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Elif Uysal-Biyikoglu

Publications and source records attributed to Elif Uysal-Biyikoglu.

At least 19 recordsLinked to original sources
arXiv2018

Delay and Peak-Age Violation Probability in Short-Packet Transmissions

This paper investigates the distribution of delay and peak age of information in a communication system where packets, generated according to an independent and identically distributed Bernoulli process, are placed in a single-server queue with first-come first-served discipline and transmitted over an additive white Gaussian noise (AWGN) channel. When a packet is correctly decoded, the sender receives an instantaneous error-free positive acknowledgment, upon which it removes the packet from the buffer. In the case of negative acknowledgment, the packet is retransmitted. By leveraging finite-blocklength results for the AWGN channel, we characterize the delay violation and the peak-age violation probability without resorting to approximations based on large deviation theory as in previous literature. Our analysis reveals that there exists an optimum blocklength that minimizes the delay violation and the peak-age violation probabilities. We also show that one can find two blocklength values that result in very similar average delay but significantly different delay violation probabilities. This highlights the importance of focusing on violation probabilities rather than on averages.

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arXiv2018

Age-Optimal Updates of Multiple Information Flows

In this paper, we study an age of information minimization problem, where multiple flows of update packets are sent over multiple servers to their destinations. Two online scheduling policies are proposed. When the packet generation and arrival times are synchronized across the flows, the proposed policies are shown to be (near) optimal for minimizing any time-dependent, symmetric, and non-decreasing penalty function of the ages of the flows over time in a stochastic ordering sense.

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arXiv2018

Achieving the Age-Energy Tradeoff with a Finite-Battery Energy Harvesting Source

We study the problem of minimizing the time-average expected Age of Information for status updates sent by an energy-harvesting source with a finite-capacity battery. In prior literature, optimal policies were observed to have a threshold structure under Poisson energy arrivals, for the special case of a unit-capacity battery. In this paper, we generalize this result to any (integer) battery capacity, and explicitly characterize the threshold structure. We obtain tools to derive the optimal policy for arbitrary energy buffer (i.e. battery) size. One of these results is the unexpected equivalence of the minimum average AoI and the optimal threshold for the highest energy state.

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arXiv2018

Kalman Prediction Based Proportional Fair Resource Allocation for a Solar Powered Wireless Downlink

Optimization of a Wireless Sensor Network (WSN) downlink with an energy harvesting transmitter (base station) is considered. The base station (BS), which is attached to the central controller of the network, sends control information to the gateways of individual WSNs in the downlink. This paper specifically addresses the case where the BS is supplied with solar energy. Leveraging the daily periodicity inherent in solar energy harvesting, the schedule for delivery of maintenance messages from the BS to the nodes of a distributed network is optimized. Differences in channel gain from the BS to sensor nodes make it a challenge to provide service to each of them while efficiently spending the harvested energy. Based on PTF (Power-Time-Fair), a close-to-optimal solution for fair allocation of harvested energy in a wireless downlink proposed in previous work, we develop an online algorithm, PTF-On, that operates two algorithms in tandem: A prediction algorithm based on a Kalman filter that operates on solar irradiation measurements, and a modified version of PTF. PTF-On can predict the energy arrival profile throughout the day and schedule transmission to nodes to maximize total throughput in a proportionally fair way.

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arXiv2018

Scheduling Policies for Minimizing Age of Information in Broadcast Wireless Networks

We consider a wireless broadcast network with a base station sending time-sensitive information to a number of clients through unreliable channels. The Age of Information (AoI), namely the amount of time that elapsed since the most recently delivered packet was generated, captures the freshness of the information. We formulate a discrete-time decision problem to find a transmission scheduling policy that minimizes the expected weighted sum AoI of the clients in the network. We first show that in symmetric networks a Greedy policy, which transmits the packet with highest current age, is optimal. For general networks, we develop three low-complexity scheduling policies: a randomized policy, a Max-Weight policy and a Whittle's Index policy, and derive performance guarantees as a function of the network configuration. To the best of our knowledge, this is the first work to derive performance guarantees for scheduling policies that attempt to minimize AoI in wireless networks with unreliable channels. Numerical results show that both Max-Weight and Whittle's Index policies outperform the other scheduling policies in every configuration simulated, and achieve near optimal performance.

