winning

OPENEDGE RDBMS / ADVANCED ENTERPRISE EDITION

Rapid changes in today s business environment mean your tools need to both keep pace and be powerful enough to manage your intensive database needs. Progress delivers an innovative on-premise, cloud or hybrid computing and application production solution in one package without breaking your budget or sacrificing security.

A Lightweight Hybrid Key Management Scheme using Third

The GA is applied for scheduling the tasks to the VMs. The following sections in the manuscript are organized in the way: Section II describes a brief overview of the existing key management schemes in cloud. Section III explains the proposed work including AES, two-level session key establishment protocol and GA-based task scheduling.

CURRICULUM VITAE MICHELLE M. ZHU

Decentralized Hybrid Workflow Scheduling Algorithm for Minimum End-to-end Delay in Heterogeneous Computing Environment. International Journal of High Performance Computing and Networking, vol. 8, no. 4, pp. 324~336, 2014. 10. M. Khaleel and M. Zhu. Energy-efficient Task Scheduling and Consolidation Algorithm for Workflow Jobs in Cloud.

TASK SCHEDULING ALGORITHM BASED ON HYBRID PARTICLE

dynamically scalable, Task scheduling which is NP-Complete problem has always been an important issue in cloud environment. In order to schedule the tasks quickly and efficiently, a task scheduling based on HPSO is proposed to meet the task requirements of users and improve the utilization of resources while minimizing the

CloudSim: A Toolkit for Modeling and Simulation of Cloud

CloudSim in their investigation on Cloud resource provisioning and energy-efficient management of data center resources. The usefulness of CloudSim is demonstrated by a case study involving dynamic provisioning of application services in hybrid federated clouds environment.

A New Multi-objective Evolutionary Algorithm for Inter

conditions and settings. The authors in 11] present a hybrid approach called FUGE that is [based on GA and fuzzy theory that aims to settle the job scheduling in cloud computing, which improves over 45% in terms of execution time, cost and average degree of imbalance than standard GA.

OSLO 17.10.2019 KEYNOTES

Multi Cloud - & Data Gateway. How the cloud gateway helps you secure you data in a multi-hybrid-cloud environment (Public Sector) One existing part of Openshift Container Storage is the Multi Cloud Data Gateway. This part provides the possibility to decide based on data regulations where things should be stored - On Premise, in AWS, GCE

HARDWARE-IN-THE-LOOP SIMULATION FOR AUTOMATED

Hardware-in-the-loop (HIL) simulation is a methodology for hybrid system synthesis where selected hardware and software components are immersed in a closed-loop virtual simulation environment (Ledin 1999). It provides a middle ground between physical prototyping and virtual simulation, combining the advantages of both approaches.

Volume 3, Issue 4, October 2013 A Survey on Resource

Major problems in task scheduling environment are load balancing, scalability, reliability, performance, and re-allocation of resources to the computing nodes dynamically. Resources such as internal and external requirements are maintained only in the cloud environment not on the primary environment. For the efficient

Tech Report of Distributed Deep Learning on Data Systems

and (4) Regular out-of-DBMS approach using Cerebro-Spark. MA is largely dominated by the UDAF approach but all the other ap-proaches fall on the Pareto frontier. For instance, the out-of-DBMS Cerebro-Spark approach and in-DB DA approaches are much more efficient than UDAF but may be harder to govern in a production environment.

Enabling Resource Awareness in Integrated Sensor Grid

The surveillance task analysis implemented in[10] identifies the sensory movement and deployment problems without conserving energy metrics. Hybrid scheme involving sensor movement and secure transmission in the sensor grid with he-terogeneous parameters are explored using the scalable key management schemes presented in [13].

Jedox Suite

Hybrid Data integration on-premise and in the cloud Jedox Cloud gives you a flexible hybrid approach where you get to enjoy the advantages of cloud economics today even while core or legacy systems remain on premise or in your own private cloud. Features of the Jedox Cloud: ⊲ Scalable

Mobile Micro-Cloud: Application Classification, Mapping

micro-cloud. First, we present an approach to deriving semantics for consistent representation of application requirements in order to enable a generic approach to application deployment in the mobile micro-cloud environment. Second, we examine the advantages of migrating an

Hybrid Approach for Resource Scheduling in Green Clouds

within Cloud computing environment. In proposed algorithm the scheduler allocate the task to that machine which is far from its critical temperature as well as it consume less power. The proposed work is on a hybrid approach for both temperature and power aware resource scheduling. Keywords - Green computing, Resource scheduling, Task

Deep Reinforcement Scheduling for Mobile Crowdsensing in

directed acyclic graph (DAG) into the task scheduling problem in a hybrid cloud environment which is similar to the fog computing [7]. Thus, Pham et al. introduced DAG to formulate the heterogeneous resources in fog computing and proposed a simple scheduling algorithm to improve the efficiency of the task scheduling in fog computing [34].

