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Wireless Sensor Networks Powered by Ambient Energy Harvesting (WSN-HEAP) – Survey and Challenges
"... Abstract—Wireless sensor networks (WSNs) research has predominantly assumed the use of a portable and limited energy source, viz. batteries, to power sensors. Without energy, a sensor is essentially useless and cannot contribute to the utility of the network as a whole. Consequently, substantial res ..."
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Abstract—Wireless sensor networks (WSNs) research has predominantly assumed the use of a portable and limited energy source, viz. batteries, to power sensors. Without energy, a sensor is essentially useless and cannot contribute to the utility of the network as a whole. Consequently, substantial research efforts have been spent on designing energy-efficient networking protocols to maximize the lifetime of WSNs. However, there are emerging WSN applications where sensors are required to operate for much longer durations (like years or even decades) after they are deployed. Examples include in-situ environmental/habitat monitoring and structural health monitoring of critical infrastructures and buildings, where batteries are hard (or impossible) to replace/recharge. Lately, an alternative to powering WSNs is being actively studied, which is to convert the ambient energy from the environment into electricity to power the sensor nodes. While renewable energy technology is not new (e.g., solar and wind) the systems in use are far too large for WSNs. Those small enough for use in wireless sensors are most likely able to provide only enough energy to power sensors sporadically and not continuously. Sensor nodes need to exploit the sporadic availability of energy to quickly sense and transmit the data. This paper surveys related research and discusses the challenges of designing networking protocols for such WSNs powered by ambient energy harvesting. I.
Wireless sensor networks with energy harvesting
- MOBILE AD HOC NETWORKING: CUTTING EDGE DIRECTIONS
, 2013
"... This chapter covers the fundamental aspects of energy harvesting-based wireless sensor networks (EHWSNs), ranging from the architecture of an EHWSN node and of its energy subsystem, to protocols for task allocation, MAC, and routing, passing through models for predicting energy availability. With th ..."
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This chapter covers the fundamental aspects of energy harvesting-based wireless sensor networks (EHWSNs), ranging from the architecture of an EHWSN node and of its energy subsystem, to protocols for task allocation, MAC, and routing, passing through models for predicting energy availability. With the advancement of energy harvesting techniques, along with the development of small factor harvester for many different energy sources, EHWSNs are poised to become the technology of choice for the host of applications that require the network to function for years or even decades. Through the definition of new hardware and communication protocols specifically tailored to the fundamentally different models of energy availability, new applications can also be conceived that rely on “perennial ” functionalities from networks that are truly self-sustaining and with low environmental impact. Wireless sensor networks (WSNs) have played a major role in the research field of multihop wireless networks as enablers of applications ranging from environmental
Pro-Energy: A novel energy prediction model for solar and wind energy-harvesting wireless sensor networks
- in Proceedings of IEEE MASS 2012, Las Vegas
, 2012
"... Abstract—Energy harvesting is one of the most promising technologies towards the goal of perpetual operation of wireless sensor networks (WSNs). Environmentally-powered systems, however, have to deal with the variable behavior of ambient energy sources, which results in different amounts and rates o ..."
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Abstract—Energy harvesting is one of the most promising technologies towards the goal of perpetual operation of wireless sensor networks (WSNs). Environmentally-powered systems, however, have to deal with the variable behavior of ambient energy sources, which results in different amounts and rates of energy available over time. To alleviate the problem of the harvested power being neither constant nor continuous, energy prediction methods can be employed. Such models forecast the source availability and estimate the expected energy intake, allowing the system to take critical decisions about the utiliza-tion of the available energy. In this work, we present a novel energy prediction model, named Pro-Energy (PROfile energy prediction model), for multi-source energy harvesting WSNs, which is able to leverage past energy observations to provide accurate estimations of future energy availability. To assess the performance of our proposed solution, we use real-life solar and wind traces that we collected by interfacing TelosB nodes with solar cells and wind micro-turbines, as well as public available traces of solar and wind obtained from weather monitoring stations in the US. A comparative performance evaluation between Pro-Energy and energy predictors previously proposed in the literature, such as EWMA and WCMA, has shown that our solution significantly outperforms existing algorithms for both short and medium term prediction horizons, improving the prediction accuracy up to 60%. Keywords-Energy predictions; Energy harvesting;
Adaptive Opportunistic Routing Protocol for Energy Harvesting Wireless Sensor Networks
"... Abstract—Using energy harvesting WSNs (EH-WSNs) are attractive as they can be solely powered by ambient energy sources. Multi-hop routing is important to achieve wide coverage as the transmission range of each node is limited. In this paper, we propose an adaptive opportunistic routing (AOR) protoco ..."