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arXiv2017

Remote Estimation of the Wiener Process over a Channel with Random Delay

In this paper, we consider a problem of sampling a Wiener process, with samples forwarded to a remote estimator via a channel that consists of a queue with random delay. The estimator reconstructs a real-time estimate of the signal from causally received samples. Motivated by recent research on age-of-information, we study the optimal sampling strategy that minimizes the mean square estimation error subject to a sampling frequency constraint. We prove that the optimal sampling strategy is a threshold policy, and find the optimal threshold. This threshold is determined by the sampling frequency constraint and how much the Wiener process varies during the channel delay. An interesting consequence is that even in the absence of the sampling frequency constraint, the optimal strategy is not zero-wait sampling in which a new sample is taken once the previous sample is delivered; rather, it is optimal to wait for a non-zero amount of time after the previous sample is delivered, and then take the next sample. Further, if the sampling times are independent of the observed Wiener process, the optimal sampling problem reduces to an age-of-information optimization problem that has been recently solved. Our comparisons show that the estimation error of the optimal sampling policy is much smaller than those of age-optimal sampling, zero-wait sampling, and classic uniform sampling.

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arXiv2017

Update or Wait: How to Keep Your Data Fresh

In this work, we study how to optimally manage the freshness of information updates sent from a source node to a destination via a channel. A proper metric for data freshness at the destination is the age-of-information, or simply age, which is defined as how old the freshest received update is since the moment that this update was generated at the source node (e.g., a sensor). A reasonable update policy is the zero-wait policy, i.e., the source node submits a fresh update once the previous update is delivered and the channel becomes free, which achieves the maximum throughput and the minimum delay. Surprisingly, this zero-wait policy does not always minimize the age. This counter-intuitive phenomenon motivates us to study how to optimally control information updates to keep the data fresh and to understand when the zero-wait policy is optimal. We introduce a general age penalty function to characterize the level of dissatisfaction on data staleness and formulate the average age penalty minimization problem as a constrained semi-Markov decision problem (SMDP) with an uncountable state space. We develop efficient algorithms to find the optimal update policy among all causal policies, and establish sufficient and necessary conditions for the optimality of the zero-wait policy. Our investigation shows that the zero-wait policy is far from the optimum if (i) the age penalty function grows quickly with respect to the age, (ii) the packet transmission times over the channel are positively correlated over time, or (iii) the packet transmission times are highly random (e.g., following a heavy-tail distribution).

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arXiv2017

Finite Horizon Energy-Efficient Scheduling with Energy Harvesting Transmitters over Fading Channels

In this paper, energy-efficient transmission schemes achieving maximal throughput over a finite time interval are studied in a problem setting including energy harvests, data arrivals and channel variation. The goal is to express the offline optimal policy in a way that facilitates a good online solution. We express any throughput maximizing energy efficient offline schedule (EE-TM-OFF) explicitly in terms of water levels. This allows per-slot real-time evaluation of transmit power and rate decisions, using estimates of the associated offline water levels. To compute the online power level, we construct a stochastic dynamic program that incorporates the offline optimal solution as a stochastic process. We introduce the "Immediate Fill" metric which provides a lower bound on the efficiency of any online policy with respect to the corresponding optimal offline solution. The online algorithms obtained this way exhibit performance close to the offline optimal, not only in the long run but also in short problem horizons, deeming them suitable for practical implementations.

