1,720,994 research outputs found
Jointly Optimal Congestion Control, Network Coding and Power Control for QoS Multicast over DiffServ MAI-affected Wireless Networks
No full textJoint control of bandwidth and playout-delay for streaming traffic over faded links (Best Paper Award)
No full textIn this paper we develop an optimized control strategy for the connection bandwidth maximization over a time varying wireless channel, by jointly controlling the adaptive source rate and the client/playout buffering policy with constraints on the maximum connection bandwidth allowed at the Application (APP) layer, the queue-capacities available at the Data-Link (DL) layer and the average and peak transmit energies sustained by the Physical (PHY) layer. The main feature of the approach we follow lies in the fact that the maximization of the throughput is performed with respect to the channel state information as well as the occupancies of the transmitter and receiver buffers, taking into account also for the need to optimize the playout buffer service so to reduce the stream-jitter provided to the final user. The resulting optimal controllers operate in a Cross-Layer (CL) fashion that involves the APP, DL and PHY layers of the underlying protocol stack. Via a parameter-depending optimization we are able to handle the jitter of the stream provided to the final user without significant impact on the bandwidth performances. The carried out numerical tests give insight into the tradeoff among average throughput, delay and jitter attained by the optimized controllers. ©2010 IEEE
Energy-Efficient Adaptive Resource Management for Real-Time Vehicular Cloud Services
No full textProviding real-time cloud services to Vehicular Clients (VCs) must cope with delay and delay-jitter issues. Fog computing is an emerging paradigm that aims at distributing small-size self-powered data centers (e.g., Fog nodes) between remote Clouds and VCs, in order to deliver data-dissemination real-time services to the connected VCs. Motivated by these considerations, in this paper, we propose and test an energy-efficient adaptive resource scheduler for Networked Fog Centers (NetFCs). They operate at the edge of the vehicular network and are connected to the served VCs through Infrastructure-to-Vehicular (I2V) TCP/IP-based single-hop mobile links. The goal is to exploit the locally measured states of the TCP/IP connections, in order to maximize the overall communication-plus-computing energy efficiency, while meeting the application-induced hard QoS requirements on the minimum transmission rates, maximum delays and delay-jitters. The resulting energy-efficient scheduler jointly performs: (i) admission control of the input traffic to be processed by the NetFCs; (ii) minimum-energy dispatching of the admitted traffic; (iii) adaptive reconfiguration and consolidation of the Virtual Machines (VMs) hosted by the NetFCs; and, (iv) adaptive control of the traffic injected into the TCP/IP mobile connections. The salient features of the proposed scheduler are that: (i) it is adaptive and admits distributed and scalable implementation; and, (ii) it is capable to provide hard QoS guarantees, in terms of minimum/maximum instantaneous rates of the traffic delivered to the vehicular clients, instantaneous rate-jitters and total processing delays. Actual performance of the proposed scheduler in the presence of: (i) client mobility; (ii) wireless fading; and, (iii) reconfiguration and consolidation costs of the underlying NetFCs, is numerically tested and compared against the corresponding ones of some state-of-the-art schedulers, under both synthetically generated and measured real-world workload traces
Optimized joint bandwidth and playout control for streaming-traffic over wireless-channels
No full textOn the information rate of multiantenna systems with isotropic unitary input signals in the presence of channel estimation errors
No full textThis correspondence focuses on the evaluation of the information rate conveyed by block-faded pilot-based multiple-input multiple-output (MIMO) systems when the input signals are isotropic-unitary (IU)-distributed and imperfect (e.g., error-affected) channel estimates are available at receiver and transmitter. Main contributions may be so summarized. First, we develop closed-form analytical formulas for the computation of the ergodic information rate conveyed by the considered MIMO systems equipped with a large number of transmit antennas. Second, we point out that no rate gain may be accomplished by shaping the transmitted streams on the basis of (possibly partial) channel state information (CSI) so that the feedback link becomes, indeed, useless when the system is block faded and fed by IU-distributed input signals. Third, we compare the obtained information rate with those supported by the corresponding MIMO systems fed by Gaussian-distributed input signals [11] for various values of the mean-squared error (MSE) impairing the available MIMO channel estimates. So doing, we gain some insight about the operating conditions where actual implementation of a feedback link may be justified by the resulting improvement in the rate conveyed by the overall system. © 2007 IEEE
Energy-efficient adaptive networked datacenters for the QoS support of real-time applications
