Optimal scheduling of real-time traffic in wireless networks with delayed feedback

Kim, Kyu Seob; Li, Chih-Ping; Kadota, Igor; Modiano, Eytan

doi:10.1109/allerton.2015.7447137

Cited by 8 publications

(12 citation statements)

References 12 publications

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“…Proposed algorithm to find γ * : start with γ = max{γ i }. Then, according to (33), all nodes have µ i = q i /p i and, by the feasibility condition in (5)…”

Section: B Optimal Stationary Randomized Policymentioning

confidence: 99%

“…A framework for modeling wireless networks with timelythroughput requirements was proposed in [2] together with two debt-based scheduling policies that fulfill any feasible requirements. Generalizations of this model to different network configurations were proposed in [3]- [5]. Scheduling policies that maximize throughput and also provide service regularity in wireless networks were studied in [6]- [8].…”

Section: Introductionmentioning

confidence: 99%

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Scheduling Algorithms for Optimizing Age of Information in Wireless Networks With Throughput Constraints

Kadota

Sinha

Modiano

2019

IEEE/ACM Trans. Networking

Self Cite

216

129

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Age of Information (AoI) is a performance metric that captures the freshness of the information from the perspective of the destination. The AoI measures the time that elapsed since the generation of the packet that was most recently delivered to the destination. In this paper, we consider a singlehop wireless network with a number of nodes transmitting timesensitive information to a Base Station and address the problem of minimizing the Expected Weighted Sum AoI of the network while simultaneously satisfying timely-throughput constraints from the nodes. We develop four low-complexity transmission scheduling policies that attempt to minimize AoI subject to minimum throughput requirements and evaluate their performance against the optimal policy. In particular, we develop a randomized policy, a Max-Weight policy, a Drift-Plus-Penalty policy and a Whittle's Index policy, and show that they are guaranteed to be within a factor of two, four, two and eight, respectively, away from the minimum AoI possible. Simulation results show that Max-Weight and Drift-Plus-Penalty outperform the other policies, both in terms of AoI and throughput, in every network configuration simulated, and achieve near optimal performance.

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“…Proposed algorithm to find γ * : start with γ = max{γ i }. Then, according to (33), all nodes have µ i = q i /p i and, by the feasibility condition in (5)…”

Section: B Optimal Stationary Randomized Policymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Scheduling Algorithms for Optimizing Age of Information in Wireless Networks With Throughput Constraints

Kadota

Sinha

Modiano

2019

IEEE/ACM Trans. Networking

Self Cite

216

129

View full text Add to dashboard Cite

show abstract

“…Proof. Consider the objective function for the Randomized policy in (28) and assume a general frame length T . To find an upper bound U R B , we derive a lower bound on E[d i ].…”

mentioning

confidence: 99%

“…Substituting the lower bound (91) into the objective function for the Randomized policy in (28) gives…”

mentioning

confidence: 99%

Scheduling Policies for Minimizing Age of Information in Broadcast Wireless Networks

Kadota

Sinha

Uysal-Biyikoğlu

et al. 2018

IEEE/ACM Trans. Networking

Self Cite

524

408

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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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“…Lyapunov optimization theory has been widely applied for developing dynamic algorithms that schedule users with packets with deadlines. In [17][18][19][20], the authors consider the rate maximization under power and delay constraints. In [17], the authors consider the power allocation for users with hard-deadline constraints.…”

Section: Related Workmentioning

confidence: 99%

Dynamic power control for time-critical networking with heterogeneous traffic

Fountoulakis¹,

Παππάς²,

Ephremides³

2021

ITU-J FET

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Future wireless networks will be characterized by heterogeneous traffic requirements. Examples can be low-latency or minimum-througput requirements. Therefore, the network has to adjust to different needs. Usually, users with low-latency requirements have to deliver their demand within a specific time frame, i.e., before a deadline, and they coexist with throughput oriented users. In addition, mobile devices have a limited-power budget and therefore, a power-efficient scheduling scheme is required by the network. In this work, we cast a stochastic network optimization problem for minimizing the packet drop rate while guaranteeing a minimum throughput and taking into account the limited-power capabilities of the users. We apply tools from Lyapunov optimization theory in order to provide an algorithm, named Dynamic Power Control (DPC) algorithm, that solves the formulated problem in real time. It is proved that the DPC algorithm gives a solution arbitrarily close to the optimal one. Simulation results show that our algorithm outperforms the baseline Largest-Debt-First (LDF) algorithm for short deadlines and multiple users.

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Optimal scheduling of real-time traffic in wireless networks with delayed feedback

Cited by 8 publications

References 12 publications

Scheduling Algorithms for Optimizing Age of Information in Wireless Networks With Throughput Constraints

Scheduling Algorithms for Optimizing Age of Information in Wireless Networks With Throughput Constraints

Scheduling Policies for Minimizing Age of Information in Broadcast Wireless Networks

Dynamic power control for time-critical networking with heterogeneous traffic

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