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Resource allocation and crosslayer control in wireless networks
 Foundations and Trends in Networking
, 2006
"... Information flow in a telecommunication network is accomplished through the interaction of mechanisms at various design layers with the end goal of supporting the information exchange needs of the applications. In wireless networks in particular, the different layers interact in a nontrivial manner ..."
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Cited by 273 (60 self)
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Information flow in a telecommunication network is accomplished through the interaction of mechanisms at various design layers with the end goal of supporting the information exchange needs of the applications. In wireless networks in particular, the different layers interact in a nontrivial manner in order to support information transfer. In this text we will present abstract models that capture the crosslayer interaction from the physical to transport layer in wireless network architectures including cellular, adhoc and sensor networks as well as hybrid wirelesswireline. The model allows for arbitrary network topologies as well as traffic forwarding modes, including datagrams and virtual circuits. Furthermore the time varying nature of a wireless network, due either to fading channels or to changing connectivity due to mobility, is adequately captured in our model to allow for state dependent network control policies. Quantitative performance measures that capture the quality of service requirements in these systems depending on the supported applications are discussed, including throughput maximization, energy consumption minimization, rate utility function maximization as well as general performance functionals. Crosslayer control algorithms with optimal or suboptimal performance with respect to the above measures are presented and analyzed. A detailed exposition of the related analysis and design techniques is provided. 1
Energy optimal control for time varying wireless networks
 IEEE Trans. Inform. Theory
, 2006
"... Abstract — We develop a dynamic control strategy for minimizing energy expenditure in a time varying wireless network with adaptive transmission rates. The algorithm operates without knowledge of traffic rates or channel statistics, and yields average power that is arbitrarily close to the minimum p ..."
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Cited by 180 (51 self)
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Abstract — We develop a dynamic control strategy for minimizing energy expenditure in a time varying wireless network with adaptive transmission rates. The algorithm operates without knowledge of traffic rates or channel statistics, and yields average power that is arbitrarily close to the minimum possible value achieved by an algorithm optimized with complete knowledge of future events. Proximity to this optimal solution is shown to be inversely proportional to network delay. We then present a similar algorithm that solves the related problem of maximizing network throughput subject to peak and average power constraints. The techniques used in this paper are novel and establish a foundation for stochastic network optimization.
Optimal Packet Scheduling in an Energy Harvesting Communication System
"... We consider the optimal packet scheduling problem in a singleuser energy harvesting wireless communication system. In this system, both the data packets and the harvested energy are modeled to arrive at the source node randomly. Our goal is to adaptively change the transmission rate according to th ..."
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Cited by 126 (26 self)
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We consider the optimal packet scheduling problem in a singleuser energy harvesting wireless communication system. In this system, both the data packets and the harvested energy are modeled to arrive at the source node randomly. Our goal is to adaptively change the transmission rate according to the traffic load and available energy, such that the time by which all packets are delivered is minimized. Under a deterministic system setting, we assume that the energy harvesting times and harvested energy amounts are known before the transmission starts. For the data traffic arrivals, we consider two different scenarios. In the first scenario, we assume that all bits have arrived and are ready at the transmitter before the transmission starts. In the second scenario, we consider the case where packets arrive during the transmissions, with known arrival times and sizes. We develop optimal offline scheduling policies which minimize the time by which all packets are delivered to the destination, under causality constraints on both data and energy arrivals.
Optimum transmission policies for battery limited energy harvesting nodes,” Submitted to IEEE Transactions on Wireless Communications, available at: http://arxiv.org/PS_cache/arxiv/pdf/1010/1010.6280v1.pdf. This full text paper was peer reviewed at the di
 in the IEEE ICC 2011 proceedings
"... Abstract—Wireless networks with energy harvesting battery equipped nodes are quickly emerging as a viable option for future wireless networks with extended lifetime. Equally important to their counterpart in the design of energy harvesting radios are the design principles that this new networking pa ..."
