Reliable and energy efficient cooperative relaying scheme (REECR) in wireless sensor networks

Zheng, Wenying; Rahman, Kazi Atiqur; Tepe, Kemal

doi:10.1109/iwcmc.2013.6583592

Cited by 4 publications

(3 citation statements)

References 16 publications

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“…For example, a detailed overview of cooperative communication concept based on replacement of direct communication link between source and destination with several shorter links using relays is given in Pejanovic‐Djurisic et al 27 Energy efficiency of relay‐assisted transmissions over fading wireless channel has been studied analytically by Chandra et al 28 where the efficiency is found to be heavily dependent on the relay location. In this paper, a reliable and energy efficient multi‐hop communications in WSNs is studied by Zheng et al, 29 where a set of RNs and power control is used for path loss savings. The total transmission power constraint and the minimum required rate constraints have been studied as an optimization problem in Bossy et al 30 to improve energy efficiency of different types of wireless networks.…”

Section: Related Workmentioning

confidence: 99%

Modulated relay based stable election protocol for large‐scale wireless sensor networks

Hamad

Dağ

Gucluoglu

2022

Int J Communication

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Summary Internet of things (IoT) applications based on wireless sensor networks (WSNs) have recently gained vast momentum. These applications vary from health care, smart cities, and military applications to environmental monitoring and disaster prevention. As a result, energy consumption and network lifetime have become the most critical research area of WSNs. Through energy‐efficient routing protocols, it is possible to reduce energy consumption and extend the network lifetime for WSNs. Using hybrid routing protocols that incorporate multiple transmission methods is an effective way to improve network performance. This paper proposes modulated R‐SEP (MR‐SEP) for large‐scale WSN‐based IoT applications. MR‐SEP is based on the well‐known stable election protocol (SEP). MR‐SEP defines three initial energy levels for the nodes to improve the network energy distribution and establishes multi‐hop communication between the cluster heads (CHs) and the base station (BS) through relay nodes (RNs) to reduce the energy consumption of the nodes to reach the BS. In addition, MR‐SEP reduces the replacement frequency of CHs, which helps increase network lifetime and decrease power consumption. Simulation results show that MR‐SEP outperforms SEP, LEACH, and DEEC protocols by 70.2%, 71.58%, and 74.3%, respectively, in terms of lifetime and by 86.53%, 86.68%, and 86.93% in terms of throughput.

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Section: Related Workmentioning

confidence: 99%

Modulated relay based stable election protocol for large‐scale wireless sensor networks

Hamad

Dağ

Gucluoglu

2022

Int J Communication

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“…For instance, some of them are integrated with the MAC layer and the transport layer protocols. Such strategies include the Node Density based Clustering and Mobile collection (NDCM) [117] , the Reliable and Energy Efficient Cooperative Relaying scheme (REECR) [118] which improves the Energy Efficiency through the cooperation among the nodes equipped with power control functions and the adoption of the Cooperative Automatic Repeat reQuest, the Load Balanced Clustering and Dual Data Uploading (LBC-DDU) [119] which achieves the goals of prolonging the Network Life, reducing network latency, and obtaining a high reliability at the same time, the Network Coding-based Cooperative Communications scheme (NCCC) which applies NC to achieve energy conservation and communication reliability [120] , the Energy Efficient Relay and Minimum Distance algorithm (EERMD) which comprehensively considers the influence of CHs and the relays on the Energy Efficiency [121] , etc. In addition, there are also some other strategies which combines with the EEMAC, such as the Channel-aware RN Placement method (CRNP) [122] which is integrated with the MAC layer to regulate the trajectory of relays and comprehensively takes the channel utilization of nodes into consideration to reduce energy consumption resulted from idle listening.…”

Section: Acm T S Nmentioning

confidence: 99%

“…Therefore, energy overhead can be cut down by means of reducing the amount of data transmission. For example, in some scenarios where the data generate in a burst mode, the energy overhead can be diminished through the reduction in the frequency of data acquisition [118] . Besides, the characteristics of data correlation in WSNs also needs to be alleviated through simple aggregation at each CH to reduce the energy overhead resulted from data redundancy.…”

Section: Classifications Of Eecsmentioning

confidence: 99%

A Survey on Energy-Efficient Strategies in Static Wireless Sensor Networks

Lin

Wang

Min

et al. 2020

ACM Trans. Sen. Netw.

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A comprehensive analysis on the energy-efficient strategy in static Wireless Sensor Networks (WSNs) which are not equipped with any energy harvesting modules was conducted in this paper. Firstly, a novel generic mathematical definition of Energy Efficiency was proposed, which took the acquisition rate of valid data, the total energy consumption, and the network lifetime of WSNs into consideration simultaneously. To the best of our knowledge, it is for the first time that the Energy Efficiency of WSNs is mathematically defined. The energy consumption characteristics of each individual sensor node and the whole network were expounded at length. Accordingly, the concepts concerning the Energy Efficiency, namely the Energy-efficient Means, the Energy-efficient Tier, and the Energy-efficient Perspective, were proposed. Subsequently, the relevant energy-efficient strategies proposed from 2002 to 2019 were tracked and reviewed. Specifically, they were classified into five categories, i.e., the Energy-Efficient Media Access Control (EEMAC) protocol, the Mobile Node Assistance Scheme (MNAS), the Energy-Efficient Clustering Scheme (EECS), the Energy-Efficient Routing Scheme (EERS), and the Compress Sensing based Scheme (CSS) respectively. A detailed elaboration on both the basic principle and the evolution of them was made. Finally, further analysis on the categories was made and the related conclusion was drawn. To be specific, the interdependence among them, the relationships between each of them and the Energy-efficient Means, the Energy-efficient Tier as well as and the Energy-efficient Perspective were analyzed in detail. Besides, the specific applicable scenarios for each of them and the relevant statistics analysis were detailed. The proportion and the number of citations of each category were illustrated by the statistical chart. In addition, the existing opportunities and challenges facing WSNs in the context of the new computing paradigm, and the feasible direction concerning the energy efficiency in the future were pointed out.

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