A QoS MAC protocol for prioritized data in energy harvesting wireless sensor networks

Sarang, Sohail; Drieberg, Micheal; Awang, Azlan; Ahmad, Rizwan

doi:10.1016/j.comnet.2018.07.022

Cited by 32 publications

(34 citation statements)

References 35 publications

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“…By presenting the AP-MAC protocol, they had achieved better higher throughput and higher efficiency. Sohail Sarang et al [14] had illustrated a QoS aware MAC protocol in energy harvesting WSN. The authors aimed to minimize the delay for data transmission.…”

Section: Related Workmentioning

confidence: 99%

Fuzzy Based Enhanced Medium Access Control protocol for Wireless Sensor Networks

Tamilarasi*,

Santhi

2020

IJRTE

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Wireless Sensor Networks (WSNs) have increased huge consideration because of their wide scope of utilizations. In these networks, the sensor hubs gather various kinds of information from the general condition. During the transmission of collected data packets, some of them will be dropped due to the collision of packets. So, collide packets are retransmitted which may lead the network to high energy consumption. As Medium Access Control (MAC) protocol has responsible for reliable communication in WSN, an enhanced MAC protocol has to be proposed for improving energy efficiency of the network. By considering this solution, Fuzzy Based Enhanced Medium Access Control protocol (Fuzzy-MAC) is proposed in this paper. Before transmission, data packets are prioritized using the Fuzzy system. Then the packets are transmitted in light of the need of the parcels. Simulation results show that the exhibition of the proposed Fuzzy-MAC beats that of existing MAC protocols as far as energy utilization, delivery ratio and throughput.

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Section: Related Workmentioning

confidence: 99%

Fuzzy Based Enhanced Medium Access Control protocol for Wireless Sensor Networks

Tamilarasi*,

Santhi

2020

IJRTE

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“…The procedure of transforming a crisp input value to a fuzzy value that is executed by the use of the data in the knowledge base. Fuzzification process commonly uses Gaussian, triangular and trapezoidal representation curves [14]. Fuzzy Implication System consists of five processes: (i) Fuzzification of the crisp inputs (ii) Apply Fuzzy operator in the ancestor (iii) Implication from the ancestor to the subsequent (iv) Aggregation of the consequents across the rules (v) Defuzzification.…”

Section: Fuzzy Implication System (Fis)mentioning

confidence: 99%

Secure Routing with Improved Medium Access Control (SRI-MAC) Protocol for Wireless Sensor Network using Particle Swarm Optimization

Tamilarasi¹,

Santhi²

2019

IJEAT

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A set of wireless sensor nodes comprises to form a sensor field called Wireless Sensor Networks (WSN).The main purpose of using the sensor node is to collect information from the ambience process it and send to a common gateway interface called Base Station(BS). The major problems that we face while using WSN are limited battery power, bandwidth, security issues and transmission delay etc. Many algorithms and protocols were developed in order to solve the above issues. Therefore, better solutions are required to face the improvements and challenges in the current technologies. In WSN, the sensor node highly loses its energy during communication period. One of the major issues of Medium Access Control (MAC) layer is collision. Collision increases the energy consumption and delay of the sensor node. So we have to conserve the energy of the sensor node in order to extend the lifetime of the network. At the same time it is also important to transmit the data through secure path and identify the malicious node. In this paper, we propose a novelty approach called Secure Routing with Improved Medium Access control (SRI –MAC) Protocol to solve the issues. SRIMAC identifies packet precedence sets using Fuzzy Implication System (FIS) to avoid packet collision in MAC layer and also it detects wormhole attacks and selects secure path among k-paths using Particle Swarm Optimization (PSO) algorithm. By simulation results, we show that the proposed approach is efficient in terms of energy consumption and secure routing.

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“…Under the senderinitiated MAC protocol, when a sender has data to be transmitted, the sender listens to and polls the channel, and if the receiver is awake, the receiver can receive the data transmitted by the sender and establish a communication, resulting in data transmission. Under the receiver-initiated MAC protocol, when the sender must transmit data, it does not initiate data transmission and must wait for a beacon from the receiver indicating that the receiver is ready to receive data [41]. When the receiver wakes, it actively sends the beacon to receive data and initiate communication.…”

Section: Introductionmentioning

confidence: 99%

“…When the receiver wakes, it actively sends the beacon to receive data and initiate communication. As the sender waits for the beacon, it can communicate with other receivers until achieving data transmission [41].…”

Section: Introductionmentioning

confidence: 99%

“…In most sensor-cloud systems, sensing devices are relatively dense, and there are always multiple sensing devices with data to transmit at the same time within a communication range; in other words, there are a manyto-one cases of communication in which multiple senders must transmit data to the same receiver [39]. Data from different senders usually is of varying priority [41], and of course high priority data must be transmitted first, as this is good for the system [41]. For example, in an emergency, alarm data should be transmitted first while less important data such as daily life data can be transmitted later.…”

Section: Introductionmentioning

confidence: 99%

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Energy-aware MAC protocol for data differentiated services in sensor-cloud computing

et al. 2020

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The energy-aware MAC protocol is the basic communication protocol for device-to-device communication in sensor-cloud computing and facilitates data sensing, computing, and sharing for applications. Transmitting highpriority data to control centers quickly to manage emergencies is essential for sensor-cloud applications. In this paper, a Dynamic Wait time-based MAC (DWT-MAC) protocol is proposed for data differentiated services of a sensor-cloud system (SCS). The DWT-MAC protocol is novel in that it changes the receiver wait time, which has been fixed in previous MAC protocols, and it reduces the delay in data transmission by dynamically adjusting the wait time. In the DWT-MAC protocol, the wait time changes according to the number of senders, which can ensure that it always approaches the optimal value. A dynamic time adjustment algorithm, which causes the wait time to always trail the optimal value, is proposed to reduce delays. While the DWT-MAC protocol cannot ensure wait times of the optimal value, it can ensure that it quickly comes close to the optimal value, which is suitable for dynamically changing networks. Extensive experiments show that the DWT-MAC protocol reduces the average delay in the transmission of data of the highest priority by 49.3%.

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A QoS MAC protocol for prioritized data in energy harvesting wireless sensor networks

Cited by 32 publications

References 35 publications

Fuzzy Based Enhanced Medium Access Control protocol for Wireless Sensor Networks

Fuzzy Based Enhanced Medium Access Control protocol for Wireless Sensor Networks

Secure Routing with Improved Medium Access Control (SRI-MAC) Protocol for Wireless Sensor Network using Particle Swarm Optimization

Energy-aware MAC protocol for data differentiated services in sensor-cloud computing

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