Workflow specification and scheduling with security constraints in hybrid clouds
Daniel S. MarconLuiz F. BittencourtRamide DantasMiguel NevesEdmundo R. M. MadeiraStênio FernandesCarlos KamienskiMarinho Pilla BarcelosLuciano Paschoal GasparyNelson L. S. da Fonseca
15
Citation
19
Reference
10
Related Paper
Citation Trend
Abstract:
Hybrid cloud management must deal with resources from both public and private clouds, as well as their interaction. When workflows are executed in a hybrid cloud, dependencies among their components bring new factors to be considered during specification, scheduling, and virtual machine provisioning. In this paper, we describe three components, namely workflow code, scheduler, and resource allocator, which enable the specification and execution of workflows in hybrid clouds in the context of the AltoStratus middleware. We present a case study that shows the interaction among these components, and their applicability in practice.Keywords:
Provisioning
As Cloud computing provides Anything as a Service (XaaS), many applications can be developed and run on the Cloud without concerns of platforms. Data-incentive applications are also easily developed on virtual machines provided by the Cloud. In this work, we investigate cost-effective resource provisioning for MapReduce applications with deadline constraints, as the MapReduce programming model is useful and powerful in developing data-incentive applications. When users want to run MapReduce applications, they submit jobs to a Cloud resource broker which allocates appropriate virtual machines with consideration of SLAs (Service-Level Agreements). The goal of resource provisioning in this paper is to minimize the cost of virtual machines for executing MapReduce applications without violating their deadlines to be finished by. We propose two resource provisioning approaches: one based on listed pricing policies and the other based on deadline-aware tasks packing. Throughout simulations, we evaluate and analyze them in various ways.
Provisioning
Cite
Citations (67)
Provisioning
Data center
Single-chip Cloud Computer
Cite
Citations (7)
Provisioning
Cite
Citations (12)
Recently, a massive migration of enterprise applications to the cloud has been recorded in the IT world. One of the challenges of cloud computing is Quality-of-Service management, which includes the adoption of appropriate methods for allocating cloud-user applications to virtual resources, and virtual resources to the physical resources. The effective allocation of resources in cloud data centers is also one of the vital optimization problems in cloud computing, particularly when the cloud service infrastructures are built by lightweight computing devices. In this paper, we formulate and present the task allocation and virtual machine placement problems in a single cloud/fog computing environment, and propose a task allocation algorithmic solution and a Genetic Algorithm Based Virtual Machine Placement as solutions for the task allocation and virtual machine placement problem models. Finally, the experiments are carried out and the results show that the proposed solutions improve Quality-of-Service in the cloud/fog computing environment in terms of the allocation cost.
Resource Management
Cite
Citations (40)
Infrastructure-as-a-service (IaaS) clouds enable customers to allocate computing resources in a flexible manner to satisfy their needs, and pay only for the allocated resources. One of the challenges for IaaS customers is the correct provisioning of their resources. Many users end up under provisioning, hurting application performance, or over provisioning, paying for resources that are not really necessary. Memory is an essential resource for any computing system, and is frequently a performance-limiting factor in cloud environments. Our work uses monitoring to enable a cloud customer to determine if the memory allocated to his virtual machines is correctly provisioned, under provisioned, or over provisioned. Experimental results with the Xen platform demonstrate the effectiveness of the proposed approach.
Provisioning
Limiting
Cite
Citations (0)
Virtual machine (VM) technology applied to HPC has been shown to improve system throughput and turnaround time [2, 3]. VMs provide additional compute power to backlogged clusters by abstracting the software environment of compute resources that are available on other clusters. Borrowing and provisioning resources from other clusters requires some way to efficiently manage VMs across multiple independent hosts [4].
