Capacity Achieving Distributed Scheduling With Finite Buffers

Xue, Dong; Murawski, Robert; Ekici, Eylem

doi:10.1109/tnet.2014.2303093

Cited by 14 publications

(18 citation statements)

References 39 publications

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“…We complete the proof. APPENDIX E: PROOF OF LEMMA 3 By Lemma 2, for any given R s , R r , N r , the recurrent class C is fixed and does not change with the threshold Q th ∈ Q, and the ergodic system throughput in (17) only depends on the steady-state probability vector π(Q th ) and the average departure rate vector r(Q th ) of C. Note that, by (15) and (16), π(Q th ) and r(Q th ) only depend on the link selection control for the recurrent states in C. Since q * th and q * th,next are two adjacent recurrent states, by (12), any threshold Q * th ∈ {Q|q * th ≤ Q < q * th,next , Q ∈ Q} leads to the same link selection control for the recurrent states, and hence achieves the same ergodic throughput. Under the stationary unichain policies in (5) and (12), the induced markov chain {Q t } is an ergodic unichain.…”

Section: Appendix B: Proof Of Lemmamentioning

confidence: 97%

“…The system of linear equations in (15) can be transformed to the following system of linear equations:…”

Section: Algorithm For Problemmentioning

confidence: 99%

“…In [14], the authors propose joint flow control, routing and scheduling algorithms to maximize the throughput. References [15] and [16] adopt similar approaches to those in [13] and [14], and design control algorithms to optimize network utilities for multi-hop networks with finite source and relay buffers. However, the gap between the utility of each algorithm proposed in [14]- [16] and the optimal utility is inversely proportional to the buffer size.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Stochastic Throughput Optimization for Two-Hop Systems With Finite Relay Buffers

Zhou

Cui

Tao

2015

IEEE Trans. Signal Process.

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Abstract-Optimal queueing control of multi-hop networks remains a challenging problem even in the simplest scenarios. In this paper, we consider a two-hop half-duplex relaying system with random channel connectivity. The relay is equipped with a finite buffer. We focus on stochastic link selection and transmission rate control to maximize the average system throughput subject to a half-duplex constraint. We formulate this stochastic optimization problem as an infinite horizon average cost Markov decision process (MDP), which is well-known to be a difficult problem. By using sample-path analysis and exploiting the specific problem structure, we first obtain an equivalent Bellman equation with reduced state and action spaces. By using relative value iteration algorithm, we analyze the properties of the value function of the MDP. Then, we show that the optimal policy has a threshold-based structure by characterizing the supermodularity in the optimal control. Based on the threshold-based structure and Markov chain theory, we further simplify the original complex stochastic optimization problem to a static optimization problem over a small discrete feasible set and propose a lowcomplexity algorithm to solve the simplified static optimization problem by making use of its special structure. Furthermore, we obtain the closed-form optimal threshold for the symmetric case. The analytical results obtained in this paper also provide design insights for two-hop relaying systems with multiple relays equipped with finite relay buffers.Index Terms-Wireless relay system, finite buffer, throughput optimization, Markov decision process, Markov chain theory, matrix update, structural results.

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Section: Appendix B: Proof Of Lemmamentioning

confidence: 97%

“…The system of linear equations in (15) can be transformed to the following system of linear equations:…”

Section: Algorithm For Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Stochastic Throughput Optimization for Two-Hop Systems With Finite Relay Buffers

Zhou

Cui

Tao

2015

IEEE Trans. Signal Process.

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“…Jensen et al [15] proposed a time/utility function to describe the relationship between the running time and the utility of a task, and their aim is to maximize the total utility by finishing all tasks as quickly as possible. References [16][17][18] studied how to get the maximal utility with limited energy. In addition, in order to satisfy the utility acquirement and the energy budget, Wu et al [19] proposed a unimodal arbitrary arrival with energy bounds algorithm (EBUA), and the EBUA solved the problem of task scheduling based on unimodal arbitrary arrival model.…”

Section: Energy Saving Scheduling Algorithmsmentioning

confidence: 99%

A dynamic scheduling algorithm for energy harvesting embedded systems

Tan

Xiang-dong

2016

J Wireless Com Network

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Energy harvesting embedded systems are embedded systems that integrate with energy harvesting modules. In this kind of systems, service tasks and energy harvesting tasks must be scheduled efficiently to keep the whole system working properly as long as possible. In this paper, we model an energy harvesting embedded system with an energy model, a task model, and a resource model and propose a dynamic task scheduling algorithm. The proposed algorithm is based on dynamic voltage and frequency scaling technique and dynamically concentrates all disperse free time together to harvest energy. We validate the efficiency and effectiveness of the proposed algorithm under both energy-constraint and non-energy-constraint situations with the Yartiss simulation tool.

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“…Backpressure using LIFO service has been shown to offer better delay performance [10]. The framework has been extended to handle finite buffer sizes [8]. Other researchers have focused on how to make backpressure scheduling more distributed so that it can be implemented more easily [13].…”

Section: Related Workmentioning

confidence: 99%

Throughput-Optimal Robotic Message Ferrying for Wireless Networks Using Backpressure Control

Gasparri

Krishnamachari

2014

2014 IEEE 11th International Conference on Mobile Ad Hoc and Sensor Systems

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We consider the problem of controlling the motion of a set of robots to ferry messages between a given set of statically-placed nodes. The design and analysis of an arrivalrate unaware throughput-optimal policy for this problem is challenging because of the coupling between position and link rate. We propose a fine-grained backpressure message ferrying algorithm (FBMF) for joint motion and transmission control of robots. Unlike traditional backpressure settings, because the controlled motion of the relay nodes changes the channel rates, it turns out that the conventional approach to prove throughput optimality does not work in this problem setting. We prove for the simplest setting (single-flow, single-robot, constant arrival) that this policy indeed achieves throughput optimality. The analysis reveals that under feasible traffic, even when queues are highly over-loaded, the change in the total queue size can be positive over a time step, nevertheless the system exhibits a limit-cycle behavior and stability holds because the change in the total queue size is negative over the cycle for sufficiently large queues. We pose the design and analysis of a throughput optimal policy for the general case as a challenging open problem for network theory.

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Capacity Achieving Distributed Scheduling With Finite Buffers

Cited by 14 publications

References 39 publications

Stochastic Throughput Optimization for Two-Hop Systems With Finite Relay Buffers

Stochastic Throughput Optimization for Two-Hop Systems With Finite Relay Buffers

A dynamic scheduling algorithm for energy harvesting embedded systems

Throughput-Optimal Robotic Message Ferrying for Wireless Networks Using Backpressure Control

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