Flexible Resource Provisioning Research Articles

Truthful VNFI Procurement Mechanisms With Flexible Resource Provisioning in NFV Markets

With the rapid development of network function virtualization (NFV), more and more enterprises and operators are seeking network service provisioning via service chains of virtual network functions (VNFs), instead of depending on proprietary hardware appliances. Following this trend, an NFV market is emerging, where users can procure different VNF instances (VNFIs) and their combinations from multiple network service providers (NSPs) in a pay-as-you-go way. In such a procurement process, how to guarantee truthfulness while enabling flexible resource provisioning in form of VNFIs is a significant challenge. In this paper, we propose a truthful reverse combinatorial auction-based mechanism to solve the combinatorial VNFI procurement problem. To support flexible resource provisioning, this mechanism allows NSPs to be multi-minded, and determine the provisioning VNFIs according to the auction results. Specifically, we design a heuristic algorithm to determine the winning bids in polynomial time. Furthermore, we devise a critical-payment-based pricing algorithm to induce NSPs to disclose their real costs, aiming to achieve truthfulness. Rigorous theoretical analysis shows the proposed mechanism can guarantee truthfulness, individual rationality and computational efficiency. Simulation results also verify the effectiveness and efficiency of the proposed mechanism.

Flexible resource provisioning of polarization independent coherent PONs based on non-orthogonal multiple access and multiCAP modulation

A combined non-orthogonal multiple access (NOMA) and multiband carrierless amplitude and phase modulation (multiCAP) scheme is proposed for flexible resource provisioning in coherent passive optical networks (PONs). While the proposed combination increases the data-rate and the number of users through the inclusion of NOMA and multiCAP, the coherent reception increases the range and splitting factor of the network through optical power budget enhancement. The proposed system is experimentally evaluated providing a 20 Gb/s aggregated data-rate per wavelength with 10G optoelectronics and applied in two main PON scenarios with four spectral configurations from full-band CAP to four-band multiCAP. The first PON scenario consists of an existing PON that the network operator requires to increase the number of users; NOMA with full-band CAP or multiCAP can be introduced replacing one or more users of the existing PON by one or several new sub-networks and multiplexing the sub-networks by NOMA. In the other PON scenario, several PONs can be nested sharing an initial splitter and achieving a larger number of users by the combination of NOMA and multiCAP. The proposed techniques are fully compatible with other multiplexing techniques such as dense wavelength division multiplexing, which should be considered to achieve higher numbers of users.

Nonorthogonal Multiple Access and Carrierless Amplitude Phase Modulation for Flexible Multiuser Provisioning in 5G Mobile Networks

In this paper, a combined nonorthogonal multiple access (NOMA) and multiband carrierless amplitude phase modulation (multiCAP) scheme is proposed for capacity enhancement of and flexible resource provisioning in 5G mobile networks. The proposed scheme is experimentally evaluated over a W-band millimeter wave radio-over fiber system. The evaluated NOMA-CAP system consists of six 1.25-GHz multiCAP bands and two NOMA levels with quadrature phase-shift keying and can provide an aggregated transmission rate of 30 Gbit/s. The proposed system can dynamically adapt to different user densities and data rate requirements. Bit error rate performance is evaluated in two scenarios: a low user density scenario where the system capacity is evenly split between two users and a high user density scenario where NOMA and multiCAP are combined to serve up to 12 users with an assigned data rate of 2.5 Gbit/s each. The proposed system demonstrates how NOMA-CAP allows flexible resource provisioning and can adapt data rates depending on user density and requirements.

Optimized Speculative Execution to Improve Performance of MapReduce Jobs on Virtualized Computing Environment

Recently, virtualization has become more and more important in the cloud computing to support efficient flexible resource provisioning. However, the performance interference among virtual machines may affect the efficiency of the resource provisioning. In a virtualized environment, where multiple MapReduce applications are deployed, the performance interference can also affect the performance of the Map and Reduce tasks resulting in the performance degradation of the MapReduce jobs. Then, in order to ensure the performance of the MapReduce jobs, a framework for scheduling the MapReduce jobs with the consideration of the performance interference among the virtual machines is proposed. The core of the framework is to identify the straggler tasks in a job and back up these tasks to make the backed up one overtake the original tasks in order to reduce the overall response time of the job. Then, to identify the straggler task, this paper uses a method for predicting the performance interference degree. A method for scheduling the backing-up tasks is presented. To verify the effectiveness of our framework, a set of experiments are done. The experiments show that the proposed framework has better performance in the virtual cluster compared with the current speculative execution framework.

MapReduce scheduler by characterizing performance interference

Recently, virtualization has become more and more important in the cloud computing to support efficient flexible resource provisioning. However, performance interference among virtual machines (VMs) has become a challenge which may affect the effectiveness of resource provisioning. In a virtual cluster which runs the MapReduce applications, the performance interference can also affect the performance of the Map and Reduce tasks and thus cause a performance degradation of the MapReduce job. Accordingly, this paper presents a MapReduce scheduling framework to mitigate this performance degradation caused by the performance interference. The framework includes a performance interference prediction module and an interference aware scheduling algorithm. To verify its effectiveness, we have done a set of experiments on a 24-node virtual MapReduce cluster. The experiments illustrate that the proposed framework can achieve a performance improvement in the virtualized environment compared with other MapReduce schedulers.

