Protocols for Wireless Sensor Networks: A Survey

Kochhar, Aarti; Kaur, Pardeep; Singh, Preeti; Sharma, Sukesha

doi:10.26636/jtit.2018.117417

Cited by 34 publications

(17 citation statements)

References 30 publications

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“…LEACH's main disadvantage is that the sensor node with considerably low energy is probable to be selected as the cluster head, and the cluster heads send the data directly to the base station in a single-hop communication. Hence, this method increases the energy consumption of the cluster head [12] [13]. The Stable Election Protocol (SEP) [14] [5] and Distributed Energy-Efficient Clustering (DEEC) [15][5] algorithms have been specifically designed for heterogeneous networks.…”

Section: -Previous Workmentioning

confidence: 99%

Energy Efficient Routing-Based Clustering Protocol Using Computational Intelligence Algorithms in Sensor-Based IoT

Sedighimanesh¹,

Zandhessami²,

Alborzi³

et al. 2021

JIST

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Section: -Previous Workmentioning

confidence: 99%

Energy Efficient Routing-Based Clustering Protocol Using Computational Intelligence Algorithms in Sensor-Based IoT

Sedighimanesh¹,

Zandhessami²,

Alborzi³

et al. 2021

JIST

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“…On the other hand, many of these OSs provide stacks of protocols responsible for managing the wireless communications of the devices. Since the appearance of the first WSNs, researchers have focused on the study of network stacks, which has led to the development of a large number of wireless protocols [12] and even some standards (IEEE 802.15.4, 6LoWPAN, ISA-100.11a). As a result, there are a variety of protocols for the MAC [13,14,15], routing [16,17], and transport [18] layers developed to overcome the different issues present in WSN communications, such as energy-efficiency, latency, scalability, throughput or quality of service (QoS).…”

Section: Related Workmentioning

confidence: 99%

Process Management in IoT Operating Systems: Cross-Influence between Processing and Communication Tasks in End-Devices

Rodriguez-Zurrunero

Utrilla

Rozas

et al. 2019

Sensors

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The emergence and spread of Internet of Things (IoT) technologies along with the edge computing paradigm has led to an increase in the computational load on sensor end-devices. These devices are now expected to provide high-level information instead of just raw sensor measurements. Therefore, the processing tasks must share the processor time with the communication tasks, and both of them may have strict timing constraints. In this work, we present an empirical study, from the edge computing perspective, of the process management carried out by an IoT Operating System (OS), showing the cross-influence between the processing and communication tasks in end-devices. We have conducted multiple tests in two real scenarios with a specific OS and a set of wireless protocols. In these tests, we have varied the processing and communication tasks timing parameters, as well as their assigned priority levels. The results obtained from these tests demonstrate that there is a close relationship between the characteristics of the processing tasks and the communication performance, especially when the processing computational load is high. In addition, these results also show that the computational load is not the only factor responsible for the communication performance degradation, as the relationship between the processing tasks and the communication protocols timing parameters also plays a role. These conclusions should be taken into account for future OSs and protocol developments.

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“…Since the data collected during environmental monitoring is collected for various purposes, quality assurance of emergency is an important consideration [1]- [3]. Also, the energy efficiency of a batteryoperated sensor affects the life of the entire network, so it must be considered [4] [3] [5]. Figure 1.…”

Section: Introductionmentioning

confidence: 99%

“…An important role of Wireless Sensor Networks in these applications is to monitor the target area [6] and deliver data collected from each sensor node [5]. Typically, Wireless Sensor Networks consist of many sensor nodes that make up their multi-hop wireless network.…”

Section: Introductionmentioning

confidence: 99%

Prioritized Energy-Efficient MAC Protocol in Wireless Sensor Networks

Park¹

2021

Int. J. Adv. Sci. Eng. Inf. Technol.

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In this paper, we propose a MAC protocol that provides energy efficiency and QoS for wireless sensor networks. Because it does not classify the data according to the characteristics, traditional MAC protocols for Wireless Sensor Networks cannot provide service differentiations for different traffic classes. For the purpose of QoS support, the input data to the node is divided into priority classes according to the transmission emergency. Depending on the urgency of the data, the protocol can provide time slots for nodes and take different contention window sizes for different traffic classes. Nodes use the reinforcement learning-based control mechanism to actively infer the status of other nodes to classify effectively under various kinds of traffic conditions. The proposed protocol can meet the QoS requirements of delay-sensitive applications and can effectively deal with the problem of a multi-channel hidden terminal with the use of multi-queue. For the next purpose, the proposed protocol is energy efficient because it is based on sleep mode. To improve the energy efficiency, each node has a short non-overlapping listening interval, saving energy in idle listening intervals. This is one of the ways to efficiently use the energy of a node to extend the life of the entire network. This achieves low power consumption by increasing the throughput of data processed across the network and enabling efficient transmission. The classified data can be further improved by rearranging the data according to the nature of the transmitted data in the queue.

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Protocols for Wireless Sensor Networks: A Survey

Cited by 34 publications

References 30 publications

Energy Efficient Routing-Based Clustering Protocol Using Computational Intelligence Algorithms in Sensor-Based IoT

Energy Efficient Routing-Based Clustering Protocol Using Computational Intelligence Algorithms in Sensor-Based IoT

Process Management in IoT Operating Systems: Cross-Influence between Processing and Communication Tasks in End-Devices

Prioritized Energy-Efficient MAC Protocol in Wireless Sensor Networks

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