Optimal placement of relay nodes in wireless sensor network using artificial bee colony algorithm

Hashim, Hashim A.; Ayinde, Babajide O.; Abido, M. A.

doi:10.1016/j.jnca.2015.09.013

Cited by 106 publications

(57 citation statements)

References 31 publications

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“…An artificial bee colony algorithm for optimal placement of relay nodes in wireless sensor networks has been presented in [12]. The goal of [12] is that of reducing the communication holes stemming from randomly-placed relay nodes.…”

Section: State Of the Artmentioning

confidence: 99%

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Optimal Fault-Tolerant Placement of Relay Nodes in a Mission Critical Wireless Network

Mancini¹,

Tronci²,

Scialanca³

et al. 2018

EasyChair Preprints

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Abstract. The operations of many critical infrastructures (e.g., airports) heavily depend on proper functioning of the radio communication network supporting operations. As a result, such a communication network is indeed a mission-critical communication network that needs adequate protection from external electromagnetic interferences. This is usually done through radiogoniometers. Basically, by using at least three suitably deployed radiogoniometers and a gateway gathering information from them, sources of electromagnetic emissions that are not supposed to be present in the monitored area can be localised. Typically, relay nodes are used to connect radiogoniometers to the gateway. As a result, some degree of fault-tolerance for the network of relay nodes is essential in order to offer a reliable monitoring. On the other hand, deployment of relay nodes is typically quite expensive. As a result, we have two conflicting requirements: minimise costs while guaranteeing a given fault-tolerance. In this paper address the problem of computing a deployment for relay nodes that minimises the relay node network cost while at the same time guaranteeing proper working of the network even when some of the relay nodes (up to a given maximum number) become faulty (fault-tolerance). We show that the above problem can be formulated as a Mixed Integer Linear Programming (MILP) as well as a Pseudo-Boolean Satisfiability (PB-SAT) optimisation problem and present experimental results comparing the two approaches on realistic scenarios.

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Section: State Of the Artmentioning

confidence: 99%

“…The goal of [12] is that of reducing the communication holes stemming from randomly-placed relay nodes. The results in [12] show that indeed a clever positioning of relay nodes decreases the network energy consumption.…”

Section: State Of the Artmentioning

confidence: 99%

Optimal Fault-Tolerant Placement of Relay Nodes in a Mission Critical Wireless Network

Mancini¹,

Tronci²,

Scialanca³

et al. 2018

EasyChair Preprints

View full text Add to dashboard Cite

show abstract

“…In [20], it is proven that just listing a set of feasible sites for the relays is already at least APX-hard. Though many heuristic algorithms have been proposed, such as Genetic Algorithm [12,21], Artificial Bee Colony Algorithm [14], and Concentric Fermat Points [31], it is still extraordinarily time-consuming.…”

Section: Related Workmentioning

confidence: 99%

“…When a node just has two neighbors, move any one towards another has the same travel distance to restore connectivity. For this case, the one with smaller failed_cost is chosen (line [11][12][13][14][15][16], this is to insure the next restoration has a smaller moving cost. By now, the initialization and proactive backup selection are done.…”

mentioning

confidence: 99%

Hybrid connectivity restoration in wireless sensor and actor networks

Yan

Luo

Tian

et al. 2017

J Wireless Com Network

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Wireless sensor and actor networks are becoming more and more popular in the recent years. Each WSAN consists of numerous sensors and a few actors working collaboratively to carry out specific tasks. Unfortunately, actors are prone to failure due to harsh deployment environments and constrained power, which may break network connectivity resulting in disjoint components. Thus, maintaining the connectivity among actors is especially important. This paper proposes hybrid connectivity restoration (HCR), which integrates proactive selection and reactive motion. An actor protectively selects a backup node through its one-hop neighbor table and informs the backup node to supervise its stage. Once it fails, the backup node moves to the best position to restore the connectivity of the failed node's neighbors reactively. This triggers a local recovery process at the backup node, which is repeated until network connectivity is restored. In order to minimize travel distance, HCR selects the backup node which moves the shortest distance to restore connectivity. Furthermore, HCR opts to reduce the number of messages by just informing the failure to its backup node. The correctness and effectiveness of HCR are validated through both theoretical analysis and simulations.

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“…Aydoğdu İ. proposed an enhanced artificial bee colony algorithm and employed it to optimize the steel space frames design [17]. Hashim H. A. proposed an enhanced deployment algorithm based on ABC algorithm [18]. Oshaba A. S. proposed a novel ABC algorithm to optimize parameters of maximum power point tracking and speed controller [19].…”

Section: Introductionmentioning

confidence: 99%

Improved Artificial Bee Algorithm for Reliability-based Optimization of Truss Structures

Li¹,

Wang²,

Liu³

et al. 2017

TOCIEJ

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Introduction:In order to optimize the reliability of the truss structure more effectively, an improved artificial bee colony algorithm based on small interval was proposed and employed to the engineering practice. Method:First, the optimization model based on the reliability was set up. In the model, the bars were treated as design variables, and the total weight was the object function. Then, the comparisons with other methods in solving the truss structure discrete variable optimization demonstrate the feasibility and effectiveness of the improved algorithm. Conclusion:This work provides a new method for the reliability-based optimization of truss structures.

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Optimal placement of relay nodes in wireless sensor network using artificial bee colony algorithm

Cited by 106 publications

References 31 publications

Optimal Fault-Tolerant Placement of Relay Nodes in a Mission Critical Wireless Network

Optimal Fault-Tolerant Placement of Relay Nodes in a Mission Critical Wireless Network

Hybrid connectivity restoration in wireless sensor and actor networks

Improved Artificial Bee Algorithm for Reliability-based Optimization of Truss Structures

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