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Cited by 122 (23 self)
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Abstract—Wireless networks with energy harvesting battery equipped nodes are quickly emerging as a viable option for future wireless networks with extended lifetime. Equally important to their counterpart in the design of energy harvesting radios are the design principles that this new networking paradigm calls for. In particular, unlike wireless networks considered to date, the energy replenishment process and the storage constraints of the rechargeable batteries need to be taken into account in designing efficient transmission strategies. In this work, such transmission policies for rechargeable nodes are considered, and optimum solutions for two related problems are identified. Specifically, the transmission policy that maximizes the short term throughput, i.e., the amount of data transmitted in a finite time horizon is found. In addition, the relation of this optimization problem to another, namely, the minimization of the transmission completion time for a given amount of data is demonstrated, which leads to the solution of the latter as well. The optimum transmission policies are identified under the constraints on energy causality, i.e., energy replenishment process, as well as the energy storage, i.e., battery capacity. For battery replenishment, a model with discrete packets of energy arrivals is considered. The necessary conditions that the throughputoptimal allocation satisfies are derived, and then the algorithm that finds the optimal transmission policy with respect to the shortterm throughput and the minimum transmission completion time is given. Numerical results are presented to confirm the analytical findings. Index Terms—Energy harvesting, optimal scheduling, wireless networks, battery limited nodes. I.
Power Allocation and Routing in Multibeam Satellites With TimeVarying Channels
 IEEE TRANSACTIONS ON NETWORKING
, 2003
"... We consider power and server allocation in a multibeam satellite downlink which transmits data to different ground locations over timevarying channels. Packets destined for each ground location are stored in separate queues and the server rate for each queue depends on the power ( ) allocated to th ..."
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Cited by 96 (23 self)
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We consider power and server allocation in a multibeam satellite downlink which transmits data to different ground locations over timevarying channels. Packets destined for each ground location are stored in separate queues and the server rate for each queue depends on the power ( ) allocated to that server and the channel state ( ) according to a concave ratepower curve ( ). We establish the capacity region of all arrival rate vectors ( 1 ... ) which admit a stabilizable system. We then develop a powerallocation policy which stabilizes the system whenever the rate vector lies within the capacity region. Such stability is guaranteed even if the channel model and the specific arrival rates are unknown. Furthermore, the algorithm is shown to be robust to arbitrary variations in the input rates and a bound on average delay is established. As a special case, this analysis verifies stability and provides a performance bound for the Choosethe LargestConnectedQueues policy when channels can be in one of two states (ON or OFF) and servers are allocated at every timestep ( ). These results are extended to treat a joint problem of routing and power allocation in a system with multiple users and satellites and a throughput maximizing algorithm for this joint problem is constructed. Finally, we address the issue of interchannel interference and develop a modified policy when power vectors are constrained to feasible activation sets. Our analysis and problem formulation is also applicable to power control for wireless systems.
Broadcasting with an energy harvesting rechargeable transmitter
 IEEE Trans. Wireless Comm
, 2010
"... Abstract—In this paper, we investigate the transmission completion time minimization problem in an additive white Gaussian noise (AWGN) broadcast channel, where the transmitter is able to harvest energy from the nature, using a rechargeable battery. The harvested energy is modeled to arrive at the t ..."
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Cited by 76 (22 self)
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Abstract—In this paper, we investigate the transmission completion time minimization problem in an additive white Gaussian noise (AWGN) broadcast channel, where the transmitter is able to harvest energy from the nature, using a rechargeable battery. The harvested energy is modeled to arrive at the transmitter during the course of transmissions. The transmitter has a fixed number of packets to be delivered to each receiver. The objective is to minimize the time by which all of the packets are delivered to their respective destinations. To this end, we optimize the transmit powers and transmission rates in a deterministic setting. We first analyze the structural properties of the optimal transmission policy in a twouser broadcast channel via the dual problem of maximizing the departure region by a fixed time
Optimal energy and delay tradeoffs for multiuser wireless downlinks
 Proc. IEEE INFOCOM
, 2006
"... Abstract — We consider the fundamental delay tradeoffs for minimizing energy expenditure in a multiuser wireless downlink with randomly varying channels. First, we extend the BerryGallager bound to a multiuser context, demonstrating that any algorithm that yields average power within O(1/V) of th ..."
