Energy-Efficient Communication Using Data Aggregation and Data Compression Techniques in Wireless Sensor Networks: A Survey

Pushpalatha, S.; Shivaprakasha, K. S.

doi:10.1007/978-981-15-0626-0_14

Cited by 21 publications

(15 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Data aggregation techniques is one of the most researched areas for energy efficiency in WSNs. It is noticeable that only in the last two years several surveys can be found in the literature in its field [ 59 , 60 , 61 , 62 ].…”

Section: Energy Conservationmentioning

confidence: 99%

Current Trends on Green Wireless Sensor Networks

López-Ardao

Rodríguez-Rubio

Suárez-González

et al. 2021

Sensors

View full text Add to dashboard Cite

The issue of energy balancing in Wireless Sensor Networks is a pivotal one, crucial in their deployment. This problem can be subdivided in three areas: (i) energy conservation techniques, usually implying minimizing the cost of communication at the nodes since it is known that the radio is the biggest consumer of the available energy; (ii) energy-harvesting techniques, converting energy from not full-time available environmental sources and usually storing it; and (iii) energy transfer techniques, sharing energy resources from one node (either specialized or not) to another one. In this article, we survey the main contributions in these three areas and identify the main trending topics in recent research. A discussion and some future directions are also included.

show abstract

Section: Energy Conservationmentioning

confidence: 99%

Current Trends on Green Wireless Sensor Networks

López-Ardao

Rodríguez-Rubio

Suárez-González

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…Hence, passing out redundant data decreases the volume of data transmitted along with the energy expenditure and the latency associated. This is why there is need for novel data aggregation schemes [166][167][168]. Likewise, the use of compression and restoration schemes provides substantial reduction of communication load [169][170][171].…”

Section: Open Research Issuesmentioning

confidence: 99%

Energy Efficient Routing in Wireless Sensor Networks: A Comprehensive Survey

2020

View full text Add to dashboard Cite

Wireless Sensor Networks (WSNs) are among the most emerging technologies, thanks to their great capabilities and their ever growing range of applications. However, the lifetime of WSNs is extremely restricted due to the delimited energy capacity of their sensor nodes. This is why energy conservation is considered as the most important research concern for WSNs. Radio communication is the utmost energy consuming function in a WSN. Thus, energy efficient routing is necessitated to save energy and thus prolong the lifetime of WSNs. For this reason, numerous protocols for energy efficient routing in WSNs have been proposed. This article offers an analytical and up to date survey on the protocols of this kind. The classic and modern protocols presented are categorized, depending on i) how the network is structured, ii) how data are exchanged, iii) whether location information is or not used, and iv) whether Quality of Service (QoS) or multiple paths are or not supported. In each distinct category, protocols are both described and compared in terms of specific performance metrics, while their advantages and disadvantages are discussed. Finally, the study findings are discussed, concluding remarks are drawn, and open research issues are indicated.

show abstract

“…Hence, data compression techniques have been used in numerous works to reduce the size of the data set that needs to be processed and exchanged to achieve energy efficiency at both computation and communication phases [173]- [175]. Most of the proposed data compression algorithms attempt to enhance the compression ratio that can be interpreted as the degree to which the redundant data is removed while maintaining a particular Root Mean Square Error (RMSE) and SNR are essential considerations in the IoWT applications [55].…”

Section: H Data Compressionmentioning

confidence: 99%

“…A, N, SW [46], [111] Energy awareness regarding neighboring nodes to select the optimal route [50] Multi parameter cost function for the next hop selection [60] Selective data routing based on the data priority Securityrelated aspects HW, DP, SW [110] Content agnostic privacy and encryption protocol eliminating the need for asymmetric encryption [180], [181] Integration of lightweight cryptography solutions including more appropriate elliptic curve types or algorithm implementations [186] More efficient utilization of manufacturer-provide SoCs accelerated for cryptographic primitives execution [187] Finding trade-offs between the primitive and required level of the provided security Processing limitations HW, DP, SW [54] The use of heterogeneous multicore processor gateway as compared to little cores gateway working as a router [64], [86], [104], [105] Task offloading to leverage high computing resources of nearby devices for improved performance [106] Edge/fog/cloud computing techniques for optimal performance [107] Seamless resource sharing between heterogeneous mobile devices Storage limitations HW [47], [55] Data compression to reduce the size of the dataset for efficient data processing and storage [106] Edge/Fog/Cloud computing techniques for better performance [173] Data summarization and aggregation Lack of hardware acceleration HW, SW [47], [55] Data compression to reduce the size of the data set for more efficient data processing and storage [64], [86], [104], [105] Task offloading to leverage high computing resources of the nearby devices for the improved performance [186] Identifying and use of present hardware acceleration, which may not be accessible by the default Inefficient use of energy consuming modules HW, SW [62] Configurable data acquisition modules [88] Replacing high power consumption modules with low power alternates, e.g., using two accelerometers instead of a gyroscope as...…”

Section: Inefficient Routingmentioning

confidence: 99%

Towards Energy Efficiency in the Internet of Wearable Things: A Systematic Review

et al. 2020

View full text Add to dashboard Cite

Personal mobile devices such as smartwatches, smart jewelry, and smart clothes have launched a new trend in the Internet of Things (IoT) era, namely the Internet of Wearable Things (IoWT). These wearables are small IoT devices capable of sensing, storing, processing, and exchanging data to assist users by improving their everyday life tasks through various applications. However, the IoWT has also brought new challenges for the research community to address such as increasing demand for enhanced computational power, better communication capabilities, improved security and privacy features, reduced form factor, minimal weight, and better comfort. Most wearables are battery-powered devices that need to be recharged-therefore, the limited battery life remains the bottleneck leading to the need to enhance the energy efficiency of wearables, thus, becoming an active research area. This paper presents a survey of energy-efficient solutions proposed for diverse IoWT applications by following the systematic literature review method. The available techniques published from 2010 to 2020 are scrutinized, and the taxonomy of the available solutions is presented based on the targeted application area. Moreover, a comprehensive qualitative analysis compares the proposed studies in each application area in terms of their advantages, disadvantages, and main contributions. Furthermore, a list of the most significant performance parameters is provided. A more in-depth discussion of the main techniques to enhance wearables' energy efficiency is presented by highlighting the trade-offs involved. Finally, some potential future research directions are highlighted.

show abstract

Energy-Efficient Communication Using Data Aggregation and Data Compression Techniques in Wireless Sensor Networks: A Survey

Cited by 21 publications

References 24 publications

Current Trends on Green Wireless Sensor Networks

Current Trends on Green Wireless Sensor Networks

Energy Efficient Routing in Wireless Sensor Networks: A Comprehensive Survey

Towards Energy Efficiency in the Internet of Wearable Things: A Systematic Review

Contact Info

Product

Resources

About