Clustering and communications scheduling in WSNs using mixed integer linear programming

Avril, François; Bernard, Thibault; Bui, Alain; Sohier, Devan

doi:10.1109/jcn.2014.000072

Cited by 14 publications

(11 citation statements)

References 19 publications

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“…But, like other centralized clustering approaches ECRA, ASPLR, and HEEMP relies on BS to compute the topology and causes a longer delay. Also, in clustering, there is no deterministic algorithm that can partition the network into balanced clusters . Moreover, in a sensor networks, there are multiple paths to reach a particular destination i.e.…”

Section: Related Workmentioning

confidence: 99%

A distributed, multi‐hop, adaptive, tree‐based energy‐balanced routing approach

Arora

Sharma²,

Sachdeva

2019

Int J Communication

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To accomplish the primary objective of data sensing and collection of wireless sensor networks (WSN), the design of an energy efficient routing algorithm is very important. However, the energy constrained sensing nodes along with the intrinsic properties of the (WSN) environment makes the routing a challenging task. To overcome this routing dilemma, an improved distributed, multi-hop, adaptive, tree-based energy-balanced (DMATEB) routing scheme is proposed in this paper. In this scheme, a relay node is selected in view of minimum distance and high energy from a current sensing node. Further, the parent node is chosen among the selected relay nodes on the basis of high residual energy and less power consumption with due consideration of its associated child nodes.As each sensing node itself selects its parent among the available alternatives, the proposed scheme offers a distributive and adaptive approach. Moreover, the proposed system does not overload any selected parent of a particular branch as it starts acting as a child whenever its energy lowers among the other available relay nodes. This leads to uniform energy utilization of nodes that offers a better energy balance mechanism and improves the network lifespan by 20% to 30% as compared with its predecessors. KEYWORDS energy efficient routing, tree-based structure, wireless sensor network Int J Commun Syst. 2019;32:e3949.wileyonlinelibrary.com/journal/dac

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Section: Related Workmentioning

confidence: 99%

A distributed, multi‐hop, adaptive, tree‐based energy‐balanced routing approach

Arora

Sharma²,

Sachdeva

2019

Int J Communication

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“…However, this solution requires all clusters to be synchronized. Paper [21] investigates the communication scheduling that can maximize the parallel communication. Authors first use clique-clustering algorithm to partition the network into maximal cliques (clusters).…”

Section: Interference-free Strategymentioning

confidence: 99%

“…Even though only a few works are dedicated to interference-free, people do realize the importance of providing interference-free communication for cluster-based networks. Most of previous works introduce interference-free based on multiple access technologies or complex timeslot allocation methods for clustered WSNs [16]- [21], but the clusters themselves are not interference-free. This makes them inefficient, especially for large-scale WSNs.…”

Section: Introductionmentioning

confidence: 99%

Interference-free Clustering Protocol for Large-Scale and Dense Wireless Sensor Networks

Chen¹,

Lin²,

Wang³

et al. 2019

KSII TIIS

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Saving energy is a big challenge for Wireless Sensor Networks (WSNs), which becomes even more critical in large-scale WSNs. Most energy waste is communication related, such as collision, overhearing and idle listening, so the schedule-based access which can avoid these wastes is preferred for WSNs. On the other hand, clustering technique is considered as the most promising solution for topology management in WSNs. Hence, providing interference-free clustering is vital for WSNs, especially for large-scale WSNs. However, schedule management in cluster-based networks is never a trivial work, since it requires inter-cluster cooperation. In this paper, we propose a clustering method, called Interference-Free Clustering Protocol (IFCP), to partition a WSN into interference-free clusters, making timeslot management much easier to achieve. Moreover, we model the clustering problem as a multi-objective optimization issue and use non-dominated sorting genetic algorithm II to solve it. Our proposal is finally compared with two adaptive clustering methods, HEED-CSMA and HEED-BMA, demonstrating that it achieves the good performance in terms of delay, packet delivery ratio, and energy consumption.

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“…Applications Technique [7] Interference-free localization Maximum flow [10], [32] Nodes deployment Quadratic Assignment [23] Network lifetime Set Cover Problem and variant [30] [43] Routing Graph Coloring Problem [33] Routing Voronoi based path searching [44], [47] Energy Saving Multipath [28] Network lifetime Linear programming [12] QoS Multipath [24] Minimizing Energy Binary Integer Linear Programming [27] Energy saving Mixed Integer Linear Programming [48] Routing and sink location Integer programming [29] Energy Minimum Dominant set [34] Routing Dominant Set [31] Node localization Integer linear programming [38] Node localization Mathematical programing [39] Node localization, network lifetime Linear Programming [41] Interference [7], [10], [27], [29], [32] [34], [41], [43], [45], [48], [49], [52], [58], [59], [62], [65] √ √ [12], [23], [24], [28], [33], [38], [39], [44], [46], …”

Section: Referencesmentioning

confidence: 99%

“…In such approaches, the node can reduce its energy so as to be able to reach only its best neighbors. In [27], authors suggested a mixed integer-programming model to solve the problem of scheduling communications in wireless sensor networks to ensure battery preservation through the use of the sleeping mode of sensors.…”

Section: Operations Research Techniques In Energy Savingmentioning

confidence: 99%

Operation Research Based Techniques in Wireless Sensors Networks

Mahlous¹,

Tounsi²

2017

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In recent years, we have seen an increasing interest in developing and designing Wireless Sensor Networks (WSNs). WSNs consist of large number of nodes, with wireless communications and computation abilities that can be used in variety of domains. It has been used in areas that have direct contact with monitoring and gathering data, to name few, health monitoring, military surveillance, geological monitoring (Earthquakes, Volcanoes, Tsunami), agriculture control and many more. However, the design and implementation of WSNs face many challenges, due to the power limitation of sensor nodes, deployment and localization, data routing and data aggregation, data security, limited bandwidth, storage capacity and network management. It is known that Operation Research (OR) has been widely used in different areas to solve optimization problems; such as improving network performance and maximizing lifetime of system. In this survey, we present the most recent OR based techniques applied to solve different WSNs problems: the node scheduling problem, energy management problems, nodes allocating issues and other WSNs related complex problems. Different Operational Research techniques are presented and discussed in details here, including graph theory based techniques, linear programing and mixed integer programming related approaches.

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Clustering and communications scheduling in WSNs using mixed integer linear programming

Cited by 14 publications

References 19 publications

A distributed, multi‐hop, adaptive, tree‐based energy‐balanced routing approach

A distributed, multi‐hop, adaptive, tree‐based energy‐balanced routing approach

Interference-free Clustering Protocol for Large-Scale and Dense Wireless Sensor Networks

Operation Research Based Techniques in Wireless Sensors Networks

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