Sleep Scheduling in Industrial Wireless Sensor Networks for Toxic Gas Monitoring

Mukherjee, Mithun; Shu, Lei; Hu, Likun; Hancke, Gerhard P.; Zhu, Chunsheng

doi:10.1109/mwc.2017.1600072wc

Cited by 63 publications

(29 citation statements)

References 10 publications

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“…The proposed algorithm makes minimum energy consumption in path establishment only by hop count concern but extending with node degree also a metric can improve the routing performance. Generally, there are some traditional routing algorithms that consider the sleep‐awake mechanism . These algorithms reduce the energy consumption by adjusting the portion of the node into “sleep” and other nodes in “awake” mode to prolong the entire network lifetime.…”

Section: Related Workmentioning

confidence: 99%

LSAPSP: Load distribution‐based slot allocation and path establishment using optimized substance particle selection in sensor networks

Natarajan¹,

Subapriya

Thangavel³

2020

Int J Communication

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Summary Sensor node energy conservation is the primary design parameters in wireless sensor networks (WSNs). Energy efficiency in sensor networks directly prolongs the network lifetime. In the process of route discovery, each node cooperates to forward the data to the base station using multi‐hop routing. But, the nodes nearer to the base station are loaded more than the other nodes that lead to network portioning, packet loss and delay as a result nodes may completely loss its energy during the routing process. To rectify these issues, path establishment considers optimized substance particle selection, load distribution, and an efficient slot allocation scheme for data transmission between the sensor nodes in this paper. The selection of forwarders and conscious multi‐hop path is selected based on the route cost value that is derived directly by taking energy, node degree and distance as crucial metrics. Load distribution based slot allocation method ensures the balance of data traffic and residual energy of the node in areal‐time environment. The proposed LSAPSP simulation results show that our algorithm not only can balance the real‐time environment load and increase the network lifetime but also meet the needs of packet loss and delay.

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Section: Related Workmentioning

confidence: 99%

LSAPSP: Load distribution‐based slot allocation and path establishment using optimized substance particle selection in sensor networks

Natarajan¹,

Subapriya

Thangavel³

2020

Int J Communication

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“…In (6), N i is the noise power received by UE i; F i,c is the interfering power received by UE i over a cellular channel, where F i,c is negligible if co-channel interference between adjacent cells is very small due to the adoption of effective cellular interference control methods; g 0i is the attenuation coefficient in the channel from the eNB to UE i, and it is subject to effects of shadowing fade, multipath fade, and path loss etc., which is usually estimated and quantified by a receiving end and then feeds back to the corresponding sending end.…”

Section: Problem Formulationmentioning

confidence: 99%

“…Þ according the Formulas (1) and (6). Also, for such path that only contains one cellular link, P i = p 0i and P…”

Section: The Theoretical Analysis For Potential Gamementioning

confidence: 99%

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Cellular throughput optimization by game-based power adjustment and outband D2D communication

Gui

Zhou

2018

J Wireless Com Network

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Device-to-device (D2D) communication is a promising option for the fifth generation (5G) mobile communication network to reduce energy consumption and increase throughput, which makes high throughput applications possible. Also, the improvement for energy and spectrum efficiency is critical in such applications. Without occupation of cellular spectrum resources, outband D2D communication is increasingly applied to high throughput applications to increase spectrum supply. However, energy efficiency is still a key issue that needs to be addressed. Moreover, the overall energy efficiency in cellular networks is severely limited by cell-edge devices. Therefore, in this paper, we apply multi-hop relay-aided outband D2D communication to cellular networks and propose a game-based power adjustment method to address throughput optimization problem. Firstly, we model an interaction relationship of power adjustment for each transmission path as a potential game, where a new utility function is designed for each player (i.e., the receiving end of a transmission path) to evaluate its action gain and to determine whether taking action or not. And then, it is proved that the utility function is an ordinal potential function (OPF) and the game of power adjustment is an ordinal potential game (OPG), which guarantees the convergence of game decision process. Moreover, we propose a new game decision algorithm, which has quicker convergence speed than the existing typical algorithm. In addition, we design a networkassisted distributed processing architecture for solving throughput optimization problem, including receiving mode selection, verification for relay selection, and transmission power adjustment, which can ease the burden of centralized processing. The experimental results show that our scheme is superior to the existing typical work in terms of throughput, delay, energy efficiency, continuous service ability, and convergence performance.

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“…The authors in [33] presented a sleep scheduling scheme for toxic gas monitoring. A sensor node inside the gas leakage area is selected as the zone head based on the largest residual energy by restricting flooding of the head selection message within the zone.…”

Section: Related Workmentioning

confidence: 99%

Boundary Region Detection for Continuous Objects in Wireless Sensor Networks

Zhang

Wang

Meng

et al. 2018

Wireless Communications and Mobile Computing

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Industrial Internet of Things has been widely used to facilitate disaster monitoring applications, such as liquid leakage and toxic gas detection. Since disasters are usually harmful to the environment, detecting accurate boundary regions for continuous objects in an energy-efficient and timely fashion is a long-standing research challenge. This article proposes a novel mechanism for continuous object boundary region detection in a fog computing environment, where sensing holes may exist in the deployed network region. Leveraging sensory data that have been gathered, interpolation algorithms have been applied to estimate sensory data at certain geographical locations, in order to estimate a more accurate boundary line. To examine whether estimated sensory data reflect that fact, mobile sensors are adopted to traverse these locations for gathering their sensory data, and the boundary region is calibrated accordingly. Experimental evaluation shows that this technique can generate a precise object boundary region with certain time constraints, and the network lifetime can be prolonged significantly.

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Sleep Scheduling in Industrial Wireless Sensor Networks for Toxic Gas Monitoring

Cited by 63 publications

References 10 publications

LSAPSP: Load distribution‐based slot allocation and path establishment using optimized substance particle selection in sensor networks

LSAPSP: Load distribution‐based slot allocation and path establishment using optimized substance particle selection in sensor networks

Cellular throughput optimization by game-based power adjustment and outband D2D communication

Boundary Region Detection for Continuous Objects in Wireless Sensor Networks

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