Autonomic resource management in virtualized data centers using fuzzy logic-based approaches
Data centers, as resource providers, are expected to deliver on performance guarantees while optimizing resource utilization to reduce cost. Virtualization techniques provide the opportunity of consolidating multiple separately managed containers of virtual resources on underutilized physical servers. A key challenge that comes with virtualization is the simultaneous on-demand provisioning of shared physical resources to virtual containers and the management of their capacities to meet service-quality targets at the least cost. This paper proposes a two-level resource management system to dynamically allocate resources to individual virtual containers. It uses local controllers at the virtual-container level and a global controller at the resource-pool level. An important advantage of this two-level control architecture is that it allows independent controller designs for separately optimizing the performance of applications and the use of resources. Autonomic resource allocation is realized through the interaction of the local and global controllers. A novelty of the local controller designs is their use of fuzzy logic-based approaches to efficiently and robustly deal with the complexity and uncertainties of dynamically changing workloads and resource usage. The global controller determines the resource allocation based on a proposed profit model, with the goal of maximizing the total profit of the data center. Experimental results obtained through a prototype implementation demonstrate that, for the scenarios under consideration, the proposed resource management system can significantly reduce resource consumption while still achieving application performance targets.

title: Towards Autonomic Grid Data Management with Virtualized Distributed File Systems
abstract: Grid data management is a challenging task because of the heterogeneous, dynamic and largescale nature of Grid environments. This paper proposes an autonomic Grid data management architecture based on virtualized distributed file systems and WSRF-compliant management services. Autonomic functions are integrated into the services to provide self-managing control over the different entities of Grid-wide file system sessions in accordance with high-level objectives and operate together to automatically achieve the desired data provisioning behaviors. Important autonomic features are designed and implemented in this system in the aspects of cache configuration, data replication and session redirection. Experiments with a prototype demonstrate that this architecture can automatically and substantially improve the performance and reliability of Grid data access.

title: Cooperative Autonomic Management in Dynamic Distributed Systems
abstract: The centralized management of large distributed systems is often impractical, particularly when the both the topology and status of the system change dynamically. This paper proposes an approach to application-centric self-management in large distributed systems consisting of a collection of autonomic components that join and leave the system dynamically. Cooperative autonomic components self-organize into a dynamically created overlay network. Through local information sharing with neighbors, each component gains access to global information as needed for optimizing performance of applications. The approach has been validated and evaluated by developing a decentralized autonomic system consisting of multiple autonomic application managers previously developed for the In-VIGO grid-computing system. Using analytical results from complex random network and measurements done in a prototype system, we demonstrate the robustness, self-organization and adaptability of our approach, both theoretically and experimentally.

title: On the Use of Virtualization and Service Technologies to Enable Grid-Computing
abstract: The In-VIGO approach to Grid-computing relies on the dynamic establishment of virtual grids on which application services are instantiated. In-VIGO was conceived to enable computational science to take place In Virtual Information Grid Organizations. Having its first version deployed on July of 2003, In-VIGO middleware is currently used by scientists from various disciplines, a noteworthy example being the computational nanoelectronics research community (http://www.nanohub.org). All components of an In-VIGO-generated virtual grid – machines, networks, applications and data – are themselves virtual and services are provided for their dynamic creation. This article reviews the In-VIGO approach to Grid-computing and overviews the associated middleware techniques and architectures for virtualizing Grid components, using services for creation of virtual grids and automatically Grid-enabling unmodified applications. The In-VIGO approach to the implementation of virtual networks and virtual application services are discussed as examples of Grid-motivated approaches to resource virtualization and Web-service creation.

title: Supporting application-tailored grid file system sessions with WSRF-based services
abstract: This paper presents novel service-based grid data management middleware that leverages standards defined by WSRF specifications to create and manage dynamic grid file system sessions. A unique aspect of the service is that the sessions it creates can be customized to address application data transfer needs. Application-tailored configurations enable selection of both performance-related features (block-based partial file transfers and/or whole-file transfers, cache parameters and consistency models) and reliability features (file system copy-on-write checkpointing to aid recovery of client-side failures; replication, autonomous failure detection and data access redirection for server-side failures). These enhancements, in addition to cross-domain user identity mapping and encrypted communication, are implemented via user level proxies managed by the service, requiring no changes to existing kernels. Sessions established using the service is mounted as distributed file systems and can be used transparently by unmodified binary applications. The paper analyzes the use of the service to support virtual machine based grid systems and workflow execution, and also reports on the performance and reliability of service managed wide-area file system sessions with experiments based on scientific applications (NanoMOS/Matlab, CHID, GAUSS and SPECseis).