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Cited by 63 (17 self)
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Abstract — We consider the fundamental delay tradeoffs for minimizing energy expenditure in a multiuser wireless downlink with randomly varying channels. First, we extend the BerryGallager bound to a multiuser context, demonstrating that any algorithm that yields average power within O(1/V) of the minimum power required for network stability must also have an average queueing delay greater than or equal to Ω ( √ V). We then develop a class of algorithms, parameterized by V, that come within a logarithmic factor of achieving this fundamental tradeoff. The algorithms overcome an exponential state space explosion, and can be implemented in real time without apriori knowledge of traffic rates or channel statistics. Further, we discover a “superfast ” scheduling mode that beats the BerryGallager bound in the exceptional case when power functions are piecewise linear. Index Terms — queueing analysis, stability, optimization, stochastic control, asymptotic tradeoffs
Optimal packet scheduling in a multiple access channel with rechargeable nodes
 in Proc. IEEE ICC
, 2011
"... Abstract: In this paper, we investigate the optimal packet scheduling problem in a twouser multiple access communication system, where the transmitters are able to harvest energy from the nature. Under a deterministic system setting, we assume that the energy harvesting times and harvested energy a ..."
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Cited by 61 (16 self)
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Abstract: In this paper, we investigate the optimal packet scheduling problem in a twouser multiple access communication system, where the transmitters are able to harvest energy from the nature. Under a deterministic system setting, we assume that the energy harvesting times and harvested energy amounts are known before the transmission starts. For the packet arrivals, we assume that packets have already arrived and are ready to be transmitted at the transmitter before the transmission starts. Our goal is to minimize the time by which all packets from both users are delivered to the destination through controlling the transmission powers and transmission rates of both users. We first develop a generalized iterative backward waterfilling algorithm to characterize the maximum departure region of the transmitters for any given deadline T. Then, based on the sequence of maximum departure regions at energy arrival instants, we decompose the transmission completion time minimization problem into convex optimization problems and solve the overall problem efficiently. Index Terms: Energyharvesting communications, iterative backward waterfilling, multiaccess channel, throughput maximization.
Energyefficient resource allocation in wireless networks: An overview of gametheoretic approaches
 IEEE Signal Process. Magazine
, 2007
"... A gametheoretic model is proposed to study the crosslayer problem of joint power and rate control with quality of service (QoS) constraints in multipleaccess networks. In the proposed game, each user seeks to choose its transmit power and rate in a distributed manner in order to maximize its own ..."
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Cited by 53 (8 self)
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A gametheoretic model is proposed to study the crosslayer problem of joint power and rate control with quality of service (QoS) constraints in multipleaccess networks. In the proposed game, each user seeks to choose its transmit power and rate in a distributed manner in order to maximize its own utility while satisfying its QoS requirements. The user’s QoS constraints are specified in terms of the average source rate and an upper bound on the average delay where the delay includes both transmission and queuing delays. The utility function considered here measures energy efficiency and is particularly suitable for wireless networks with energy constraints. The Nash equilibrium solution for the proposed noncooperative game is derived and a closedform expression for the utility achieved at equilibrium is obtained. It is shown that the QoS requirements of a user translate into a “size ” for the user which is an indication of the amount of network resources consumed by the user. Using this competitive multiuser framework, the tradeoffs among throughput, delay, network capacity and energy efficiency are studied. In addition, analytical expressions are given for users ’ delay profiles and the delay performance of the users at Nash equilibrium is quantified.
PEDAMACS: Power efficient and delay aware medium access protocol for sensor networks
 IEEE Transactions on Mobile Computing
, 2002
"... Abstract—PEDAMACS is a Time Division Multiple Access (TDMA) scheme that extends the common single hop TDMA to a multihop sensor network, using a highpowered access point to synchronize the nodes and to schedule their transmissions and receptions. The protocol first enables the access point to gathe ..."
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Cited by 48 (6 self)
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Abstract—PEDAMACS is a Time Division Multiple Access (TDMA) scheme that extends the common single hop TDMA to a multihop sensor network, using a highpowered access point to synchronize the nodes and to schedule their transmissions and receptions. The protocol first enables the access point to gather topology (connectivity) information. A scheduling algorithm then determines when each node should transmit and receive data, and the access point announces the transmission schedule to the other nodes. The performance of PEDAMACS is compared to existing protocols based on simulations in TOSSIM, a simulation environment for TinyOS, the operating system for the Berkeley sensor nodes. For the traffic application we consider, the PEDAMACS network provides a lifetime of several years compared to several months and days based on random access schemes with and without sleep cycles, respectively, making sensor network technology economically viable. Index Terms—Sensor networks, energy efficiency, delay guarantee. 1