9529180
Joint Power and Channel Resource Allocation for F/TDMA Decode and Forward Relay Networks
In this paper, we study the joint power and channel resource allocation problem for a multiuser F/TDMA decode-and-forward (DF) relay network under per-node power constraints and a total channel resource constraint. Our goal is to maximize the total throughput achieved by the systems. To that end, we formulate a joint power and channel resource allocation problem. We develop an iterative optimization algorithm to solve this problem, whose convergence and optimality are guaranteed. Due to the per-node power constraints, more than one relay node may be needed for a single data stream. Our solution also provides a way of finding the optimal relays among the assisting relay nodes.
2080159
The Impacts of Radio Channels and Node Mobility on Link Statistics in Mobile Ad Hoc Networks
Understanding link statistics in mobile ad hoc networks (MANETs) is essential to design adaptive routing protocols and achieve desired network performance. While much attention has been given to the node mobility impacts, little has been done to investigate the influence of dynamic channel fadings and the joint effects of the interactions among radio channels, transmission range, node mobility and node-pair distance on link statistics. In this paper, we investigate the link stability and availability by using a distance transition probability matrix of a relative distance between two nodes. Our analysis takes the node effective transmission range Re into account. The relative node movement is based on the Semi-Markov Smooth (SMS) mobility model [1] which captures the smooth node speed (V) transition and the radio channel variations in a small time- scale. We show that the PDF of link lifetime in MANETs can be effectively approximated by the exponential distribution characterized by the parameter V/Re. Moreover, we And that the impacting factors on residual link lifetime are in the decreasing order of node speed, transmission range, node-pair distance. The analytical results are validated by extensive simulations.
3677775
Relaying Schemes for MIMO Broadcast Channels: Coexistence of Direct-Link and Relay-Link Users
The combination of relay and Multiple-Input Multiple-Output (MIMO) techniques can significantly benefit the signal transmission in cellular networks. In this work, we propose a novel relaying scheme for the relay assisted MIMO broadcast channel including user classification and precoding. The users are firstly classified as Direct Link (DL) users and Relay Link (RL) users according to their channel conditions. After classification, both DL and RL users may coexist in the system, and Zero-Forcing (ZF) precoding is employed at both the BS and the relay for interference cancellation. Analysis and simulation results show that the proposed relaying scheme can effectively combat the large scale fading of the channels and provide significant performance gain compared with the conventional MIMO relaying schemes without user classification.
27105771
A Novel Evaluation Method for the Downlink Capacity of Distributed Antenna Systems
This letter focuses on the simplified capacity evaluation for the downlink of a distributed antenna system (DAS) with random antenna layout. Based on system scale-up, we derive a good approximation of the downlink capacity by developing the results from random matrix theory. We also propose an iterative method to calculate the unknown parameters in the approximated expression of the downlink capacity. The approximation is illustrated to be quite accurate and the iterative method is shown to be quite efficient by Monte Carlo simulations.
12272080
Linear Precoding for V-BLAST Systems in the Presence of Fading Correlations
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.
122893722
Iterative Turbo Channel Estimation for OFDM System over Rapid Dispersive Fading Channel
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.
9640803
Distributed File System Virtualization Techniques Supporting On-Demand Virtual Machine Environments for Grid Computing
This paper presents a data management solution which allows fast Virtual Machine (VM) instantiation and efficient run-time execution to support VMs as execution environments in Grid computing. It is based on novel distributed file system virtualization techniques and is unique in that: (1) it provides on-demand cross-domain access to VM state for unmodified VM monitors; (2) it enables private file system channels for VM instantiation by secure tunneling and session-key based authentication; (3) it supports user-level and write-back disk caches, per-application caching policies and middleware-driven consistency models; and (4) it leverages application-specific meta-data associated with files to expedite data transfers. The paper reports on its performance in wide-area setups using VMware-based VMs. Results show that the solution delivers performance over 30% better than native NFS and with warm caches it can bring the application-perceived overheads below 10% compared to a local-disk setup. The solution also allows a VM with 1.6 GB virtual disk and 320 MB virtual memory to be cloned within 160 seconds for the first clone and within 25 seconds for subsequent clones.
6728240
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.
1774593
Markovian mixture face recognition with discriminative face alignment
A typical automatic face recognition system is composed of three parts: face detection, face alignment and face recognition. Conventionally, these three parts are processed in a bottom-up manner: face detection is performed first, then the results are passed to face alignment, and finally to face recognition. The bottom-up approach is one extreme of vision approaches. The other extreme approach is top-down. In this paper, we proposed a Markovian stochastic mixture approach for combining bottom-up and top-down face recognition: face recognition is performed from the results of face alignment in a bottom-up way, and face alignment is performed based on the results of face recognition in a top-down way. By modeling the mixture face recognition as a stochastic process, the recognized person is decided probabilistically according to the probability distribution coming from the stochastic face recognition, and the recognition problem becomes that ldquowho the most probable person is when the stochastic process of face recognition goes on for an infinite long durationrdquo. This problem is solved with the theory of Markov chains by properly modeling the stochastic process of face recognition as a Markov chain. As conventional face alignment is not suitable for this mixture approach, discriminative face alignment is proposed. And we also prove that the Markovian mixture face recognition results only depend on discriminative face alignment, not on conventional face alignment. Our approach can surprisingly outperform the face recognition performance with manual face localization, which is demonstrated by extensive experiments.
16153431
On the Use of Fuzzy Modeling in Virtualized Data Center Management
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.
6353584
A CoS-enabled Request Scheduling Policy
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.