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227
Data collection in wireless sensor networks with mobile elements: A survey
- ACM Trans. Sensor Networks
"... Wireless sensor networks (WSNs) have emerged as an effective solution for a wide range of applications. Most of the traditional WSN architectures consist of static nodes which are densely deployed over a sensing area. Recently, several WSN architectures based on mobile elements (MEs) have been propo ..."
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Cited by 34 (4 self)
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Wireless sensor networks (WSNs) have emerged as an effective solution for a wide range of applications. Most of the traditional WSN architectures consist of static nodes which are densely deployed over a sensing area. Recently, several WSN architectures based on mobile elements (MEs) have been proposed. Most of them exploit mobility to address the problem of data collection in WSNs. In this paper we first define WSNs with MEs and provide a comprehensive taxonomy of their architectures, based on the role of the MEs. Then, we present an overview of the data collection process in such scenario, and identify the corresponding issues and challenges. On the basis of these issues, we provide an extensive survey of the related literature. Finally, we compare the underlying approaches and solutions, with hints to open problems and future research directions.
Extending the Lifetime of Wireless Sensor Networks through Adaptive Sleep
- IEEE TRANSACTIONS ON INDUSTRUSTRIAL INFORMATICS
, 2009
"... In recent years, the use of wireless sensor networks for industrial applications has rapidly increased. However, energy consumption still remains one of the main limitations of this technology. As communication typically accounts for the major power consumption, the activity of the transceiver shou ..."
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Cited by 18 (2 self)
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In recent years, the use of wireless sensor networks for industrial applications has rapidly increased. However, energy consumption still remains one of the main limitations of this technology. As communication typically accounts for the major power consumption, the activity of the transceiver should be minimized, in order to prolong the network lifetime. To this end, this paper proposes an Adaptive Staggered sLEEp Protocol (ASLEEP) for efficient power management in wireless sensor networks targeted to periodic data acquisition. This protocol dynamically adjusts the sleep schedules of nodes to match the network demands, even in time-varying operating conditions. In addition, it does not require any a-priori knowledge of the network topology or traffic pattern. ASLEEP has been extensively studied with simulation. The results obtained show that, under stationary conditions, the protocol effectively reduces the energy consumption of sensor nodes (by dynamically adjusting their duty-cycle to current needs) thus increasing significantly the network lifetime. With respect to similar non-adaptive solutions, it also reduces the average message latency and may increase the delivery ratio. Under timevarying conditions the protocol is able to adapt the duty-cycle of single nodes to the new operating conditions while keeping a consistent sleep schedule among sensor nodes. The results presented here are also confirmed by an experimental evaluation in a real testbed.
Reliable and Energy-efficient Data Collection in Sparse Sensor Networks with Mobile Elements
, 2009
"... Sparse wireless sensor networks (WSNs) are emerging as an effective solution for a wide range of applications, especially for environmental monitoring. In many scenarios, a moderate number of sparsely deployed nodes can be sufficient to get the required information about the sensed phenomenon. To th ..."
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Cited by 17 (4 self)
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Sparse wireless sensor networks (WSNs) are emerging as an effective solution for a wide range of applications, especially for environmental monitoring. In many scenarios, a moderate number of sparsely deployed nodes can be sufficient to get the required information about the sensed phenomenon. To this end, special mobile elements, i.e. mobile data collectors (MDCs), can be used to get data sampled by sensor nodes. In this paper we present an analytical evaluation of the data collection performance in sparse WSNs with MDCs. Our main contribution is the definition of a flexible model which can derive the total energy consumption for each message correctly transferred by sensors to the MDC. The obtained energy expenditure for data transfer also accounts for the overhead due to the MDC detection when sensor nodes operate with a low duty cycle. The results show that a low duty cycle is convenient and allows a significant amount of correctly received messages, especially when the MDC moves with a low speed. When the MDC moves fast, depending on its mobility pattern, a low duty cycle may not always be the most energy efficient option.
