Connectivity and coverage in machine-type communications

Sarigiannidis, Panagiotis; Zygiridis, Theodoros T.; Sarigiannidis, Antonios; Λάγκας, Θωμάς; Obaidat, Mohammad S.; Kantartzis, Nikolaos V.

doi:10.1109/icc.2017.7996897

Cited by 15 publications

(7 citation statements)

References 16 publications

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“…However, these works do not consider the capacity of the sensor nodes for service provisioning. In the existing literature, researchers proposed a few schemes for the optimal selection of physical sensor nodes in WSNs, viz., [15]- [17] and Internet-of-Things devices [18], [19]. However, these schemes are designed with the aim of solving specific issues such as coverage and eventdetection.…”

Section: Related Workmentioning

confidence: 99%

QoS-Aware Dispersed Dynamic Mapping of Virtual Sensors in Sensor-Cloud

Misra

Chakraborty

2021

IEEE Trans. Serv. Comput.

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In this paper, we study the problem of dynamic mapping of virtual sensors in sensor-cloud for provisioning high quality of Sensors-as-a-Service (Se-aaS) in the presence of multiple sensor-owners and heterogeneous sensor nodes. We divide this problem into two subproblems-optimal dispersed node selection and optimal data-rate distribution, and analyze that these problems are NP-complete. Hence, we propose a game theory-based online scheme, named QADMAP, to solve these two problems in polynomial time. For the optimal node selection problem, we design a dynamic coalition-formation game-based online scheme, while maximizing the dispersion index of the selected nodes. On the other hand, we propose an evolutionary game theory-based scheme for distributing the data-rate requirements of the services among the selected nodes, optimally. As per our knowledge, none of the existing works on dynamic mapping of virtual sensors considers the stochastic behavior of sensor-cloud for provisioning Se-aaS. From simulations, we observe that, using QADMAP, the energy consumption of the network reduces by 29.88-31.73%, thereby improving the QoS in terms of service availability by 11% and increasing the profit of the SCSP by 3.63-9.82%, compared to the existing benchmark schemes.

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Section: Related Workmentioning

confidence: 99%

QoS-Aware Dispersed Dynamic Mapping of Virtual Sensors in Sensor-Cloud

Misra

Chakraborty

2021

IEEE Trans. Serv. Comput.

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“…Sensor nodes are self-dependent that is after their deployment they can work without any form of human interference. These nodes sense, collect, process and then transmit data to base station [13][14][15].…”

Section: Fig 4 Components Of a Sensor Nodementioning

confidence: 99%

The Coverage Issues in WSNs

Rani

Anand

2020

ARJOM

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Aim: Wireless Sensor Networks is one of the hot research topic in previous years due to its wide contribution in emerging industry that is Internet of Things. A wireless sensor network is a network of tiny devices, which can gather the information from surrounding and then successfully communicate it via wireless link. WSNs are widely used for monitoring targets in given field of interest. Most popular area of research in Wireless Sensor Networks is coverage. This paper focus on coverage issues in Wireless Sensor Networks. Study Design: Various Issues in WSNs being studied and analyzed. Place and Duration of Study: Swami Parmanand College Lalru, between May 2019 to December 2019. Methodology: It included following steps:- Survey of the literature related to the proposed work. Comparison of different types of WSNs and challenges and issues related to them. Detailed study of coverage issue involved in implementation of WSN. Results: Coverage selection depends on the system requirement. Each coverage has its own advantages and disadvantages related to its implementation. “Table 2: Comparison between Various WSN and challenges related to them” it discusses about various types of WSNs and the challenges related to each one of them. Conclusion: Coverage in WSNs can be defined on how well the sensor nodes monitor the targets in given field of interest. Each application comes with different set of coverage requirements; hence, deployment strategies are chosen based on the requirements.

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“…As Q. Wu such, WPT is a promising technology for achieving selfsustainable and scalable machine-type communications [5] and will have a significant impact on future IoT networks [6]. Recently, wireless-powered communication networks (WPCNs) have been proposed in [7] where a dedicated power station (PS) first broadcasts energy signals to devices for downlink (DL) WPT and then the devices exploit the harvested energy for uplink wireless information transmission (UL WIT).…”

Section: Introductionmentioning

confidence: 99%

Generalized Wireless-Powered Communications: When to Activate Wireless Power Transfer?

Zhang

et al. 2019

IEEE Trans. Veh. Technol.

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Wireless-powered communication network (WPCN) is a key technology to power energy-limited massive devices, such as on-board wireless sensors in autonomous vehicles, for Internet-of-Things (IoT) applications. Conventional WPCNs rely only on dedicated downlink wireless power transfer (WPT), which is practically inefficient due to the significant energy loss in wireless signal propagation. Meanwhile, ambient energy harvesting is highly appealing as devices can scavenge energy from various existing energy sources (e.g., solar energy and cellular signals). Unfortunately, the randomness of the availability of these energy sources cannot guarantee stable communication services. Motivated by the above, we consider a generalized WPCN where the devices can not only harvest energy from a dedicated multipleantenna power station (PS), but can also exploit stored energy stemming from ambient energy harvesting. Since the dedicated WPT consumes system resources, if the stored energy is sufficient, WPT may not be needed to maximize the weighted sum rate (WSR). To analytically characterize this phenomenon, we derive the condition for WPT activation and reveal how it is affected by the different system parameters. Subsequently, we further derive the optimal resource allocation policy for the cases that WPT is activated and deactivated, respectively. In particular, it is found that when WPT is activated, the optimal energy beamforming at the PS does not depend on the devices' stored energy, which is shown to lead to a new unfairness issue. Simulation results verify our theoretical findings and demonstrate the effectiveness of the proposed optimal resource allocation.Index Terms-Energy-constrained IoT networks, when to activate WPT, energy beamforming, optimal resource allocation.

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Connectivity and coverage in machine-type communications

Cited by 15 publications

References 16 publications

QoS-Aware Dispersed Dynamic Mapping of Virtual Sensors in Sensor-Cloud

QoS-Aware Dispersed Dynamic Mapping of Virtual Sensors in Sensor-Cloud

The Coverage Issues in WSNs

Generalized Wireless-Powered Communications: When to Activate Wireless Power Transfer?

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