SEER: spectrum- and energy-efficient routing protocol for cognitive radio ad hoc networks

Hou, Ling; Yeung, K.H.; Wong, Kin-Yeung

doi:10.1007/s11276-015-0906-3

Cited by 5 publications

(3 citation statements)

References 19 publications

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“…The network's lifetime in addition to energy consumption of nodes is considered as metrics by the authors in [44]. Based on the existing several packets within the queue of the nodes in addition to the usual energy usage per packet, the consumption of energy is computed.…”

Section: Literature Surveymentioning

confidence: 99%

An Enhanced Routing Technique to Improve the Network Lifetime of Cognitive Sensor Network

Jyothi

Subramanyam²

2021

Wireless Pers Commun

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In terms of using the technology of Cognitive Radio (CR), a Cognitive Sensor Network (CSN) is varied from the conventional Wireless Sensor Networks (WSNs). According to the interaction with the surrounding environment, the transmitter parameters can be modified in the sensor nodes of CSN adaptively. In CSNs, routing is one of the important components. Based on the capability of spectrum-aware, the schemes of routing of CSNs are district from other networks. The changeable spectrum resource dynamically should be understood by the routing scheme to establish a path of reliable forwarding by the adjustment of routing policy adaptively. In CSNs, reliable routing is an essential thing but still not a well-explored problem in CSNs. Packet drops due to spectrum unavailability and buffer overflows seriously affects the connectivity of the nodes. The whole network's lifetime and the data delivery rate are impacted by the prolonging packet drops. To increase the nodes' lifetime, the addressing of this drawback in the phase of routing should be done. Before the making of routing decisions, a new routing technique is proposed named as Drop factor based energy efficient routing technique (DFBEER) with the use of packet drop ratio and power dissipation metric of the spectrum links. With the total number of users in the routing path, the drop factor is computed. Power dissipation is calculated based on the transmitted data packets versus the amount of total consumed energy. This method reduces the drop ratio by avoiding the high drop factor nodes from being participating in the routing process. It always ensures that the data would be handled by the low dropping ratio nodes, thus the network's lifetime is improved.

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Section: Literature Surveymentioning

confidence: 99%

An Enhanced Routing Technique to Improve the Network Lifetime of Cognitive Sensor Network

Jyothi

Subramanyam²

2021

Wireless Pers Commun

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“…Synchronization schemes among SUs are needed to distribute the channel availability information periodically. SEER protocol [111] considers the power consumed over the link and the energy consumed by nodes. The number of packets queued at each node is used to estimate the energy each node will consume to forward these packets.…”

Section: ) Static Crnsmentioning

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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“…A utility function is designed to capture the effect of spectrum measurement, fluctuation of bandwidth availability, and path quality. A spectrum-and energy-efficient routing (SEER) protocol for CRAHNs is proposed by Hou et al (2015), which improves transmission efficiency and balances energy consumption. The design of the protocol uses the techniques of expected transmission power, expected residual lifetime and utility indifference curves.…”

mentioning

confidence: 99%

A high reliability and low latency routing algorithm in cognitive wireless mesh networks

Kuang

Chen

2017

IJCNDS

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A channel utility value computing (CUVC) algorithm is proposed. The channel utility value contains channel usage probability and channel stability. A high reliability and low latency wireless link weight computing algorithm (RL2W) is proposed. On this basis, a high reliability and low latency routing and spectrum allocation algorithm based on dynamic programming in cognitive wireless mesh networks (HRL2A) is proposed. High reliability and low latency route is the objective of HRL2A. Firstly, HRL2A computes the channel utility value using CUVC for constructing the high reliability route. Secondly, HRL2A uses the algorithm RL2W computing wireless link weight. Thirdly, the route of high reliability and low latency is constructed based on dynamic programming, and the wireless link channel is allocated. Simulation results show that HRL2A algorithm can achieve expectation goal. The construction route not only has higher reliability, but also has lower latency. The throughput has been increased.

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SEER: spectrum- and energy-efficient routing protocol for cognitive radio ad hoc networks

Cited by 5 publications

References 19 publications

An Enhanced Routing Technique to Improve the Network Lifetime of Cognitive Sensor Network

An Enhanced Routing Technique to Improve the Network Lifetime of Cognitive Sensor Network

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

A high reliability and low latency routing algorithm in cognitive wireless mesh networks

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