Docker Enterprise Edition on Cisco UCS C220 M5 Servers for

Docker works as effectively in on-prem or cloud environments; and supports both traditional and microservices architectures. Docker is widely used for building, networking, securing and scheduling applications, and managing them right from development to production. Docker sets enterprises on the path to digital transformation by

Review on Max-Min Task scheduling Algorithm for Cloud

Task scheduling algorithm is a basic requirement To make a number of cloud services for an efficient provider infrastructure. Task scheduling algorithm is responsible for mapping jobs submitted to cloud environment onto available resources in such a way that the total response time ,the makespan is minimized[6]. In cloud computing,There are many tasks require to be executed by the on hand

Curriculum Vitae Ioan Raicu, Ph.D.

4. Iman Sadooghi, Ioan Raicu (advisor). Scalable Resource Management in Cloud Computing , Illinois Institute of Technology, Computer Science Department, Doctorate Dissertation, September 2016 5. Itua Ijagbone, Ioan Raicu. Scalable Indexing and Searching on Distributed File Systems , Department of Computer Science,

Elysium PRO Titles with Abstracts 2019-20

logs, we propose an efficient method, called f-HMD, aims at scalable hybrid model discovery in a cloud computing environment. We present the detailed implementation of our approach over the Spark framework, and our experimental results demonstrate that the proposed method is efficient and scalable

Bi-Objective Virtual Machine Placement using Hybrid of

infrastructure [2]. It offers scalable and elastic computing and storage services. Cloud users can access computing resources without having to own, manage, and maintain them. There are three common cloud computing certain types of MOPs. Among these alternative approaches,models known as Infrastructure-as-a-Service (IaaS), Platform-as-a-Service

Mu lti-criteria D ec ision -m aking in Cloud S ervice S

(AHP) is the most efficient MCDM method for managing information security in Cloud computing as well as for task scheduling and resource allocation. The main limitation of multi-criteria optimization techniques such as genetic algorithms, is that they cannot handle mixed qualitative and quantitative criteria. Therefore,

Parallel Differential Evolution approach for Cloud

algorithms on Cloud clusters to solve specific optimization problems, and not scheduling of actual workflows based on multiple objectives. B. The DIET Middleware DIET [20] is an open-source middleware that enables a scalable execution of applications. Tasks are scheduled on distributed resources using a hierarchy of agents, as shown in Figure 1.

STOCKHOLM 3.10.2019 KEYNOTES

Multi Cloud - & Data Gateway. How the cloud gateway helps you secure you data in a multi-hybrid-cloud environment (Public Sector) One existing part of Openshift Container Storage is the Multi Cloud Data Gateway. This part provides the possibility to decide based on data regulations where things should be stored - On Premise, in AWS, GCE

A Self-Adaptive Resource Provisioning Approach using Fuzzy

challenging task due to the fluctuations of workload, cost, and few other quality parameters. Ghobaei-Arani et al. [8] introduced a self- adaptive resource provisioning technique for cloud-based applications. A hybrid approach is introduced with the combination of reinforcement learning and

Hybrid Computing Hierarchy based on-Line Analysis Service

users. This paper designs a hybrid dispatching cloud system based on cloud computing and edge computing, and studies online computing process in cloud computing environment, then concept of service-oriented is used to realize online computing service, designs the hierarchical online computing

Towards Understanding Uncertainty in Cloud Computing

scheduling assumes complete information about the scheduling problem and a static deterministic execution environment. However, in the cloud computing, services and resources are subject to considerable uncertainty during provisioning. We argue that the uncertainty is the main hassle of cloud

Powerful business rules and event management

planning use cases (e.g., vehicle routing, employee rostering, cloud optimization, task assignment, job scheduling, bin packing). Every organization faces scheduling puzzles and has to figure out how best to assign a limited set of constrained resources (employees, assets, time, and money) to

