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74
Dynamic Power Allocation and Routing for Time Varying Wireless Networks
 IEEE Journal on Selected Areas in Communications
, 2003
"... We consider dynamic routing and power allocation for a wireless network with time varying channels. The network consists of power constrained nodes which transmit over wireless links with adaptive transmission rates. Packets randomly enter the system at each node and wait in output queues to be tran ..."
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Cited by 211 (50 self)
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We consider dynamic routing and power allocation for a wireless network with time varying channels. The network consists of power constrained nodes which transmit over wireless links with adaptive transmission rates. Packets randomly enter the system at each node and wait in output queues to be transmitted through the network to their destinations. We establish the capacity region of all rate matrices (# ij ) that the system can stably supportwhere (# ij ) represents the rate of traffic originating at node i and destined for node j. A joint routing and power allocation policy is developed which stabilizes the system and provides bounded average delay guarantees whenever the input rates are within this capacity region. Such performance holds for general arrival and channel state processes, even if these processes are unknown to the network controller. We then apply this control algorithm to an adhoc wireless network where channel variations are due to user mobility, and compare its performance with the GrossglauserTse relay model developed in [13].
Gamal, “Energyefficient packet transmission over a wireless link
 IEEE/ACM Trans. Networking
, 2002
"... Abstract—The paper considers the problem of minimizing the energy used to transmit packets over a wireless link via lazy schedules that judiciously vary packet transmission times. The problem is motivated by the following observation. With many channel coding schemes, the energy required to transmit ..."
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Cited by 103 (2 self)
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Abstract—The paper considers the problem of minimizing the energy used to transmit packets over a wireless link via lazy schedules that judiciously vary packet transmission times. The problem is motivated by the following observation. With many channel coding schemes, the energy required to transmit a packet can be significantly reduced by lowering transmission power and code rate, and therefore transmitting the packet over a longer period of time. However, information is often timecritical or delaysensitive and transmission times cannot be made arbitrarily long. We therefore consider packet transmission schedules that minimize energy subject to a deadline or a delay constraint. Specifically, we obtain an optimal offline schedule for a node operating under a deadline constraint. An inspection of the form of this schedule naturally leads us to an online schedule which is shown, through simulations, to perform closely to the optimal offline schedule. Taking the deadline to infinity, we provide an exact probabilistic analysis of our offline scheduling algorithm. The results of this analysis enable us to devise a lazy online algorithm that varies transmission times according to backlog. We show that this lazy schedule is significantly more energyefficient compared to a deterministic (fixed transmission time) schedule that guarantees queue stability for the same range of arrival rates. Index Terms—Minimum energy transmission, optimal schedules, power control, wireless LAN. I.
Energylatency tradeoffs for data gathering in wireless sensor networks
 In IEEE Infocom
, 2004
"... Abstract — We study the problem of scheduling packet transmissions for data gathering in wireless sensor networks. The focus is to explore the energylatency tradeoffs in wireless communication using techniques such as modulation scaling. The data aggregation tree – a multiplesource singlesink com ..."
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Cited by 80 (4 self)
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Abstract — We study the problem of scheduling packet transmissions for data gathering in wireless sensor networks. The focus is to explore the energylatency tradeoffs in wireless communication using techniques such as modulation scaling. The data aggregation tree – a multiplesource singlesink communication paradigm – is employed for abstracting the packet flow. We consider a realtime scenario where the data gathering must be performed within a specified latency constraint. We present algorithms to minimize the overall energy dissipation of the sensor nodes in the aggregation tree subject to the latency constraint. For the offline problem, we propose (a) a numerical algorithm for the optimal solution, and (b) a pseudopolynomial time approximation algorithm based on dynamic programming. We also discuss techniques for handling interference among the sensor nodes. Simulations have been conducted for both longrange communication and shortrange communication. The simulation results show that compared with the classic shutdown technique, between 20 % to 90 % energy savings can be achieved by our techniques, under different settings of several key system parameters. We also develop an online distributed protocol that relies only on the local information available at each sensor node within the aggregation tree. Simulation results show that between 15 % to 90 % energy conservation can be achieved by the online protocol. The adaptability of the protocol with respect to variations in the packet size and latency constraint is also demonstrated through several runtime scenarios. Index terms – System design, Mathematical optimization I.
