A Lifetime Optimization Algorithm Limited by Data Transmission Delay and Hops for Mobile Sink-Based Wireless Sensor Networks

Chen, Yourong; Lv, Xiaowen; Lu, Siyi; Ren, Tiaojuan

doi:10.1155/2017/7507625

Cited by 12 publications

(13 citation statements)

References 14 publications

(45 reference statements)

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“…On the contrary, a node of a chain-type network with multi-hop communication methods requires more power as it is closer to the base station, since it is subject to a more intense data traffic compared with the one of the most peripheral nodes. This issue is addressed in several papers like [ 47 , 48 , 49 , 50 , 51 ]. There are also some surveys and papers that investigated power optimization algorithms for WSN [ 52 , 53 , 54 , 55 , 56 ].…”

Section: Related Workmentioning

confidence: 99%

A Low Power IoT Sensor Node Architecture for Waste Management Within Smart Cities Context

Cerchecci

Luti

Mecocci

et al. 2018

Sensors

125

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This paper focuses on the realization of an Internet of Things (IoT) architecture to optimize waste management in the context of Smart Cities. In particular, a novel typology of sensor node based on the use of low cost and low power components is described. This node is provided with a single-chip microcontroller, a sensor able to measure the filling level of trash bins using ultrasounds and a data transmission module based on the LoRa LPWAN (Low Power Wide Area Network) technology. Together with the node, a minimal network architecture was designed, based on a LoRa gateway, with the purpose of testing the IoT node performances. Especially, the paper analyzes in detail the node architecture, focusing on the energy saving technologies and policies, with the purpose of extending the batteries lifetime by reducing power consumption, through hardware and software optimization. Tests on sensor and radio module effectiveness are also presented.

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Section: Related Workmentioning

confidence: 99%

A Low Power IoT Sensor Node Architecture for Waste Management Within Smart Cities Context

Cerchecci

Luti

Mecocci

et al. 2018

Sensors

125

View full text Add to dashboard Cite

show abstract

“…Dividing sensing field into subareas is proposed in [20,21]. Chen et al [20] introduced algorithm to improve the network lifetime considering data transmission delay and number of hops. The algorithm divided the sensing field into grids; the mobile sink has to stay at the grid center for data collection.…”

Section: Related Workmentioning

confidence: 99%

“…← set of nodes in (V , V ) not in ; (15) if is not empty then (16) Flag ← true ; (17) = NRA( , ) ; / * call Node Removal Algorithm * / ← ∪ ; (18) if Flag= false then (19) if V selected as then (20) =index of tree rooted on if is not empty then (13) for each tree index in do (14) get ← number of trees in ; (5) Find the farthest leave vertex V from using ; (6) Find the routing path…”

Section: Farthest Node First-bounded Hop Algorithm (Fnf-bha)mentioning

confidence: 99%

Delay Tolerance and Energy Saving in Wireless Sensor Networks with a Mobile Base Station

Jerew

Bassam

2019

Wireless Communications and Mobile Computing

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Recent research shows that significant energy saving can be achieved in wireless sensor networks by using mobile devices. A mobile device roams sensing fields and collects data from sensors through a short transmission range. Multihop communication is used to improve data gathering by reducing the tour length of the mobile device. In this paper we study the trade-off between energy saving and data gathering latency in wireless sensor networks. In particular, we examine the balance between the relay hop count and the tour length of a mobile Base Station (BS). We propose two heuristic algorithms, Adjacent Tree-Bounded Hop Algorithm (AT-BHA) and Farthest Node First-Bounded Hop Algorithm (FNF-BHA), to reduce energy consumption of sensor nodes. The proposed algorithms select groups of Collection Trees (CTs) and a subset of Collection Location (CL) sensor nodes to buffer and forward data to the mobile BS when it arrives. Each CL node receives sensing data from its CT nodes within bounded hop count. Extensive experiments by simulation are conducted to evaluate the performance of the proposed algorithms against another heuristic. We demonstrate that the proposed algorithms outperform the existing work with the mean of the length of mobile BS tour.

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“…Hence, the free space model is used for inter-cluster and intra-cluster communications while the multi-path model is used for transmission to BS. Network latency can be defined as the time lapse between the data packet generated by first node in chain and reception of all packets by BS, illustrated by [1,23,24]:…”

Section: Intelligent Routing Technique For Wireless Sensor Networkmentioning

confidence: 99%

Energy-efficient chain-cluster based intelligent routing technique for wireless sensor networks

Ramluckun

Bassoo

2018

ACI

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With the increasing acclaim of Wireless Sensor Networks and its diverse applications, research has been directed into optimising and prolonging the network lifetime. Energy efficiency has been a critical factor due to the energy resource impediment of batteries in sensor nodes. The proposed routing algorithm therefore aims at extending lifetime of sensors by enhancing load distribution in the network. The scheme is based on the chain-based routing technique of the PEGASIS (Power Energy GAthering in Sensor Information Systems) protocol and uses Ant Colony Optimisation to obtain the optimal chain. The contribution of the proposed work is the integration of the clustering method to PEGASIS with Ant Colony Optimisation to reduce redundancy of data, neighbour nodes distance and transmission delay associated with long links, and the employment an appropriate cluster head selection method. Simulation results indicates proposed method’s superiority in terms of residual energy along with considerable improvement regarding network lifetime, and significant reduction in delay when compared with existing PEGASIS protocol and optimised PEG-ACO chain respectively.

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A Lifetime Optimization Algorithm Limited by Data Transmission Delay and Hops for Mobile Sink-Based Wireless Sensor Networks

Cited by 12 publications

References 14 publications

A Low Power IoT Sensor Node Architecture for Waste Management Within Smart Cities Context

A Low Power IoT Sensor Node Architecture for Waste Management Within Smart Cities Context

Delay Tolerance and Energy Saving in Wireless Sensor Networks with a Mobile Base Station

Energy-efficient chain-cluster based intelligent routing technique for wireless sensor networks

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