Backpressure Delay Enhancement for Encounter-Based Mobile Networks While Sustaining Throughput Optimality

Alresaini, Majed; Wright, Kwame-Lante; Krishnamachari, Bhaskar; Neely, Michael J.

doi:10.1109/tnet.2015.2404331

Cited by 26 publications

(17 citation statements)

References 52 publications

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“…Other works attempt to ameliorate the delay performance while considering the throughput utility [3, 20–23] and produced good results. Lotfinezhad and Marbach [22] achieve optimal throughput and the approximate delay optimality in the torus topology.…”

Section: Related Workmentioning

confidence: 99%

“…Supittayapornpong and Neely [21] develop a distributed algorithm that achieves near‐optimal utility considering the corresponding delay, where the delay refers to the average delay in a steady state. Aiming at the problem of long delays in the back‐pressure routeing, Alresaini et al [23] propose a backpressure with adaptive redundancy (BWAR) algorithm, which improves the method but still considers the average delay that refers to the total queue occupancy of undelivered packets when all queues are stabilised. However, the worst‐case delay is rarely addressed, which is an important measure that determines if one job is served or not before the allowable delay.…”

Section: Related Workmentioning

confidence: 99%

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Workload scheduling toward worst‐case delay and optimal utility for single‐hop Fog‐IoT architecture

et al. 2018

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Workload scheduling toward worst‐case delay and optimal utility for single‐hop Fog‐IoT architecture

et al. 2018

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“…In addition to the shortest-path-based method, improvements to the queue structure and queueing management have been made to reduce the delay of back-pressure routeing. In [4], Alresaini et al improve the packet delivery efficiency by proposing a redundancybased back-pressure algorithm which adds some duplicate buffers to increase the pressure of some flows. In [11], Ji et al describe a delay-based back-pressure algorithm which introduces a delayaware queueing policy to improve the original back-pressure algorithm.…”

Section: Related Workmentioning

confidence: 99%

“…However, the literature notes that this pre-establish routeing method wastes the space gain of the network and cannot maximise network throughput. Throughput-optimal routeing and scheduling, first developed in the seminal work of [1], has been extensively studied in [2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Shortest‐path‐based back‐pressure routing with single‐FIFO queueing in ad hoc networks'

2019

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Owing to the limited network resources in ad hoc networks, improving network throughput is the key to solve network congestion and increase network transmission efficiency. Back-pressure routeing, as an optimal routeing strategy for throughput, has recently received substantial attention for joint routeing and scheduling over multi-hop wireless networks. However, the inefficient routeing decision and complex queueing management of back-pressure routeing make it unsuitable for practical applications. This study proposes an improved back-pressure routeing algorithm with one first-input-first-output (FIFO) queueing structure using the shortest-path decision. By making use of the shortest-path knowledge, the feasible routes quickly converge to the shortest path when the network is lightly loaded. On the other hand, when the network load is heavy, the proposed algorithm remains optimal for exploring all the feasible paths between each source and destination. The backpressure routeing design based on a single-FIFO queue architecture greatly simplifies the complexity of packet queueing management. The authors' results indicate that the proposed routeing algorithm achieves lower end-to-end delay than that of some other back-pressure algorithms without reducing the network throughput performance.

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“…Scheduling based on the back-pressure algorithm is equivalent to solving the problem of a maximum weighted independent set (MWIS), which has been proven to be NP-hard. Several suboptimal scheduling algorithms have been proposed to approximate throughput optimality with low computation complexity [20,21,22,23]. A popular algorithm is greedy maximal scheduling (also known as the longest-queue-first policy), which is based on the greedy MWIS algorithm, in [20].…”

Section: Introductionmentioning

confidence: 99%

Distributed Rate-Control and Delay-Guaranteed Scheduling in MR-MC Wireless Mesh Networks

Zhao

Geng

2019

Sensors

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Wireless mesh networks (WMNs) can provide flexible wireless connections in smart city, Internet of Things (IoT), and device-to-device (D2D) communications. The performance of WMNs can be greatly enhanced by adopting the multi-radio multi-channel (MR-MC) technique, which enables a node to communicate with more nodes simultaneously. However, increasing the number of data flows will result in network congestion and longer end-to-end delays. In this paper, a distributed rate-control and delay-aware (DRDA) scheduling algorithm is proposed based on a multidimensional conflict graph. To satisfy the arrival rate and delay constraints of a flow, two virtual queues are constructed. All the actual and virtual queues are stabilized by the Lyapunov drift optimization method. The scheduling policy of each flow is optimized only based on the local information. The simulation results show that our proposed algorithm can maintain the stability of all the queues and strictly satisfy the arrival rate and delay constraint of each flow in the network as well.

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Backpressure Delay Enhancement for Encounter-Based Mobile Networks While Sustaining Throughput Optimality

Cited by 26 publications

References 52 publications

Workload scheduling toward worst‐case delay and optimal utility for single‐hop Fog‐IoT architecture

Workload scheduling toward worst‐case delay and optimal utility for single‐hop Fog‐IoT architecture

Shortest‐path‐based back‐pressure routing with single‐FIFO queueing in ad hoc networks'

Distributed Rate-Control and Delay-Guaranteed Scheduling in MR-MC Wireless Mesh Networks

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