Energyconstrained modulation optimization
 IEEE Transactions on Wireless Communications
, 2005
"... Abstract — We consider wireless systems where the nodes operate on batteries so that energy consumption must be minimized while satisfying given throughput and delay requirements. In this context, we analyze the best modulation strategy to minimize the total energy consumption required to send a giv ..."
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Cited by 75 (9 self)
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Abstract — We consider wireless systems where the nodes operate on batteries so that energy consumption must be minimized while satisfying given throughput and delay requirements. In this context, we analyze the best modulation strategy to minimize the total energy consumption required to send a given number of bits. The total energy consumption includes both the transmission energy and the circuit energy consumption. For uncoded systems, by optimizing the transmission time and the modulation parameters we show that up to 80 % energy savings is achievable over nonoptimized systems. For coded systems, we show that the benefit of coding varies with the transmission distance and the underlying modulation schemes. Index Terms — Energy efficiency, modulation optimization, MQAM, MFSK.
MiSer: An optimal lowenergy transmission strategy for
 In Proc. of the ACM/IEEE Intl. Conference on Mobile Computing and Networking
, 2003
"... Reducing the energy consumption by wireless communication devices is perhaps the most important issue in the widelydeployed and exponentiallygrowing IEEE 802.11 Wireless LANs (WLANs). TPC (Transmit Power Control) and PHY (physical layer) rate adaptation have been recognized as two most effective w ..."
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Cited by 72 (1 self)
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Reducing the energy consumption by wireless communication devices is perhaps the most important issue in the widelydeployed and exponentiallygrowing IEEE 802.11 Wireless LANs (WLANs). TPC (Transmit Power Control) and PHY (physical layer) rate adaptation have been recognized as two most effective ways to achieve this goal. The emerging 802.11h standard, which is an extension to the current 802.11 MAC and the highspeed 802.11a PHY, will provide a structured means to support intelligent TPC. In this paper, we propose a novel scheme, called MiSer, that minimizes the communication energy consumption in 802.11a/h systems by combining TPC with PHY rate adaptation. The key idea is to compute offline an optimal ratepower combination table, and then at runtime, a wireless station determines the most energyefficient transmission strategy for each data frame by a simple table lookup. Another key contribution of this paper is to provide a rigorous analysis of the relation among different radio ranges and TPC’s effect on the interference in 802.11a/h systems, which justifies MiSer’s approach to ameliorating the TPCcaused interference by transmitting the CTS frames at a stronger power level. Our simulation results show that MiSer delivers about 20 % more data per unit of energy consumption than the PHY rate adaptation scheme without TPC, while outperforming singlerate TPC schemes significantly thanks to the excellent energysaving capability of PHY rate adaptation.
Latency of wireless sensor networks with uncoordinated power saving mechanisms
 in Proceedings of Mobihoc, 2004
, 2004
"... We consider a wireless sensor network, where nodes switch between an active (on) and a sleeping (off) mode, to save energy. The basic assumptions are that the on/off schedules are completely uncoordinated and that the sensors are distributed according to a Poisson process and their connectivity rang ..."
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Cited by 61 (6 self)
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We consider a wireless sensor network, where nodes switch between an active (on) and a sleeping (off) mode, to save energy. The basic assumptions are that the on/off schedules are completely uncoordinated and that the sensors are distributed according to a Poisson process and their connectivity ranges are larger or equal to their sensing ranges. Moreover, the durations of active and sleeping periods are such that the number of active nodes at any particular time is so low that the network is always disconnected. Is it possible to use such a network for timecritical monitoring of an area? Such a scenario requires indeed to have bounds on the latency, which is the delay elapsed between the time at which an incoming event is sensed by some node of the network and the time at which this information is retrieved by the data collecting sink. A positive answer is provided to this question under some simplifying assumptions discussed in the paper. More precisely, we prove that the messages sent by a sensing node reach the sink with a fixed asymptotic speed, which does not depend on the random location of the nodes, but only on the network parameters (node density, connectivity range, duration of active and sleeping periods). The results are obtained rigorously by using an extension of first passage percolation theory.
