Delay-Optimal Back-Pressure Routing Algorithm for Multihop Wireless Networks

Long, Hai; Gao, Qinghua; Wang, Jie; He, Zuyuan; Wang, Ping

doi:10.1109/tvt.2017.2770183

Cited by 32 publications

(23 citation statements)

References 35 publications

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“…The back-pressure method works based on local data and node decisions for routing [42]. In fact, this method is not meant to select a specific route at the beginning or even the start of transmission, but rather helps each node decide to which node a packet should be transmitted for the subsequent delivery to the sink.…”

Section: ) the Back-pressure Congestion Control Methodsmentioning

confidence: 99%

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

et al. 2020

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The classical Internet of things routing and wireless sensor networks can provide more precise monitoring of the covered area due to the higher number of utilized nodes. Because of the limitations in shared transfer media, many nodes in the network are prone to the collision in simultaneous transmissions. Medium access control protocols are usually more practical in networks with low traffic, which are not subjected to external noise from adjacent frequencies. There are preventive, detection and control solutions to congestion management in the network which are all the focus of this study. In the congestion prevention phase, the proposed method chooses the next step of the path using the Fuzzy decision-making system to distribute network traffic via optimal paths. In the congestion detection phase, a dynamic approach to queue management was designed to detect congestion in the least amount of time and prevent the collision. In the congestion control phase, the back-pressure method was used based on the quality of the queue to decrease the probability of linking in the pathway from the pre-congested node. The main goals of this study are to balance energy consumption in network nodes, reducing the rate of lost packets and increasing quality of service in routing. Simulation results proved the proposed Congestion Control Fuzzy Decision Making (CCFDM) method was more capable in improving routing parameters as compared to recent algorithms. INDEX TERMS Internet of Things, wireless sensor network, congestion control, fuzzy decision making, and back-pressure.

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Section: ) the Back-pressure Congestion Control Methodsmentioning

confidence: 99%

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

et al. 2020

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“…Besides the above methods, some delay-based methods are proposed to improve the delay of back-pressure routeing [6,13,14]. In [13], Gao et al propose a machine-learning-based method which adopts general measurements as the features injecting into a specific Q-learning to reduce packet delay.…”

Section: Related Workmentioning

confidence: 99%

“…Wu et al [14] propose a delay-based method which uses packet delay instead of the queue length in the calculation of data pressure. Our previous work gives another delay-based method which uses an accumulated packet delays as the backlog in the back-pressure calculation [6]. Although the above work can be proven to effectively reduce network latency while maintaining the throughput optimality of routeing, they still need large computing resource and space resource to calculate the delays of packets.…”

Section: Related Workmentioning

confidence: 99%

“…In the simulation, we call our routeing scheme Shortest-path Single-queue based Back-Pressure routing (SSBP) and compare it with Back-Pressure routing (BP) [17], Back-Pressure routing with Shortest Path (BPSP) [10], and Delay based Back-Pressure routing (DBP) [6]. BP is the traditional back-pressure routeing.…”

Section: Simulation Settingsmentioning

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%

See 2 more Smart Citations

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

2019

Self Cite

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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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Centralized Multicasting AODV Routing Protocol Optimized for Intermittent Cognitive Radio Ad Hoc Networks

Phaswana

Velempini

2023

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Delay-Optimal Back-Pressure Routing Algorithm for Multihop Wireless Networks

Cited by 32 publications

References 35 publications

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

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

Centralized Multicasting AODV Routing Protocol Optimized for Intermittent Cognitive Radio Ad Hoc Networks

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