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arXiv2017

Scheduling Status Updates to Minimize Age of Information with an Energy Harvesting Sensor

Age of Information is a measure of the freshness of status updates in monitoring applications and update-based systems. We study a real-time remote sensing scenario with a sensor which is restricted by time-varying energy constraints and battery limitations. The sensor sends updates over a packet erasure channel with no feedback. The problem of finding an age-optimal threshold policy, with the transmission threshold being a function of the energy state and the estimated current age, is formulated. The average age is analyzed for the unit battery scenario under a memoryless energy arrival process. Somewhat surprisingly, for any finite arrival rate of energy, there is a positive age threshold for transmission, which corresponding to transmitting at a rate lower than that dictated by the rate of energy arrivals. A lower bound on the average age is obtained for general battery size.

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arXiv2015

Optimal Energy Allocation Policies for a High Altitude Flying Wireless Access Point

Inspired by recent industrial efforts toward high altitude flying wireless access points powered by renewable energy, an online resource allocation problem for a mobile access point (AP) travelling at high altitude is formulated. The AP allocates its resources (available energy) to maximize the total utility (reward) provided to a sequentially observed set of users demanding service. The problem is formulated as a 0/1 dynamic knapsack problem with incremental capacity over a finite time horizon, the solution of which is quite open in the literature. We address the problem through deterministic and stochastic formulations. For the deterministic problem, several online approximations are proposed based on an instantaneous threshold that can adapt to short-time-scale dynamics. For the stochastic model, after showing the optimality of a threshold based solution on a dynamic programming (DP) formulation, an approximate threshold based policy is obtained. The performances of proposed policies are compared with that of the optimal solution obtained through DP.

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arXiv2014

UROP: A Simple, Near-Optimal Scheduling Policy for Energy Harvesting Sensors

This paper considers a single-hop wireless network where a central node (or fusion center, FC) collects data from a set of m energy harvesting (EH) nodes (e.g. nodes of a wireless sensor network). In each time slot, k of m nodes can be scheduled by the FC for transmission over k orthogonal channels. FC has no knowledge about EH processes and current battery states of nodes; however, it knows outcomes of previous transmission attempts. The objective is to find a low complexity scheduling policy that maximizes total throughput of the data backlogged system using the harvested energy, for all types (uniform, non-uniform, independent, correlated (i.e. Markovian), etc.) EH processes. Energy is assumed to be stored losslessly in the nodes batteries, up to a storage capacity (the infinite capacity case is also considered.) The problem is treated in finite and infinite problem horizons. A low-complexity policy, UROP (Uniformizing Random Ordered Policy) is proposed, whose near optimality is shown. Numerical examples indicate that under a reasonable-sized battery capacity, UROP uses the arriving energy with almost perfect efficiency. As the problem is a restless multi-armed bandit (RMAB) problem with an average reward criterion, UROP may have a wider application area than communication networks.

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arXiv2013

Finite Horizon Online Lazy Scheduling with Energy Harvesting Transmitters over Fading Channels

Lazy scheduling, i.e. setting transmit power and rate in response to data traffic as low as possible so as to satisfy delay constraints, is a known method for energy efficient transmission.This paper addresses an online lazy scheduling problem over finite time-slotted transmission window and introduces low-complexity heuristics which attain near-optimal performance.Particularly, this paper generalizes lazy scheduling problem for energy harvesting systems to deal with packet arrival, energy harvesting and time-varying channel processes simultaneously. The time-slotted formulation of the problem and depiction of its offline optimal solution provide explicit expressions allowing to derive good online policies and algorithms.

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arXiv2013

Finite-horizon Online Transmission Rate and Power Adaptation on a Communication Link with Markovian Energy Harvesting

As energy harvesting communication systems emerge, there is a need for transmission schemes that dynamically adapt to the energy harvesting process. In this paper, after exhibiting a finite-horizon online throughput-maximizing scheduling problem formulation and the structure of its optimal solution within a dynamic programming formulation, a low complexity online scheduling policy is proposed. The policy exploits the existence of thresholds for choosing rate and power levels as a function of stored energy, harvest state and time until the end of the horizon. The policy, which is based on computing an expected threshold, performs close to optimal on a wide range of example energy harvest patterns. Moreover, it achieves higher throughput values for a given delay, than throughput-optimal online policies developed based on infinite-horizon formulations in recent literature. The solution is extended to include ergodic time-varying (fading) channels, and a corresponding low complexity policy is proposed and evaluated for this case as well.