Poweraware scheduling for makespan and flow
 In Proc. SPAA, 2006
, 2006
"... We consider offline scheduling algorithms that incorporate speed scaling to address the bicriteria problem of minimizing energy consumption and a scheduling metric. For makespan, we give lineartime algorithms to compute all nondominated solutions for the general uniprocessor problem and for the mu ..."
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Cited by 36 (1 self)
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We consider offline scheduling algorithms that incorporate speed scaling to address the bicriteria problem of minimizing energy consumption and a scheduling metric. For makespan, we give lineartime algorithms to compute all nondominated solutions for the general uniprocessor problem and for the multiprocessor problem when every job requires the same amount of work. We also show that the multiprocessor problem becomes NPhard when jobs can require different amounts of work. For total flow, we show that the optimal flow corresponding to a particular energy budget cannot be exactly computed on a machine supporting arithmetic and the extraction of roots. This hardness result holds even when scheduling equalwork jobs on a uniprocessor. We do, however, extend previous work by Pruhs et al. to give an arbitrarilygood approximation for scheduling equalwork jobs on a multiprocessor. 1
EnergyBalanced Task Allocation for Collaborative Processing in Wireless Sensor Networks
 Mobile Networks and Applications
, 2005
"... We propose an energybalanced allocation of a realtime application onto a singlehop cluster of homogeneous sensor nodes connected with multiple wireless channels. An epochbased application consisting of a set of communicating tasks is considered. Each sensor node is equipped with discrete dynam ..."
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Cited by 35 (3 self)
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We propose an energybalanced allocation of a realtime application onto a singlehop cluster of homogeneous sensor nodes connected with multiple wireless channels. An epochbased application consisting of a set of communicating tasks is considered. Each sensor node is equipped with discrete dynamic voltage scaling (DVS). The time and energy costs of both computation and communication activities are considered. We propose both an Integer Linear Programming (ILP) formulation and a polynomial time 3phase heuristic. Our simulation results show that for small scale problems (with # ## tasks), up to 5x lifetime improvement is achieved by the ILPbased approach, compared with the baseline where no DVS is used. Also, the 3phase heuristic achieves up to 63% of the system lifetime obtained by the ILPbased approach. For large scale problems (with 60  100 tasks), up to 3.5x lifetime improvement can be achieved by the 3phase heuristic. We also incorporate techniques for exploring the energylatency tradeoffs of communication activities (such as modulation scaling), which leads to 10x lifetime improvement in our simulations.
Gamal, “On adaptive transmission for energy efficiency in wireless data networks
 IEEE Transactions on Information Theory
, 2004
"... Abstract—This paper investigates the problem of energyefficient transmission of data packets in a wireless network by jointly adapting to backlog and channel condition. Specifically, we consider minimumenergy scheduling problems over multipleaccess channels, broadcast channels, and channels with ..."
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Cited by 31 (0 self)
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Abstract—This paper investigates the problem of energyefficient transmission of data packets in a wireless network by jointly adapting to backlog and channel condition. Specifically, we consider minimumenergy scheduling problems over multipleaccess channels, broadcast channels, and channels with fading, when packets of all users need to be transmitted before a deadline. Earlier work has considered a similar setup and demonstrated significant transmission energy saving by adapting to backlog for channels that are time invariant and when transmission is restricted to timedivision. For concreteness, throughout the paper, rates and powers corresponding to optimal coding over discretetime additive white Gaussian noise (AWGN) channels are assumed. The results, however, hold for more general channels and coding schemes where the total transmitted power is convex in the transmission rates. The offline scheduling problems for all the channels considered are shown to reduce to convex optimization problems with linear constraints. An iterative algorithm, referred to as FlowRight, that finds optimal offline schedules is presented. A heuristic online algorithm that we call lookahead waterfilling, which jointly adapts to both channel fading state and backlog is described. By the use of a small buffer which introduces an almost fixed delay, this algorithm achieves a considerable reduction in energy relative to water filling solely on channel states. Index Terms—Adaptive transmission, broadcast, energyefficient transmission, iterative algorithm, multipleaccess, power
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 29 (11 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.