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Fair design of plugin electric vehicles aggregator for v2g regulation
 Vehicular Technology, IEEE Transactions on
, 2012
"... Abstract—Plugin electric vehicles (PEVs) have recently attracted much attention due to their potential to reduce CO2 emissions and transportation costs and can be grouped into entities (aggregators) to provide ancillary services such as frequency regulation. In this paper, the application of agg ..."
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Abstract—Plugin electric vehicles (PEVs) have recently attracted much attention due to their potential to reduce CO2 emissions and transportation costs and can be grouped into entities (aggregators) to provide ancillary services such as frequency regulation. In this paper, the application of aggregators to frequency regulation by making fair use of their energy storage capacity is addressed. When the power grid requires frequency regulation service to the aggregator to adjust the grid frequency, the PEVs participating in providing the service can either draw energy (as it is usually done to charge the vehicle) or deliver energy to the grid by means of the vehicletogrid (V2G) interface. Under the general framework of optimizing the aggregator profit, different methods, such as statedependent allocation and the waterfilling approach, are proposed to achieve a final state of charge (SOC) of the PEVs that satisfy the desired fairness criteria once the regulation service has been carried out. Index Terms—Aggregator, fairness, frequency regulation service, plugin electric vehicle (PEV), state of charge (SOC), vehicle to grid (V2G).
Crosslayer design with adaptive modulation: Delay, rate, energy tradeoffs,” Accepted to Globecom
, 2008
"... Abstract — We present a crosslayer framework for optimizing the performance of wireless networks as measured by applications or upper layer protocols. The approach combines adaptive modulation with Network Utility Maximization. We extend the approach to find optimal source rates and transmitter powe ..."
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Abstract — We present a crosslayer framework for optimizing the performance of wireless networks as measured by applications or upper layer protocols. The approach combines adaptive modulation with Network Utility Maximization. We extend the approach to find optimal source rates and transmitter power and rate policies without explicit knowledge of the distribution of channel states. These optimal power and rate policies balance delay (backlog), transmission rate and energy to maximize network performance under constraints on average transmitter power and link buffer arrival and departure rates. Explicit policies are found for single links, and algorithmic methods presented to find optimal policies for complex interfering networks. I.
Completion Time Minimization and Robust Power Control in Wireless Packet Networks
, 2008
"... A wireless packet network is considered in which each user transmits a stream of packets to its destination. The transmit power of each user interferes with the transmission of all other users. A convex cost function of the completion times of the user packets are minimized by optimally allocating t ..."
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A wireless packet network is considered in which each user transmits a stream of packets to its destination. The transmit power of each user interferes with the transmission of all other users. A convex cost function of the completion times of the user packets are minimized by optimally allocating the users ’ transmission power subject to their respective power constraints. It is shown that, at all ranges of SINR, completion time minimization can be formulated as a convex optimization problem and hence can be efficiently solved. When channel knowledge is imperfect, robust power control is considered based on the channel fading distribution subject to outage probability constraints. The problem is shown to be convex when the fading distribution is logconcave in exponentiated channel power gains; e.g., when each user is under independent Rayleigh, Nakagami, or lognormal fading.
Optimal Crosslayer Wireless Control Policies using TD Learning
"... Abstract — We present an online crosslayer control technique to characterize and approximate optimal policies for wireless networks. Our approach combines network utility maximization and adaptive modulation over an infinite discretetime horizon using a class of performance measures we call time s ..."
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Abstract — We present an online crosslayer control technique to characterize and approximate optimal policies for wireless networks. Our approach combines network utility maximization and adaptive modulation over an infinite discretetime horizon using a class of performance measures we call time smoothed utility functions. We model the system as an averagecost Markov decision problem. Model approximations are used to find suitable basis functions for application of least squares TDlearning techniques. The approach yields network control policies that learn the underlying characteristics of the random wireless channel and that approximately optimize network performance. Acknowledgment Financial support from the National Science Foundation under CCF0729031 and ITMANET DARPA RK 200607284 is gratefully acknowledged. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of NSF or DARPA. I.
Adaptive modulation with smoothed flow utility
 EURASIP J. Wirel. Commun. Netw
"... Abstract We consider the problem of choosing the data flow rate on a wireless link with randomly varying channel gain, to optimally trade off average transmit power and the average utility of the smoothed data flow rate. The smoothing allows us to model the demands of an application that can tolera ..."
