Comparative Study of Radio Models for data Gathering in Wireless Sensor Network

Banerjee, Joydeep; Swarup, Kumar Mitra; Mrinal, Kanti Naskar

doi:10.5120/3433-4480

Cited by 15 publications

(5 citation statements)

References 7 publications

(21 reference statements)

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“…In order to measure energy consumption, the first-order radio model was used [11]. Moreover, the parameters used in the performance measurement of the first-order radio model are adapted from it.…”

Section: Related Workmentioning

confidence: 99%

“…There is no hardware changes required to deploy this model on sensor nodes. An energy and network lifetime analysis of the first-order radio model is presented [11].…”

Section: Proposed Workmentioning

confidence: 99%

“…Various assumptions about radio characteristics might be beneficial to different protocols such as energy dissipated in transmitters and receivers. Here, we assume a simple and most commonly used radio model [11] to achieve an acceptable Eb/N0 [12]. En-route filtering schemes, notably, DEF and CCEF, result in a better security at the expense of network lifetime.…”

Section: Introductionmentioning

confidence: 99%

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AEF: Adaptive En-Route Filtering to Extend Network Lifetime in Wireless Sensor Networks

Shahzad

Islam

Kwak

et al. 2019

Sensors

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Static sink-based wireless sensor networks (WSNs) suffer from an energy-hole problem. This incurs as the rate of energy consumption on sensor nodes around sinks and on critical paths is considerably faster. State-of-the-art en-routing filtering schemes save energy by countering false report injection attacks. In addition to their unique limitations, these schemes generally do not examine energy awareness in underlying routing. Mostly, these security methods are based on a fixed filtering capacity, unable to respond to changes in attack intensity. Therefore, these limitations cause network partition(s), exhibiting adverse effects on network lifetime. Extending network lifetime while preserving energy and security thus becomes an interesting challenge. In this article, we address the aforesaid shortcomings with the proposed adaptive en-route filtering (AEF) scheme. In energy-aware routing, the fitness function, which is used to select forwarding nodes, considers residual energy and other factors as opposed to distance only. In pre-deterministic key distribution, keys are distributed based on the consideration of having paths with a different number of verification nodes. This, consequently, permits us to have multiple paths with different security levels that can be exploited to counter different attack intensities. Taken together, the integration of the special fitness function with the new key distribution approach enables the AEF to adapt the underlying dynamic network conditions. The simulation experiments under different settings show significant improvements in network lifetime.

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Section: Related Workmentioning

confidence: 99%

“…There is no hardware changes required to deploy this model on sensor nodes. An energy and network lifetime analysis of the first-order radio model is presented [11].…”

Section: Proposed Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

AEF: Adaptive En-Route Filtering to Extend Network Lifetime in Wireless Sensor Networks

Shahzad

Islam

Kwak

et al. 2019

Sensors

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“…CHs received data from nodes and transmit it to BS. Depending on the distance between transceiver and receiver, we use the first order radio model and free space model in our proposed protocol [30]. We use this model for better comparison with existing protocols [17], [18], [19], [20], [21].…”

Section: Energy Dissipationmentioning

confidence: 99%

Neighbour-Cooperation Heterogeneity-Aware Traffic Engineering for Wireless Sensor Networks

Mumpe¹,

Tang²,

Asad³

et al. 2018

ijacsa

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Extending the operational duration is a major field of interest in Wireless Sensor Networks (WSNs). This lifetime enhancement task challenges researchers to design an energy efficient traffic engineering which minimizes the dissipation energy and retain the expected quality of routing protocols. Network lifetime can be prolonged by balancing the energy optimization throughout the network period over which sensors relay data traffic towards Base Station (BS). Existing techniques of continuous and autonomous reporting sensor nodes, offer an opportunity to design the sensing and reporting co-operation between sensor nodes. Nearby nodes with similar reading environment can cooperate with each other to avoid transmission redundant information. In this paper we propose "Adaptive Inter-Networking Improved (AINI)" multi-hop routing protocol with co-operate sensing of inter and intra cluster communication by exploiting the concept of tripling the sensor nodes. Proposed routing protocol improved the reliability of whole network by improving the reliability of inter-cluster multi-hoping. Sensor nodes use the shortest path to deliver data to CH using intra-cluster multihoping and these CHs are accountable to forward this data to BS using inter-cluster multi-hop communication. Proposed routing protocol resolves the certain issues of WSN like network lifetime, network stability and CHs selection technique. To prove the efficiency of our proposed model we compared the simulation results with existing state-of-the art routing protocols such as, LEACH, LEACH-C, SEP, ESEP and DEEC. Experimental results shows the benefits of neighbour cooperation and heterogeneityaware by the performance of proposed protocol over existing state-of-the-art routing protocols.

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“…This ideal power model facilitates deployment-based optimization but may lead to misleading results. Aslam et al [ 46 ] and Banerjee et al [ 47 ] compared the continuous and discrete power models available from sensor manufacturers in terms of energy consumption and lifetime calculations, and the results show large differences. Guo et al [ 48 ] studied the lifetime optimization problem for a one-tiered linear WSN used to monitor oil pipelines and proposed two efficient placement heuristics that minimized the energy consumption using the realistic discrete power model.…”

Section: Introductionmentioning

confidence: 99%

Deployment-based lifetime optimization for linear wireless sensor networks considering both retransmission and discrete power control

Huang

et al. 2017

PLoS ONE

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A sophisticated method for node deployment can efficiently reduce the energy consumption of a Wireless Sensor Network (WSN) and prolong the corresponding network lifetime. Pioneers have proposed many node deployment based lifetime optimization methods for WSNs, however, the retransmission mechanism and the discrete power control strategy, which are widely used in practice and have large effect on the network energy consumption, are often neglected and assumed as a continuous one, respectively, in the previous studies. In this paper, both retransmission and discrete power control are considered together, and a more realistic energy-consumption-based network lifetime model for linear WSNs is provided. Using this model, we then propose a generic deployment-based optimization model that maximizes network lifetime under coverage, connectivity and transmission rate success constraints. The more accurate lifetime evaluation conduces to a longer optimal network lifetime in the realistic situation. To illustrate the effectiveness of our method, both one-tiered and two-tiered uniformly and non-uniformly distributed linear WSNs are optimized in our case studies, and the comparisons between our optimal results and those based on relatively inaccurate lifetime evaluation show the advantage of our method when investigating WSN lifetime optimization problems.

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Comparative Study of Radio Models for data Gathering in Wireless Sensor Network

Cited by 15 publications

References 7 publications

AEF: Adaptive En-Route Filtering to Extend Network Lifetime in Wireless Sensor Networks

AEF: Adaptive En-Route Filtering to Extend Network Lifetime in Wireless Sensor Networks

Neighbour-Cooperation Heterogeneity-Aware Traffic Engineering for Wireless Sensor Networks

Deployment-based lifetime optimization for linear wireless sensor networks considering both retransmission and discrete power control

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