Context-Aware Mobile Cloud Computing and Its Challenges

Cloud computing is gaining popularity due to virtually unlimited resources, low capital cost, ease of adoption, flexible resource provisioning, and high scalability. Considering these benefits, researchers envision the usage of cloud computing for mobile devices to overcome the ever-increasing computational and energy demands of smartphone applications. However, this requires specialized context-ware application development models that can facilitate the development of cloud-enabled applications capable of making context-aware computation offloading decisions. This article provides an overview of mobile cloud computing technology, focusing on its context-awareness aspects and challenges.

An architecture to stimulate behavioral development of academic cloud users

Academic cloud infrastructures are constructed and maintained so they minimally constrain their users. Since they are free and do not limit usage patterns, academics developed such behavior that jeopardizes fair and flexible resource provisioning. For efficiency, related work either explicitly limits user access to resources, or introduce automatic rationing techniques. Surprisingly, the root cause (i.e., the user behavior) is disregarded by these approaches. This article compares academic cloud user behavior to its commercial equivalent. We deduce, that academics should behave like commercial cloud users to relieve resource provisioning. To encourage commercial like behavior, we propose an architectural extension to existing academic infrastructure clouds. First, every user's energy consumption and efficiency is monitored. Then, energy efficiency based leader boards are used to ignite competition between academics and reveal their worst practices. Leader boards are not sufficient to completely change user behavior. Thus, we introduce engaging options that encourage academics to delay resource requests and prefer resources more suitable for the infrastructure's internal provisioning. Finally, we evaluate our extensions via a simulation using real life academic resource request traces. We show a potential resource utilization reduction (by the factor of at most 2.6) while maintaining the unlimited nature of academic clouds.

Hybrid resource provisioning for clouds

Flexible resource provisioning, the assignment of virtual machines (VMs) to physical machine, is a key requirement for cloud computing. To achieve "provisioning elasticity", the cloud needs to manage its available resources on demand. A-priori, static, VM provisioning introduces no runtime overhead but fails to deal with unanticipated changes in resource demands. Dynamic provisioning addresses this problem but introduces runtime overhead. To reduce VM management overhead so more useful work can be done and to also avoid sub-optimal provisioning we propose a hybrid approach that combines static and dynamic provisioning. The idea is to adapt a good initial static placement of VMs in response to evolving load characteristics, using live migration, as long as the overhead of doing so is low and the effectiveness is high. When this is no longer so, we trigger a revised static placement. (Thus, we are essentially applying local multi-objective optimization to tune a global optimization with reduced overhead.) This approach requires a complicated migration decision algorithm based on current and predicted:future workloads, power consumptions and memory usage in the host machines as well as network burst characteristics for the various possible VM multiplexings (combinations of VMs on a host). A further challenge is to identify those characteristics of the dynamic provisioning that should trigger static re-provisioning.

The necessity of legally compliant data management in European cloud architectures

Taking advantage of flexible resource provisions enabled by Cloud Computing, many businesses have recently migrated their IT applications and data to the Cloud, allowing them to respond to new demands and requests from customers. However, Cloud Computing also moves functions and responsibilities away from local ownership and management to a third-party provided service, and brings with it a set of associated legal issues, such as data protection, licensing, intellectual property rights and the need to comply to necessary regulation. In this paper we evaluate commonly-observed Cloud Computing use cases against the law applying to Cloud Computing to find where legal problems may arise. We derive a general architecture for Clouds and use it to illustrate common Cloud Computing usage patterns. The use cases are assessed against evaluation criteria derived from the relevant Cloud Computing law for the data processing of end-user details and materials, including roles and responsibilities necessary for legal compliance. The Data Protection Directive of the European Union has been used in this evaluation, as it is a commonly accepted and influential directive in the field of data processing legislation.

Dynamic resource management using virtual machine migrations

Virtualization is a key concept in enabling the "computing-as-a-service" vision of cloud-based solutions. Virtual machine related features such as flexible resource provisioning, and isolation and migration of machine state have improved efficiency of resource usage and dynamic resource provisioning capabilities. Live virtual machine migration transfers "state" of a virtual machine from one physical machine to another, and can mitigate overload conditions and enables uninterrupted maintenance activities. The focus of this article is to present the details of virtual machine migration techniques and their usage toward dynamic resource management in virtualized environments. We outline the components required to use virtual machine migration for dynamic resource management in the virtualized cloud environment. We present categorization and details of migration heuristics aimed at reducing server sprawl, minimizing power consumption, balancing load across physical machines, and so on. We conclude with a discussion of open research problems in the area.