title: On the Use of Fuzzy Modeling in Virtualized Data Center Management
abstract: One of the most important goals of data-center management is to reduce cost through efficient use of resources. Virtualization techniques provide the opportunity of carving individual physical servers into multiple virtual containers that can be run and managed separately. A key challenge that comes with virtualization is the simultaneous on-demand provisioning of shared resources to virtual containers and the management of their capacities to meet service quality targets at the least cost. This paper proposes a two-level resource management system with local controllers at the virtual-container level and a global controller at the resource-pool level. Autonomic resource allocation is realized through the interaction of the local and global controllers. A novelty of the controller designs is their use of fuzzy logic to efficiently and robustly deal with the complexity of the virtualized data center and the uncertainties of the dynamically changing workloads. Experimental results obtained through a prototype implementation demonstrate that, for the scenarios under consideration, the proposed resource management system can significantly reduce resource consumption while still achieving application performance targets.

title: A CoS-enabled Request Scheduling Policy
abstract: As a lightweight SLA between service providers and consumers, class of service (CoS) can avoid the runtime overhead brought by multiple negotiation of service agreements. This is especially important in grid environment where lots of transient services exist. We bring CoS into grid environment and propose a QoS-enabled framework named CQEF for grid service. In this paper, we present a CoSenabled request scheduling policy for CoS deployment in CQEF. According to this policy, incoming requests can be identified and classified based on the CoS information attached to them and subsequently be assigned to different waiting queues with different priorities. Besides, queuing scheduling algorithm is used to achieve the CoS enabling purpose. A prototype has been developed over the Globus platform. The test results show that, by using this policy, service providers are able to offer differentiated services for different CoS and QoS of premium CoSs will be guaranteed preferentially.

title: Robust Transmission for Multiuser MIMO Downlink Systems with Imperfect CSIT
abstract: The performance of multiuser MIMO (MU-MIMO) downlink systems with preceding and decoding method by minimizing the total mean square error (TMSE) of all data streams of all users (T-MMSE) depends on the accuracy of the channel state information (CSI) available at the transmitter (CSIT). In this paper, a robust transmission scheme is proposed to suppress the interferences among data streams and users caused by imperfect CSIT. At the transmitter, the precoders are obtained through an iterative procedure by minimizing the expectation of the TMSE of all data streams of all users conditioned on the estimated CSI under a total transmit power constraint. At each user, a linear decoder is calculated based on the minimum mean square error (MMSE) criteria according to the realtime CSI. To fulfill it, a new pilot-sending architecture is introduced. Numerical results demonstrate that the proposed scheme is robust not only to the channel uncertainty at the transmitter but also to the channel uncertainty at each user, and can effectively improve the system performance.

title: Iterative Turbo Channel Estimation for OFDM System over Rapid Dispersive Fading Channel
abstract: Coherent OFDM detection requires accurate channel state information (CSI). Mobile radio channels are both time and frequency dispersive, especially at high vehicular speeds, which makes channel estimation a challenging problem in system design. Conventional preamble-based and pilot-aided channel estimation require numerous reference signals, which significantly compromises the system throughput. This paper proposes a novel low complexity iterative turbo channel estimation technique which makes use of preamble, pilots and soft decoded data information in an iterative fashion to improve the system performance over the time and frequency selective fading channel while maintaining the system throughput. The numerical and analytical results show that the proposed technique can approach the performance of systems with perfect CSI with much fewer preamble and pilots symbols compared to existing channel estimation methods.

title: Linear Precoding for V-BLAST Systems in the Presence of Fading Correlations
abstract: This letter proposed a linear precoding scheme for the V-BLAST system that requires only knowledge of the statistical CSI; the transmitter does not need the instantaneous CSI. Power allocation on the eigenmodes of the transmit correlation matrix is one way to minimize bit error rate (BER). Simulation results show that the proposed precoding V-BLAST system provides a significant reduction in the BER compared with the conventional V-BLAST systems.

title: Capacity bound of mimo systems with mpsk modulation and superimposed pilots
abstract: The enormous capacity potential of multiple-input multiple-output (MIMO) is based on some unrealistic assumptions, such as the complete channel state information (CCSI) at the receiver and Gaussian distributed data. In this paper, in frequency-flat Rayleigh fading environment, we investigate the ergodic capacity of MIMO systems with M-ary phase-shift keying (MPSK) modulation and superimposed pilots for channel estimation. With linear minimum mean square error (LMMSE) channel estimation, the optimal pilots design is presented. For the mathematical tractability, we also derive an easy-computing closed-form lower bound of the channel capacity. Furthermore, the optimal power allocation between the data and pilots is investigated by numerical optimization. It is shown that more power should be devoted to the data in low SNR environments and to the pilots in high SNR environments.