2014 9th IEEE International Conference on Networking

Tianjin, China 6-8 August 2014 IEEE Catalog Number: ISBN: CFP1462C-POD 978-1-4799-4086-8 2014 9th IEEE International Conference on Networking, Architecture, and Storage

Systematic Review on Existing Load Balancing Techniques in

efficient multi-objective load balancing of tasks scheduling algorithm with quality of service improvements for homogeneous and federated heterogeneous cloud environment. Keywords Cloud Computing, Load Balancing, Task Scheduling, Federated Cloud. 1. INTRODUCTION Load balancing appears to be Lthe major challenge in cloud computing, due to heterogeneous nature of cloud environment

International Journal of Computer Applications Technology

Traditional scheduling algorithms cannot operate in cloud environment (because of overhead costs), thus providers have resorted to heuristic or hybrid algorithms to fill this gap [1]. Effectiveness of task scheduling has a direct effect on the quality of cloud, thus many algorithms have been developed

HYBRID CAT SWARM OPTIMIZATION AND SIMULATED

al. (2016) proposed a multi-objective task scheduling method based on Ant Colony Optimization (MOSACO). The objective of the study is to address deadline and cost in a hybrid cloud computing environment. The researchers have been able to measure the effectiveness of their proposed MOSACO

Load Balancing Algorithms in Cloud Computing

Scheduling and load balancing are the two common concepts that cloud computing relies on ensuring that a prescribed task is assigned to the most appropriate virtual machine. Also, cloud computing should have the ability to handle multiple independent tasks that are arriving and execute them in

Industry s first hybrid cloud management solution for Dell

Efficient hybrid cloud management solution. Per seat, per year subscription with the option of either on-premises and cloud management or a combination of both with floating license allocation between private and public clouds. Free trial. Keep everything running. Stay

Microsoft Open Platform and Tools for AI (IoT)

Our Approach Time-slicing and migration as the primitives for scheduling (similar to OS) Mitigate head-of-line blocking Explore more trials in parallel Introspection: Application-aware profiling (time-per-minibatch) Continuous and introspective scheduling to adapt quickly to the changing environment Efficient implementation by exploiting the

The Definitive Guide to Rubrik Cloud Data Management

optimize resource utilization through two methods: Task Scheduling and Task Maintenance. Task Scheduling ensures that tasks are evenly distributed across the cluster while Task Maintenance enforces SLA policies on a daily and long-term basis. Once an SLA policy is set, Task Maintenance strategizes to meet these set goals for

Comparative Analysis of VM Scheduling Algorithms in Cloud

based on certain constraints. This task is performed by a VM scheduler using a suitable scheduling algorithm. VM scheduling plays an important role in balancing the load of the system so that the utilization of the resources should be optimum. Better the scheduling policy, more the efficient operation of the cloud system. General Terms

A Detailed Study on Heterogeneous Energy Approximation

Allocation and De-allocation of resources to the task arrived requires efficient scheduling method to uphold the factors such as performance, reliability, scalability, availability and most importantly Energy Efficiency. Cloud architecture consists of massively distributed datacenters around the globe and provides various scalable

HYBRID ACO-IWD OPTIMIZATION ALGORITHM FOR MINIMIZING

the efficient scheduling of the independent computational jobs. The results are obtained by the combination of the ACO algorithm with local and tabu search. Cristian Mateos et al [3] were the one who used the ant colony optimization inspired algorithm in cloud environment. This usage is based on minimizing the make span and the weighted

Cheshire East Council

Full cloud infrastructure as a service (IaaS) and associated applications Hybrid (a combination of the traditional and cloud approaches): 50% cloud and 50% on premise hosting 80% cloud and 20% on premise hosting Cloud migration partner investment to support the

A State-of-Art on Cloud Load Balancing Algorithms

One of the major issues in cloud computing which, needs serious attention is load balancing for its efficient performance. In the present work, a deep literature study has been carried out by considering the state of art algorithms for cloud load balancing. The algorithm includes traditional methods, heuristic, meta-heuristic, and hybrid approach.

INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY

still main concern in cloud computing. Task scheduling is a pivotal part in the field of the cloud environment. In task scheduling user requests for certain task, then tasks are scheduled to certain resources at a specific exemplification of time. Basically task scheduling mainly focuses to diminish the make span and lengthen the resource utilization. Task scheduling is an Non Polynomial-Complete