An adaptive strategy for energy-efficient data collection in sparse wireless sensor networks
- In EWSN
, 2010
"... Abstract. Sparse wireless sensor networks (WSNs) are being effectively used in several applications, which include transportation, urban safety, environment monitoring, and many others. Sensor nodes typically transfer acquired data to other nodes and base stations. Such data transfer operations are ..."
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Cited by 14 (2 self)
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Abstract. Sparse wireless sensor networks (WSNs) are being effectively used in several applications, which include transportation, urban safety, environment monitoring, and many others. Sensor nodes typically transfer acquired data to other nodes and base stations. Such data transfer operations are critical, especially in sparse WSNs with mobile elements. In this paper, we investigate data collection in sparse WSNs by means of special nodes called Mobile Data Collectors (MDCs), which visit sensor nodes opportunistically to gather data. As contact times and other information are not known a priori, the discovery of an incoming MDC by the static sensor node becomes a critical task. Ideally, the discovery strategy should be able to correctly detect contacts while keeping a low energy consumption. In this paper, we propose an adaptive discovery strategy that exploits distributed independent reinforcement learning to meet these two necessary requirements. We carry out an extensive simulation analysis to demonstrate the energy efficiency and effectiveness of the proposed strategy. The obtained results show that our solution provides superior performance in terms of both discovery efficiency and energy conservation. 1
Opportunistic routing in wireless sensor networks powered by ambient energy harvesting
- Computer Networks
"... Energy consumption is an important issue in the design of wireless sensor networks (WSNs) which typically rely on portable energy sources like batteries for power. Recent advances in ambient energy harvesting technologies have made it possible for sensor nodes to be powered by ambient energy entirel ..."
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Cited by 13 (5 self)
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Energy consumption is an important issue in the design of wireless sensor networks (WSNs) which typically rely on portable energy sources like batteries for power. Recent advances in ambient energy harvesting technologies have made it possible for sensor nodes to be powered by ambient energy entirely without the use of batteries. However, since the energy harvesting process is stochastic, exact sleep-and-wakeup schedules cannot be determined in WSNs Powered solely using Ambient Energy H arvesters (WSN-HEAP). Therefore, many existing WSN routing protocols cannot be used in WSN-HEAP. In this paper, we design an opportunistic routing protocol (EHOR) for multi-hop WSN-HEAP. Unlike traditional opportunistic routing protocols like ExOR or MORE, EHOR takes into account energy constraints because nodes have to shut down to recharge once their energy is depleted. Furthermore, since the rate of charging is dependent on environmental factors, the exact identities of nodes that are awake cannot be determined in advance. Therefore, choosing an optimal forwarder is another challenge in EHOR. We use a regioning approach to achieve this goal. Using extensive simulations incorporating experimental results from the characterization ∗ corresponding author, telephone number: +65-64082319
Energy-aware sparse approximation technique (east) for rechargeable wireless sensor networks
- Wireless Sensor Networks
, 2010
"... Abstract. Due to non-homogeneous spread of sunlight, sensing nodes typically have non-uniform energy profiles in rechargeable Wireless Sen-sor Networks (WSNs). An energy-aware work load distribution is there-fore necessary for good data accuracy while ensuring an energy-neutral operation. Recently p ..."
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Cited by 11 (5 self)
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Abstract. Due to non-homogeneous spread of sunlight, sensing nodes typically have non-uniform energy profiles in rechargeable Wireless Sen-sor Networks (WSNs). An energy-aware work load distribution is there-fore necessary for good data accuracy while ensuring an energy-neutral operation. Recently proposed signal approximation strategies, in form of Compressive Sensing, assume uniform sampling and thus cannot be de-ployed to facilitate energy neutral operation in rechargeable WSNs. We propose a sparse approximation driven sensing technique (EAST) that adapts sensor node sampling workload according to solar energy avail-ability. To the best of our knowledge, we are the first to propose sparse approximation for modeling energy-aware work load distribution in order to improve signal approximation from rechargeable WSNs. Experimental result, by using data from an outdoor WSN deployment, suggests that EAST significantly improves the approximation accuracy while support-ing approximately 50 % higher sensor on-time compared to an approach that assumes uniform energy profile of the nodes. 1
The progressive smart grid system from both power and communications aspects
- IEEE Communications Surveys & Tutorials
, 2011
"... Abstract—The present electric power system structure has lasted for decades; it is still partially proprietary, energy-inefficient, physically and virtually (or cyber) insecure, as well as prone to power transmission congestion and consequent failures. Recent efforts in building a smart grid system ..."
