An Advanced Energy Consumption Model for terrestrial Wireless Sensor Networks

Ahmad, Ashfaq; Javaid, Nadeem; Imran, Muhammad; Guizani, Mohsen; Alhamed, Ahmad A.

doi:10.1109/iwcmc.2016.7577158

Cited by 21 publications

(18 citation statements)

References 9 publications

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“…Sensors are generally energy constrained in practical application scenarios, and it is not cost-effective to change batteries for sensors in general, which reduce the life of WSNs to some extent. The first radio energy model [Ahmad, Javaid, Imran et al (2016)] is applied to calculate the energy consumption during data transmission in this paper. Due to the power dissipation of transmission unit in sensors is much bigger than the sum of other units, we only take energy used in transmission into consideration.…”

Section: Energy Modelmentioning

confidence: 99%

An Asynchronous Clustering and Mobile Data Gathering Schema Based on Timer Mechanism in Wireless Sensor Networks

Wang¹,

Gao²,

Liu³

et al. 2019

Computers, Materials &Amp; Continua

163

115

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Recently, Wireless sensor networks (WSNs) have become very popular research topics which are applied to many applications. They provide pervasive computing services and techniques in various potential applications for the Internet of Things (IoT). An Asynchronous Clustering and Mobile Data Gathering based on Timer Mechanism (ACMDGTM) algorithm is proposed which would mitigate the problem of "hot spots" among sensors to enhance the lifetime of networks. The clustering process takes sensors' location and residual energy into consideration to elect suitable cluster heads. Furthermore, one mobile sink node is employed to access cluster heads in accordance with the data overflow time and moving time from cluster heads to itself. Related experimental results display that the presented method can avoid long distance communicate between sensor nodes. Furthermore, this algorithm reduces energy consumption effectively and improves package delivery rate.

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Section: Energy Modelmentioning

confidence: 99%

An Asynchronous Clustering and Mobile Data Gathering Schema Based on Timer Mechanism in Wireless Sensor Networks

Wang¹,

Gao²,

Liu³

et al. 2019

Computers, Materials &Amp; Continua

163

115

View full text Add to dashboard Cite

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“…The radio energy dissipation of LLN model used in this paper is referred to [37,43]. A node consumes energy in transmitting ETX and receiving ERX of l-bits data over a radio range d according to Eqs.…”

Section: Energy Consumption Of Lln Modelmentioning

confidence: 99%

A QoS-Aware Data Collection Protocol for LLNs in Fog-Enabled Internet of Things

Hosen

Singh

Sharma

et al. 2020

IEEE Trans. Netw. Serv. Manage.

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Improving quality of service (QoS) of low power and lossy networks (LLNs) in internet of things (IoT) is a major challenge. Cluster-based routing technique is an effective approach to achieve this goal. This paper proposes a QoS-aware clustering-based routing (QACR) mechanism for LLNs in Fogenabled IoT which provides a clustering, a cluster head (CH) election, and a routing path selection technique. The clustering adopts the community detection algorithm that partitions the network into clusters with available nodes' connectivity. The CH election and relay node selection both are weighted by the rank of the nodes which take node's energy, received signal strength, link quality, and number of cluster members into consideration as the ranking metrics. The number of CHs in a cluster is adaptive and varied according to a cluster state to balance the energy consumption of nodes. Besides, the protocol uses the CH role handover technique during CH election that decreases the control messages for the periodic election and cluster formation in detail. An evaluation of the QACR has performed through simulations for various scenarios. The obtained results show that the QACR improves the QoS in terms of packet delivery ratio, latency, and network lifetime compared to the existing protocols.

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“…Baranda and others presented the ns-3 framework for modeling hybrid terrestrial-satellite mesh backhaul networks that carry LTE traffic, and a comparison of the different backpressure-based approaches against generic shortest-path routing, in a low-density suburban scenario for LTE networks [5]. Lin and others proposed a beamforming scheme to enhance wireless information and power transfer in terrestrial cellular networks coexisting with satellite networks [6], while Ahmad and others presented an advanced first-order energy consumption model for terrestrial wireless sensor networks [7].…”

Section: Related Workmentioning

confidence: 99%

Exploiting cognitive wireless nodes for priority‐based data communication in terrestrial sensor networks

Bayrakdar

2019

ETRI Journal

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A priority-based data communication approach, developed by employing cognitive radio capacity for sensor nodes in a wireless terrestrial sensor network (TSN), has been proposed. Data sensed by a sensor node-an unlicensed user-were prioritized, taking sensed data importance into account. For data of equal priority, a first come first serve algorithm was used. Non-preemptive priority scheduling was adopted, in order not to interrupt any ongoing transmissions. Licensed users used a nonpersistent, slotted, carrier sense multiple access (CSMA) technique, while unlicensed sensor nodes used a nonpersistent CSMA technique for lossless data transmission, in an energy-restricted, TSN environment. Depending on the analytical model, the proposed wireless TSN environment was simulated using Riverbed software, and to analyze sensor network performance, delay, energy, and throughput parameters were examined. Evaluating the proposed approach showed that the average delay for sensed, high priority data was significantly reduced, indicating that maximum throughput had been achieved using wireless sensor nodes with cognitive radio capacity.

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An Advanced Energy Consumption Model for terrestrial Wireless Sensor Networks

Cited by 21 publications

References 9 publications

An Asynchronous Clustering and Mobile Data Gathering Schema Based on Timer Mechanism in Wireless Sensor Networks

An Asynchronous Clustering and Mobile Data Gathering Schema Based on Timer Mechanism in Wireless Sensor Networks

A QoS-Aware Data Collection Protocol for LLNs in Fog-Enabled Internet of Things

Exploiting cognitive wireless nodes for priority‐based data communication in terrestrial sensor networks

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