Energy-Efficient Sensing in Wireless Sensor Networks Using Compressed Sensing

Razzaque, Mohammad A.; Dobson, Simon

doi:10.3390/s140202822

Cited by 156 publications

(109 citation statements)

References 68 publications

(231 reference statements)

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“…Typical values for the distribution of different energy consumers are from [9] and [12]. Energy harvesting increases the lifetime of the battery assisted device (N H ) by ∼30% for low-power sensor devices (such as temperature, pressure, and light sensors).…”

Section: A Scenario I: Uniform Distribution In a Ring Topologymentioning

confidence: 99%

Wireless energy harvesting for the Internet of Things

et al. 2015

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Internet of Things (IoT) is an emerging computing concept that describes a structure in which everyday physical objects, each provided with unique identifiers, are connected to the Internet without requiring human interaction.Long-term and self-sustainable operation are key components for realization of such a complex network, and entail energy-aware devices that are potentially capable of harvesting their required energy from ambient sources. Among different energy harvesting methods such as vibration, light and thermal energy extraction, wireless energy harvesting (WEH) has proven to be one of the most promising solutions by virtue of its simplicity, ease of implementation and availability. In this article, we present an overview of enabling technologies for efficient WEH, analyze the life-time of WEH-enabled IoT devices, and briefly study the future trends in the design of efficient WEH systems and research challenges that lie ahead.

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Section: A Scenario I: Uniform Distribution In a Ring Topologymentioning

confidence: 99%

Wireless energy harvesting for the Internet of Things

et al. 2015

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“…Still concerning video coding, the compressive sensing paradigm exploits the information rate within a particular signal, removing redundancy in the signal during the sampling process [58,59]. As compression is performed "during" sensing functions, encryption before transmission may also be relieved, which may benefit security mechanisms.…”

Section: Video Cryptographymentioning

confidence: 99%

Cryptography in Wireless Multimedia Sensor Networks: A Survey and Research Directions

2017

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Wireless multimedia sensor networks will play a central role in the Internet of Things world, providing content-rich information for an uncountable number of monitoring and control scenarios. As more applications rely on multimedia data, security concerns gain attention, and new approaches arise to provide security for such networks. However, the usual resource constraints of processing, memory and the energy of multimedia-based sensors have brought different challenges for data encryption, which have driven the development of different security approaches. In this context, this article presents the state-of-the-art of cryptography in wireless multimedia sensor networks, surveying innovative works in this area and discussing promising research directions.

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“…One other advantage of clustered routing is better traffic balancing, which makes the clustering approach preferable choice over the tree based routing scheme. A theoretical analysis presented in [14] proves the efficiency of the compressed data gathering. Aiming the network energy consumption, the authors in [15] proposed a greedy heuristic solution which uses CS with joint routing protocol.…”

Section: Related Workmentioning

confidence: 99%

“…To overcome these drawbacks, the idea of hybrid CS was proposed but hybrid CS has its own disadvantages. The selection of non-CS and CS points within the hybrid-CS scheme is critical in getting the benefit of CS [13], [14], [15]. Distributed CS [23] suffers as compared to a mixed protocol in large-scale WSNs, under real technological constrains.…”

Section: Related Workmentioning

confidence: 99%

Hierarchical Compressed Sensing for Cluster Based Wireless Sensor Networks

Singh¹,

Kumar²

2016

ijacsa

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Abstract-Data transmission consumes significant amount of energy in large scale wireless sensor networks (WSNs). In such an environment, reducing the in-network communication and distributing the load evenly over the network can reduce the overall energy consumption and maximize the network lifetime significantly. In this work, the aforementioned problem of network lifetime and uneven energy consumption in large scale wireless sensor networks is addressed. This work proposes a hierarchical compressed sensing (HCS) scheme to reduce the innetwork communication during the data gathering process. Corelated sensor readings are collected via a hierarchical clustering scheme. A compressed sensing (CS) based data processing scheme is devised to transmit the data from the source to the sink. The proposed HCS is able to identify the optimal position for the application of CS to achieve reduced and similar number of transmissions on all the nodes in the network. An activity map is generated to validate the reduced and uniformly distributed communication load of the WSN. Based on the number of transmissions per data gathering round, the bit-hop metric model is used to analyse the overall energy consumption. Simulation results validate the efficiency of the proposed method over the existing CS based approaches.

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Energy-Efficient Sensing in Wireless Sensor Networks Using Compressed Sensing

Cited by 156 publications

References 68 publications

Wireless energy harvesting for the Internet of Things

Wireless energy harvesting for the Internet of Things

Cryptography in Wireless Multimedia Sensor Networks: A Survey and Research Directions

Hierarchical Compressed Sensing for Cluster Based Wireless Sensor Networks

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