Joint Routing and Channel Assignment for Delay Minimization in Multi-Channel Multi-Flow Mobile Cognitive Ad Hoc Networks

Zhou, Tong; Tang, Feilong; Li, Jie; Yang, Yanqin; Xu, Wenchao; Yao, Bin; Guo, Minyi

doi:10.1109/glocom.2014.7417505

Cited by 2 publications

(6 citation statements)

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“…Multi-objective differential evolution identifies a set of optimal routes with different possible tradeoffs between energy consumption and delay for a communication between 2 nodes. Some literature in CR systems (eg, Tang et al, 2 Abbagnale and Cuomo, 24 Chowdhury and Felice, 25 Filippini et al, 26 Zhu et al, 27 Feng et al, 28 and Zhou et al 29,30 ) propose algorithms based on the path stability. Abbagnale and Cuomo 24 address the link availability in terms of the path connectivity based on the Laplacian spectrum of the graph in mobile CRAHNs.…”

Section: Discussionmentioning

confidence: 99%

“…Some literature in CR systems (eg, Tang et al, Abbagnale and Cuomo, Chowdhury and Felice, Filippini et al, Zhu et al, Feng et al, and Zhou et al) propose algorithms based on the path stability. Abbagnale and Cuomo address the link availability in terms of the path connectivity based on the Laplacian spectrum of the graph in mobile CRAHNs.…”

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

“…In Zhou et al and Tang et al, the authors formulate the joint routing and channel assignment problem with the objective of the delay minimization. Zhou et al presents the Joint Routing and Channel Assignment problem to minimize the end‐to‐end delay in mobile CRAHNs. Zhou et al propose the Joint Channel assignment, stable Routing, and adaptive Power control algorithm which controls the transmission power to avoid the channel interference and improves the channel utilization in mobile CRAHNs.…”

Section: Related Workmentioning

confidence: 99%

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Joint load balanced stable routing and communication segment assignment in mobile cognitive radio ad‐hoc networks

Amiri-Doomari

Mirjalily

Abouei

2018

Int J Communication

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Summary The fundamental issues in mobile cognitive radio ad‐hoc networks are the selection of the optimal stable paths between nodes and proper assignment of the frequency channels/time slots (communication segments) to the links. In this paper, a joint load balanced stable routing and communication segment assignment algorithm is proposed that considers jointly the mobility prediction, mitigating the co‐channel interference and energy consumption. The novelty of the proposed algorithm lies in the increasing of the path stability, which benefits from the maximum link lifetime parameter and introduced weighting function to keep routes away from the PU's region. This avoids the negative impacts on the PUs' operations and decreases the conflict of the cognitive nodes. In the proposed algorithm, the concept of load balancing is considered that yields in the balancing energy consumption in the network, improving the network performance and distributing traffic loads on all available channels. The effectiveness of the proposed algorithm is verified by evaluating the aggregate interference energy, average end‐to‐end delay, goodput, and the energy usage per packet under 6 scenarios. The results show that the performance of the proposed algorithm is significantly better than the recently proposed joint stable routing and channel assignment protocol.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Joint load balanced stable routing and communication segment assignment in mobile cognitive radio ad‐hoc networks

Amiri-Doomari

Mirjalily

Abouei

2018

Int J Communication

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“…The delay prediction model in JRCA [104] is used to minimize delay based on channel collision probability. The model predicts transmission time and media access time to detect any channel interference among different primary and secondary nodes.…”

Section: Delay-aware Routing Protocols For Static Crsnsmentioning

confidence: 99%

A Survey on Routing Protocols for Delay and Energy-Constrained Cognitive Radio Networks

2020

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The ever-growing demand for higher network data rates, lower delay, and conservative energy consumption at reduced costs, to support Internet-of-things (IoT) communications, has pushed wireless technologies into a new frontier. The growing demand for such technologies can be attributed to several factors, such as the massive number of the upcoming bandwidth-hungry IoT applications and the enormous number ofoften battery-powereddevices expected to connect to the network. Cognitive Radio Networks (CRNs) can play a significant role in future generations of mobile-communication technologies by providing dynamic access to underutilized licensed bands. However, battery-operated devices, which communicate delay-sensitive data over multihop links, impose serious energy-delay limits. In such CRN-based IoT communications, as one device depletes its energy, network disconnectivity may arise, which can degrade the network efficiency. Therefore, building a reactive routing protocol to recover from any sudden link breakage is necessary to maintain prolonged network connectivity. This paper provides a comprehensive survey of CRN routing protocols that are based on two essential metrics, namely, packet delay, energy consumption, or both, while excluding all other CRN routing protocols. The survey is meant to support the designers of future CRN-based IoT communication frameworks with a detailed comparative survey, which targets the most relevant proposed routing protocols, including the specifics of the routing metrics, implemented spectrum awareness strategy, and employed medium-access control standard along with the simulator tool used for performance evaluation. In addition, this survey finds that the majority of cognitive radio routing protocols address either delay or energy consumption, but only a few consider a joint delay-energy metric, which suits delay-sensitive IoT applications running on energy-constrained devices. INDEX TERMSCognitive Radio, Delay, Energy, Internet-of-things, Routing, Sensor Network I. INTRODUCTIONThe rapid expansion of wireless devices has enabled the extensive use of various real-time applications. Some of these applications serve classified information for the military, while others serve the civil defense, fire systems, healthcare, home appliances, and e-commerce transactions. Several applications serve multimedia communications such as video conferencing, Internet telephony, and chatting, while others serve online gaming and entertainment communications. Some of these applications have delay and energy constraints due to the urgency of the carried information and the energy-limited devices used. Users of such applications often seek to avoid service disruption and depletion of their device battery whileat the same timeassuring immediate information transfer at a high delivery rate.The Internet-of-things (IoT) paradigm [1] [2] enables the interaction between devices from several application domains that includebut not limited to mobile phones, routers, game consoles, printers, pacemakers, telepho...

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Joint Routing and Channel Assignment for Delay Minimization in Multi-Channel Multi-Flow Mobile Cognitive Ad Hoc Networks

Cited by 2 publications

References 12 publications

Joint load balanced stable routing and communication segment assignment in mobile cognitive radio ad‐hoc networks

Joint load balanced stable routing and communication segment assignment in mobile cognitive radio ad‐hoc networks

A Survey on Routing Protocols for Delay and Energy-Constrained Cognitive Radio Networks

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