Provisioning
Virtual machining
Turnaround time
Resource Management
Live migration
Cite
Citations (0)
In PaaS, the issue of resource provisioning becomes more challenging because a great number of applications share and compete for resources simultaneously. PaaS platform should be able to maximize the resources utilization, while satisfying the performance requirements of all applications. However on-line request workload can be fluctuated during the run time of applications and static resource allocation may cause either under provisioning or over provisioning problem. In this paper, we propose an adaptive resource provisioning approach to dynamically allocate resources for applications according to the workload variation. In case of performance violation, our approach can make an efficient plan to keep application performance within a valid range.
Provisioning
Resource Management
Cite
Citations (1)
클라우드 환경은 여러 개의 컴퓨팅 자원들을 이용하는 분산 컴퓨팅 환경의 일종으로 가상머신을 이용 하여 작업을 처리한다. 클라우드 환경은 작업 요청에 따르는 부하분산과 빠른 작업 처리를 위한 프로비저닝 기술을 이용하여 가상머신의 상태에 따라 작업을 할당 한다. 하지만, 클라우드 환경의 작업 스케줄링을 위해서는 가상머신의 성능에 따르는 애매모호한 상태에 대한 가용성의 정의가 필요하다. 본 논문에서는 클라우드 환경의 프로비저닝 스케줄링을 위해 퍼지 로직 기반의 자원평가를 이용한 가상머신 프로비저닝 스케줄링(FVPRE: Fuzzy logic driven Virtual machine Provisioning scheduling using Resource Evaluation)을 제안한다. FVPRE는 각 가상머신의 정의하기 어려운 성능의 상태를 분석하여 자원 가용성에 대한 값을 구체화하여 정확한 자원의 가용성 평가를 통해 효율적인 프로비저닝 스케줄링이 가능하다. FVPRE는 클라우드 환경의 작업 처리에 대해 높은 처리율과 활용율을 보인다. Cloud computing is one of the distributed computing environments and utilizes several computing resources. Cloud environment uses a virtual machine to process a requested job. To balance a workload and process a job rapidly, cloud environment uses a provisioning technique and assigns a task with a status of virtual machine. However, a scheduling method for cloud computing requires a definition of virtual machine availabilities, which have an obscure meaning. In this paper, we propose Fuzzy logic driven Virtual machine Provisioning scheduling using Resource Evaluation(FVPRE). FVPRE analyzes a state of every virtual machine and actualizes a value of resource availability. Thus FVPRE provides an efficient provisioning scheduling with a precise evaluation of resource availability. FVPRE shows a high throughput and utilization for job processing on cloud environments.
Provisioning
Cite
Citations (7)
Virtual Computing Lab (VCL) environment at Computer communications lab enables students remote access to virtual environments, in which they fulfill their course assignments. It is comprised of 11 physical servers with VMware hardware virtualization that allows provisioning of virtual machines. Most of the time the private cloud in underutilizated, while it gets overutilizated during usage peaks at the end of semester or around deadlines for certain student assignments. In this thesis we suggest a solution for the overutilization problem in form of a hybrid cloud. Current private cloud could still be used as it was untill now, but we would have a possibility to expand available resources with public cloud during usage peaks. To address this issue we have developed a new VCL provisioning module for provisioning Amazon EC2 public cloud resources. Hybrid cloud solution expands capabilites of VCL environment during usage peaks and provides optimal resource utilization. With public cloud's »pay-as-you-go« model we only pay for resources (compute cycles, storage) that we actually use. With hybrid cloud we achieve better cost efficency, than we would have with investments into new physical infrastructure to meet the demand for resources during usage peaks. To really understand how hybrid cloud solution works, we discuss cloud computing, describe open-source VCL environment and EC2 public cloud. In the end we explain how to integrate hybrid cloud with connecting via public cloud's API interface and suggest hybrid cloud's architecture in case of Computer communications lab. The result of this thesis is a working proof-of-concept hybrid cloud solution for VCL environment.
Provisioning
Cite
Citations (0)
Education of cloud engineers will be crucial for the continued development of cloud technologies. We have developed an open-source software platform called edubase Cloud for education. The platform has multi-cloud architecture. In this paper, we discuss how edubase Cloud provides an alterable cloud platform and how effective it is for educating cloud engineers.
Cite
Citations (6)