Journal ArticleDOI
Green Sensing and Communication: A Step Towards Sustainable IoT Systems
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This article surveys the existing green sensing and communication approaches to realize sustainable IoT systems for various applications and presents a few case studies that aim to generate sensed traffic data intelligently as well as prune it efficiently without sacrificing the required service quality.Abstract:
With the advent of Internet of Things (IoT) devices, their reconfigurability, networking, task automation, and control ability have been a boost to the evolution of traditional industries such as health-care, agriculture, power, education, and transport. However, the quantum of data produced by the IoT devices poses serious challenges on its storage, communication, computation, security, scalability, and system’s energy sustainability. To address these challenges, the concept of green sensing and communication has gained importance. This article surveys the existing green sensing and communication approaches to realize sustainable IoT systems for various applications. Further, a few case studies are presented that aim to generate sensed traffic data intelligently as well as prune it efficiently without sacrificing the required service quality. Challenges associated with these green techniques, various open issues, and future research directions for improving the energy efficiency of the IoT systems are also discussed.read more
Citations
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Journal ArticleDOI
An Energy-Efficient Edge Computing Framework for Decentralized Sensing in WSN-Assisted IoT
Vini Gupta,Swades De +1 more
TL;DR: Improved energy efficiency and network energy balance of the proposed framework over the existing closest competitive centralized and decentralized approaches are illustrated.
Journal ArticleDOI
Collaborative Sensing in Internet of Things: A Comprehensive Survey
TL;DR: This article comprehensively survey the sensing mechanism, collaboration and applications in the context of IoT, and highlights that sensing application is coupled with sensing mechanism and sensing collaboration, and discusses promising sensing applications.
Journal ArticleDOI
Green IoT: A Review and Future Research Directions
TL;DR: In this paper , the authors present a thorough examination of energy-efficient practices and strategies for IoT to assist in the advancement of sustainable and energyefficient IoT technologies in the future, including energy efficient machine-to-machine (M2M) communications, energy efficient and eco-sustainable wireless sensor networks (WSN), energy efficient radio-frequency identification (RFID), and energy efficient microcontroller units and integrated circuits (IC).
Journal ArticleDOI
Collaborative Sensing in Internet of Things: A Comprehensive Survey
TL;DR: In this article , a comprehensive survey of collaborative sensing in the context of the Internet of Things is presented, where the authors highlight that sensing application is coupled with sensing mechanism and sensing collaboration, and comprehensively survey the sensing mechanism, collaboration and applications.
Journal ArticleDOI
Edge Intelligence Framework for Data-Driven Dynamic Priority Sensing and Transmission
TL;DR: A novel edge intelligence-based data-driven priority-aware sensing and transmission framework that saves up to 41% energy and 32% bandwidth with 68% data accuracy compared to the existing competitive frameworks for non-real-time systems.
References
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Compressed sensing
TL;DR: It is possible to design n=O(Nlog(m)) nonadaptive measurements allowing reconstruction with accuracy comparable to that attainable with direct knowledge of the N most important coefficients, and a good approximation to those N important coefficients is extracted from the n measurements by solving a linear program-Basis Pursuit in signal processing.
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Subspace Pursuit for Compressive Sensing Signal Reconstruction
Wei Dai,Olgica Milenkovic +1 more
TL;DR: The presented analysis shows that in the noiseless setting, the proposed algorithm can exactly reconstruct arbitrary sparse signals provided that the sensing matrix satisfies the restricted isometry property with a constant parameter.
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Subspace Pursuit for Compressive Sensing Signal Reconstruction
Wei Dai,Olgica Milenkovic +1 more
TL;DR: In this paper, the subspace pursuit algorithm was proposed for sparse signals with and without noisy perturbations, which has low computational complexity, comparable to that of orthogonal matching pursuit techniques when applied to very sparse signals, and reconstruction accuracy of the same order as that of LP optimization methods.
Journal ArticleDOI
Sparse Bayesian learning for basis selection
David Wipf,Bhaskar D. Rao +1 more
TL;DR: This paper adapts SBL to the signal processing problem of basis selection from overcomplete dictionaries, proving several results about the SBL cost function that elucidate its general behavior and providing solid theoretical justification for this application.