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Abstract We consider the problem of choosing the data flow rate on a wireless link with randomly varying channel gain, to optimally trade off average transmit power and the average utility of the smoothed data flow rate. The smoothing allows us to model the demands of an application that can tolerate variations in flow over a certain time interval; we will see that this smoothing leads to a substantially different optimal data flow rate policy than without smoothing. We pose the problem as a convex stochastic control problem. For the case of a single flow, the optimal data flow rate policy can be numerically computed using stochastic dynamic programming. For the case of multiple flows on a single link, we propose an approximate dynamic programming approach to obtain suboptimal data flow rate policies. We illustrate, through numerical examples, that nearly optimal performance can be obtained with these approximate policies.
Optimal Data Transmission and Channel Code Rate Allocation in Multipath Wireless Networks
"... Abstract—Wireless links are often unreliable and prone to transmission error due to varying channel conditions. These can degrade the performance in wireless networks, particularly for applications with tight qualityofservice requirements. A common remedy is to use channel coding where the transmi ..."
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Abstract—Wireless links are often unreliable and prone to transmission error due to varying channel conditions. These can degrade the performance in wireless networks, particularly for applications with tight qualityofservice requirements. A common remedy is to use channel coding where the transmitter node adds redundant bits to the transmitted packets in order to reduce the error probability at the receiver. However, this perlink solution can compromise the effective link data rate, leading to undesired endtoend performance. In this paper, we show that this latter shortcoming can be mitigated if the endtoend transmission rates and channel code rates are selected properly over multiple routing paths. We formulate the joint channel coding and endtoend data rate allocation problem in multipath wireless networks as a network throughput maximization problem, which is nonconvex. We tackle the nonconvexity by using function approximation and iterative techniques from signomial programming. Simulation results confirm that by using channel coding jointly with multipath routing, the endtoend network performance can be improved significantly. I.
EURASIP Journal on Wireless Communications and Networking
, 2012
"... PDF corresponds to the article as it appeared upon acceptance. Fully formatted PDF and full text (HTML) versions will be made available soon. Adaptive access and rate control of CSMA for energy, rate, and delay optimization ..."
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PDF corresponds to the article as it appeared upon acceptance. Fully formatted PDF and full text (HTML) versions will be made available soon. Adaptive access and rate control of CSMA for energy, rate, and delay optimization
Optimizing Adaptive Modulation in Wireless Networks via MultiPeriod Network Utility Maximization
"... Abstract — We present a crosslayer technique to find and characterize optimal control policies for wireless networks operating at different time scales at the upper layer and physical layer. The technique can also be directly applied to networks carrying traffic with different time dependencies such ..."
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Abstract — We present a crosslayer technique to find and characterize optimal control policies for wireless networks operating at different time scales at the upper layer and physical layer. The technique can also be directly applied to networks carrying traffic with different time dependencies such as data or video. Our approach combines network utility maximization and adaptive modulation over an infinite discrete time horizon using a class of performance measures we call time smoothed utility functions. We describe the properties of optimal physical layer power and link rate policies and characterize optimal upper layer policies, which determine when packets should be injected into the network. We also characterize the behavior of optimal policies as different system parameters are used. I.
Adaptive Modulation in Wireless Networks with Smoothed Flow Utility
"... Abstract—We investigate flow rate optimization on a wireless link with randomly varying channel gain using techniques from adaptive modulation and network utility maximization. We consider the problem of choosing the data flow rate to optimally trade off average transmit power and the average utilit ..."
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Abstract—We investigate flow rate optimization on a wireless link with randomly varying channel gain using techniques from adaptive modulation and network utility maximization. We consider the problem of choosing the data flow rate to optimally trade off average transmit power and the average utility of the smoothed data flow rate. The smoothing allows us to model the demands of an application that can tolerate variations in flow over a certain time interval; we will see that this smoothing leads to a substantially different optimal data flow rate policy than without smoothing. We pose the problem as a convex stochastic control problem. For the case of a single flow, the optimal data flow rate policy can be numerically computed using stochastic dynamic programming. For the case of multiple data flows on a single link, we propose an approximate dynamic programming approach to obtain suboptimal data flow rate policies. We illustrate, through numerical examples, that these approximate policies perform very well. I.