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arXiv2012

Proportional Fair Resource Allocation on an Energy Harvesting Downlink - Part I: Structure

This paper considers the allocation of time slots in a frame, as well as power and rate to multiple receivers on an energy harvesting downlink. Energy arrival times that will occur within the frame are known at the beginning of the frame. The goal is to optimize throughput in a proportionally fair way, taking into account the inherent differences of channel quality among users. Analysis of structural characteristics of the problem reveals that it can be formulated as a biconvex optimization problem, and that it has multiple optima. Due to the biconvex nature of the problem, a Block Coordinate Descent (BCD) based optimization algorithm that converges to an optimal solution is presented. Numerical and simulation results show that the power-time allocations found by BCD achieve a good balance between total throughput and fairness.

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arXiv2012

Proportional Fair Resource Allocation on an Energy Harvesting Downlink - Part II: Algorithms

In this paper, the proportionally fair allocation of time slots in a frame, as well as power level to multiple receivers in an energy harvesting broadcast system, is considered. Energy harvest times in a frame are assumed to be known at the beginning of that frame. The goal is to solve an optimization problem designed to maximize a throughput-based utility function that provides proportional fairness among users. An optimal solution of the problem was obtained by using a Block Coordinate Descent (BCD) method in earlier work (presented in Part I of this study). However, finding the optimal allocation entails a computational complexity that increases sharply in terms of the number of users or slots. In this paper, certain structural characteristics of the optimal power-time allocation policy are derived. Building on those, two simple and computationally scalable heuristics, PTF and ProNTO are proposed. Simulation results suggest that PTF and ProNTO can closely track the performance of the BCD solution.

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arXiv2011

Optimal Offline Broadcast Scheduling with an Energy Harvesting Transmitter

We consider an energy harvesting transmitter broadcasting data to two receivers. Energy and data arrivals are assumed to occur at arbitrary but known instants. The goal is to minimize the total transmission time of the packets arriving within a certain time window, using the energy that becomes available during this time. An achievable rate region with structural properties satisfied by the two-user AWGN BC capacity region is assumed. Structural properties of power and rate allocation in an optimal policy are established, as well as the uniqueness of the optimal policy under the condition that all the data of the "weaker" user are available at the beginning. An iterative algorithm, DuOpt, based on block coordinate descent that achieves the same structural properties as the optimal is described. Investigating the ways to have the optimal schedule of two consecutive epochs in terms of energy efficiency and minimum transmission duration, it has been shown that DuOpt achieves best performance under the same special condition of uniqueness.

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arXiv2011

A Greedy link scheduler for Wireless Networks having Gaussian Broadcast and Multiple Access Channels

Information theoretic Broadcast Channels (BC) and Multiple Access Channels (MAC) enable a single node to transmit data simultaneously to multiple nodes, and multiple nodes to transmit data simultaneously to a single node respectively. In this paper, we address the problem of link scheduling in multihop wireless networks containing nodes with BC and MAC capabilities. We first propose an interference model that extends protocol interference models, originally designed for point to point channels, to include the possibility of BC and MAC. Due to the high complexity of optimal link schedulers, we introduce the Multiuser Greedy Maximum Weight algorithm for link scheduling in multihop wireless networks containing BCs and MACs. Given a network graph, we develop new local pooling conditions and show that the performance of our algorithm can be fully characterized using the associated parameter, the multiuser local pooling factor. We provide examples of some network graphs, on which we apply local pooling conditions and derive the multiuser local pooling factor. We prove optimality of our algorithm in tree networks and show that the exploitation of BCs and MACs improve the throughput performance considerably in multihop wireless networks.

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