No full textIn this paper, we develop the optimal minimum-energy scheduler for the adaptive joint allocation of the task sizes, computing rates, communication rates and communication powers in virtualized networked data centers (VNetDCs) that operate under hard per-job delay-constraints. The considered VNetDC platform works at the Middleware layer of the underlying protocol stack. It aims at supporting real-time stream service (such as, for example, the emerging big data stream computing (BDSC) services) by adopting the software-as-a-service (SaaS) computing model. Our objective is the minimization of the overall computing-plus-communication energy consumption. The main new contributions of the paper are the following ones: (i) the computing-plus-communication resources are jointly allotted in an adaptive fashion by accounting in real-time for both the (possibly, unpredictable) time fluctuations of the offered workload and the reconfiguration costs of the considered VNetDC platform; (ii) hard per-job delay-constraints on the overall allowed computing-plus-communication latencies are enforced; and, (iii) to deal with the inherently nonconvex nature of the resulting resource optimization problem, a novel solving approach is developed, that leads to the lossless decomposition of the afforded problem into the cascade of two simpler sub-problems. The sensitivity of the energy consumption of the proposed scheduler on the allowed processing latency, as well as the peak-to-mean ratio (PMR) and the correlation coefficient (i.e., the smoothness) of the offered workload is numerically tested under both synthetically generated and real-world workload traces. Finally, as an index of the attained energy efficiency, we compare the energy consumption of the proposed scheduler with the corresponding ones of some benchmark static, hybrid and sequential schedulers and numerically evaluate the resulting percent energy gaps
Optimal Energy-Scheduling for Rate-Guaranteed Download over Faded Multi-Channel Networks
No full textDistributed and adaptive resource management in Cloud-assisted Cognitive Radio Vehicular Networks with hard reliability guarantees
No full textIn this contribution, we design and test the performance of a distributed and adaptive resource management controller, which allows the optimal exploitation of Cognitive Radio and soft-input/soft-output data fusion in Vehicular Access Networks. The ultimate goal is to allow energy and computing-limited car smartphones to utilize the available Vehicular-to-Infrastructure WiFi connections for performing traffic offloading towards local or remote Clouds by opportunistically acceding to a spectral-limited wireless backbone built up by multiple Roadside Units. For this purpose, we recast the afforded resource management problem into a suitable constrained stochastic Network Utility Maximization problem. Afterwards, we derive the optimal cognitive resource management controller, which dynamically allocates the access time-windows at the serving Roadside Units (i.e., the access points) together with the access rates and traffic flows at the served Vehicular Clients (i.e., the secondary users of the wireless backbone). Interestingly, the developed controller provides hard reliability guarantees to the Cloud Service Provider (i.e., the primary user of the wireless backbone) on a per-slot basis. Furthermore, it is also capable to self-acquire context information about the currently available bandwidth-energy resources, so as to quickly adapt to the mobility-induced abrupt changes of the state of the vehicular network, even in the presence of fadings, imperfect context information and intermittent Vehicular-to-Infrastructure connectivity. Finally, we develop a related access protocol, which supports a fully distributed and scalable implementation of the optimal controller
On the Information Rate of Multi-Antenna Systems with Isotropic Unitary input signals in the presence of Channel Estimation Errors
No full textThis correspondence focuses on the evaluation of the information rate conveyed by block-faded pilot-based multiple-input multipleoutput (MIMO) systems when the input signals are isotropic–unitary (IU)- distributed and imperfect (e.g., error-affected) channel estimates are available at receiver and transmitter. Main contributions may be so summarized. First, we develop closed-form analytical formulas for the computation of the ergodic information rate conveyed by the considered MIMO systems equipped with a large number of transmit antennas. Second, we point out that no rate gain may be accomplished by shaping the transmitted streams on the basis of (possibly partial) channel state information (CSI) so that the feedback link becomes, indeed, useless when the system is block faded and fed by IU-distributed input signals. Third, we compare the obtained information rate with those supported by the corresponding MIMO systems fed by Gaussian-distributed input signals [11] for various values of the mean-squared error (MSE) impairing the available MIMO channel estimates. So doing, we gain some insight about the operating conditions where actual implementation of a feedback link may be justified by the resulting improvement in the rate conveyed by the overall system
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