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Cited by 9 (1 self)
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Abstract—The present electric power system structure has lasted for decades; it is still partially proprietary, energy-inefficient, physically and virtually (or cyber) insecure, as well as prone to power transmission congestion and consequent failures. Recent efforts in building a smart grid system have focused on addressing the problems of global warming effects, rising energy-hungry demands, and risks of peak loads. One of the major goals of the new system is to effectively regulate energy usage by utilizing the backbone of the prospectively
An Analytical Study of Reliable and Energy-efficient Data Collection in Sparse Sensor Networks with Mobile Relays
"... Abstract. Sparse wireless sensor networks (WSNs) are emerging as an effective solution for a wide range of applications, especially for environmental monitoring. In this context, special mobile elements – i.e. mobile relays (MRs) – can be used to get data sampled by sensor nodes. In this paper we p ..."
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Cited by 9 (0 self)
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Abstract. Sparse wireless sensor networks (WSNs) are emerging as an effective solution for a wide range of applications, especially for environmental monitoring. In this context, special mobile elements – i.e. mobile relays (MRs) – can be used to get data sampled by sensor nodes. In this paper we present an analytical evaluation of the data collection performance in sparse WSNs with MRs. Our main contribution is the definition of a flexible model which can derive the total energy consumption for each message correctly transferred by sensors to the MR. The results show that a low duty cycle is convenient and allows a significant amount of correctly received messages, especially when the MR moves with a low speed. When the MR moves fast, depending on its mobility pattern, a low duty cycle may not always be the most energy efficient option. 1
A security analysis for wireless sensor mesh networks in highly critical systems
- Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on 40.4
, 2010
"... Nowadays, critical control systems are a fundamental component con-tributing to the overall performance of critical infrastructures in our soci-ety, most of which belong to the industrial sector. These complex systems include in their design different types of ICT (Information and Commu-nication Tec ..."
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Cited by 9 (4 self)
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Nowadays, critical control systems are a fundamental component con-tributing to the overall performance of critical infrastructures in our soci-ety, most of which belong to the industrial sector. These complex systems include in their design different types of ICT (Information and Commu-nication Technology) systems, such as Wireless (Mesh) Sensor Networks, to carry out control processes in real-time. This fact has meant that sev-eral communication standards, such as Zigbee PRO, WirelessHART and ISA100.11a, have been specified to ensure coexistence, reliability and se-curity in their communications. The main purpose of this paper has been to review these three standards and analyze their security. We have iden-tified a set of threats and potential attacks in their routing protocols, and we consequently provide recommendations and countermeasures to help Industry protect its infrastructures.
Medical diagnostic-based sensor selection
- IEEE Sensors
, 2011
"... Abstract—Wearable sensing systems have facilitated a variety of applications in Wireless Health. Due to the considerable number of sensors and their constant monitoring these systems are often expensive and power hungry. Traditional approaches to sensor selection in large multisensory arrays attempt ..."
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Cited by 8 (7 self)
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Abstract—Wearable sensing systems have facilitated a variety of applications in Wireless Health. Due to the considerable number of sensors and their constant monitoring these systems are often expensive and power hungry. Traditional approaches to sensor selection in large multisensory arrays attempt to alleviate these issues by removing redundant sensors while maintaining overall sensor predictability. However, predicting sensors is unnecessary if ultimately the system needs only to quantify diagnostic measurements specific to the application domain. We propose a new method for optimizing the design of medical sensor systems through diagnostic-based bottom-up sensor selection. We reduce the original sensor array from ninety nine to twelve sensors while maintaining a prediction error rate of less than 5 % over all diagnostic metrics in our testing dataset. I.
