Data transmission and base-station placement for optimizing the lifetime of wireless sensor networks

Arkin, Esther M.; Efrat, Alon; Mitchell, Joseph S. B.; Polishchuk, Valentin; Ramasubramanian, Srinivasan; Sankararaman, Swaminathan; Taheri, Javad

doi:10.1016/j.adhoc.2011.09.010

Cited by 13 publications

(9 citation statements)

References 27 publications

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“…1 is a continuous VOLUME 3, 2015 function in (0, D], then there must be one d hop ∈ (0, D], which achieves minimum value in (24). As a result, the optimal d hop is existed if the following equation is proved.…”

Section: Optimizing Design a Single-source Linear Networkmentioning

confidence: 93%

Reliability guaranteed efficient data gathering in wireless sensor networks

et al. 2015

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Wireless sensor networks (WSNs) are widely applied in various industrial applications. In this paper, we present an efficient data gathering scheme that guarantees the Quality of Service and optimizes the following network performance metrics as well as the end-to-end reliability in WSNs: 1) minimum total energy consumption; 2) minimum unit data transmitting energy consumption; and 3) maximum utilization efficiency defined as network lifetime per unit deployment. We first transform the performance optimization problem into a problem to optimize the following parameters: 1) deployed nodal number N * ; 2) nodal placement d * ; and 3) nodal transmission structure p * . Then, we prove that the optimization problem is solvable mathematically. For our observation, the sensor nodes close to the sink trend failed early since they consumed more energy with heavier relay traffic destined for the sink, which seriously affects the network performance. The key point of this optimization is adopting lower reliability requirements and shorter transmission distance for nodes near the sink. Consequently, this reduces the energy consumption of the nodes in the hotspot area. Meanwhile, it adopts higher reliability requirements and farther transmission distance for nodes far from the sink to make full use of the node residual energy, so as to optimize the network performance without harming network reliability. Numerical simulation results demonstrate that our optimal approach improves the network lifetime by 18%-48% and network utility by 17%, and guarantees desire reliability level.INDEX TERMS Wireless sensor networks, source location privacy, network lifetime, tree based routing, performance optimization.

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Section: Optimizing Design a Single-source Linear Networkmentioning

confidence: 93%

Reliability guaranteed efficient data gathering in wireless sensor networks

et al. 2015

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“…In the context of sensor networks, several studies have considered the optimal node placement schemes which are always NP-hard. To tackle such complexity, several heuristics have been proposed to find sub-optimal solutions [5,6] in presence of stationary nodes. In VANETs and mesh networks, there are several studies on roadside units (RSUs) placement problem.…”

Section: Related Workmentioning

confidence: 99%

Roadside Infrastructure Placement for Information Dissemination in Urban ITS Based on a Probabilistic Model

Xie

Xia

Chen

2013

Lecture Notes in Computer Science

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Abstract. Information dissemination is an important application in VANETs for traffic safety and efficiency. In urban area, roadside infrastructure nodes can be deployed for information dissemination. However, it is inefficient and uneconomical to cover the whole urban area. How to find the optimal locations to place DPs is a research problem. Some works on this issue have to collect accurate trajectories of all the vehicles, which is not practical in the real environment. In this paper, we propose a novel approach for DPs placement in grid road networks without knowing trajectories. Based on the analysis of path number between two intersections, a probabilistic model is proposed to get the trajectories estimation of vehicles. The theoretical optimal algorithm (OA) and two heuristic algorithms (called KP-G and GA) are developed for the problem. Simulation results reveal that GA is scalable and has the highest coverage ratio on average. IntroductionInformation dissemination based on Vehicular Ad hoc Networks (VANETs) is intended to the support traffic safety and efficiency, as well as services for drivers [1][2][3]. In this paper, we deal with information dissemination from roadside infrastructure to passing vehicles, tackling the specific issue of deploying an intelligent transport system infrastructure that efficiently achieves the dissemination goal. For example, transport department can disseminate some traffic news to vehicles. We refer to the vehicles who have received the disseminated information as informed vehicles. Our goal is to maximize the number of informed vehicles. In other words, we aim at maximizing the coverage ratio of information dissemination. In principle, an information dissemination system could leverage both vehicle-tovehicle (V2V) and vehicles-to-infrastructure (V2I) communications. When only a few of roadside units (RSUs) are deployed, V2V communications could enable data sharing thus increasing the coverage ratio of information dissemination. However, the gain achieved through V2V communication strictly depends on the network topology

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“…In 2014, Arkin et al [1] focused on shallow tree topologies to maximize the network lifetime for energy efficiency on wireless sensor network optimization problem. However, Chanak et al [3] identified an issue in WSN for analyzing the network due to improvisational nature.…”

Section: Related Workmentioning

confidence: 99%

“…Their review outcomes are summarized in Table 1. The LEACH method used in [1] has advantages such as scalability and increased network lifetime. Nevertheless, it does not have inter-cluster communication.…”

Section: Problem Statementmentioning

confidence: 99%

“…Wireless Sensor Network (WSN) is most commonly used in various applications such as military, industrial, health monitoring and vehicular tracking [1,2]. Moreover, WSN consists of thousand sensors with small nodes, and it has the advantages like low cost, high storage capacity, sensing and consumes low power while comparing with other computer networks [3].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Base Station Positioning in Wireless Sensor Network to aid Cluster Head Selection Process

Shankar¹,

Jaisankar²

2017

IJIES

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Abstract:In this paper, we propose an (SAPSO) Self-Adaptive Particle Swarm Optimization algorithm to solve the base station positioning problem. This algorithm is used to minimize the distance between the base station and cluster head owing to maximizing the energy. Moreover, the proposed algorithm is compared with many other conventional algorithms such as Artificial Bee Colony-Dynamic Scout bee (ABC-DS) algorithm, Genetic algorithm (GA), Particle swarm optimization (PSO) and Firefly with Dual Update Process (FFDUP) algorithm. Also, empowering SAPSO helps to find the optimal location of the base station to conserve energy in a noteworthy manner to maximize the network lifetime and prolong network connectivity regarding minimizing distance, delay and maximizing the security, energy. Our simulation results demonstrate that the proposed SAPSO algorithm performs better than the other conventional algorithm.

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Data transmission and base-station placement for optimizing the lifetime of wireless sensor networks

Cited by 13 publications

References 27 publications

Reliability guaranteed efficient data gathering in wireless sensor networks

Reliability guaranteed efficient data gathering in wireless sensor networks

Roadside Infrastructure Placement for Information Dissemination in Urban ITS Based on a Probabilistic Model

Base Station Positioning in Wireless Sensor Network to aid Cluster Head Selection Process

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