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Abstract—Using energy harvesting WSNs (EH-WSNs) are attractive as they can be solely powered by ambient energy sources. Multi-hop routing is important to achieve wide coverage as the transmission range of each node is limited. In this paper, we propose an adaptive opportunistic routing (AOR) protocol for multi-hop EH-WSNs that achieves high throughput using a regioning scheme that adapts to network conditions and energy availability. We evaluate AOR using extensive simulations incorporating experimental results from the characterization of different types of energy harvesters. The results show that AOR increases throughput in both monitoring and event-driven WSNs with different node densities and energy harvesting rates compared to traditional opportunistic routing protocols and other non-opportunistic routing protocols. We have also implemented AOR on a testbed of 20 energy harvesting sensor nodes and results show that AOR works well in EH-WSNs. I.
Research in Energy Harvesting Wireless Sensor Networks and the Challenges Ahead
"... Abstract—Wireless sensor networks (WSNs) are set to form a significant part of the new pervasive Internet, often referred to as the Internet of Things. WSNs have traditionally been powered by limited energy sources, viz. batteries, limiting their operational lifetime. To ensure the sustainability of ..."
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Abstract—Wireless sensor networks (WSNs) are set to form a significant part of the new pervasive Internet, often referred to as the Internet of Things. WSNs have traditionally been powered by limited energy sources, viz. batteries, limiting their operational lifetime. To ensure the sustainability of WSNs, researchers have turned to alternative energy sources for power. Harvesting ambient energy from the environment to power WSNs is a promising approach but it is currently unable to provide a sustained energy supply to support continuous operation. Sensor nodes therefore need to exploit the sporadic availability of energy to quickly sense and transmit the data. We first review the recent developments in energy harvesting technology and research on networking protocol design for Wireless Sensor Networks Powered by Ambient Energy Harvesting. Then, we discuss some of the challenges faced by researchers in designing networking protocols and summarize the open research problems. Index Terms—Energy harvesting/scavenging, Protocol design, Wireless sensor network.
OR-AHaD: An Opportunistic Routing Algorithm for Energy Harvesting WSN
, 2013
"... With recent advances, the trend has shifted from battery-powered wireless sensor networks towards ones powered by ambient energy harvesters (WSN-HEAP). In such networks, operability of the node is dependent on the harvesting rate which is usually stochastic in nature. Therefore, it is necessary to d ..."
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With recent advances, the trend has shifted from battery-powered wireless sensor networks towards ones powered by ambient energy harvesters (WSN-HEAP). In such networks, operability of the node is dependent on the harvesting rate which is usually stochastic in nature. Therefore, it is necessary to devise routing protocols with energy management capabilities that consider variations in the availability of the environmental energy. In this book chapter, we design OR-AHaD, an Opportunistic Routing algorithm with Adaptive Harvesting-aware Duty Cycling. In the proposed algorithm, candidates are primarily prioritized by applying geographical zoning and later coordinated in a timer-based fashion by exchanging coordination messages. An energy management model is presented which uses the estimated harvesting rate in the near future to adjust the duty cycle of each node adaptively. Simulation results show that OR-AHaD exploits the available energy resources in an efficient way and increases goodput in comparison to other opportunistic routing protocols for WSN-HEAP.
Opportunistic Routing with Adaptive Harvesting-aware Duty Cycling in Energy Harvesting WSN
"... Abstract—With recent advances, the trend has shifted from battery-powered wireless sensor networks towards ones powered by ambient energy harvesters (WSN-HEAP). In such networks, operability of the node is dependent on the harvesting rate which is usually stochastic in nature. Therefore, it is neces ..."
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Abstract—With recent advances, the trend has shifted from battery-powered wireless sensor networks towards ones powered by ambient energy harvesters (WSN-HEAP). In such networks, operability of the node is dependent on the harvesting rate which is usually stochastic in nature. Therefore, it is necessary to devise routing protocols with energy management capabilities that consider variations in the availability of the environmental energy. In this paper, we design OR-AHaD, an Opportunistic Routing algorithm with Adaptive Harvesting-aware Duty Cycling. In the proposed algorithm, candidates are primarily prioritized by applying geographical zoning and later coordinated in a timer-based fashion by exchanging coordination messages. An energy management model is presented that uses the estimated harvesting rate in the near future to adjust the duty cycle of each node adaptively. Simulation results show that OR-AHaD exploits the available energy resources in an efficient way and increases goodput in comparison to other opportunistic routing protocols for WSN-HEAP. I.
Research Article Modeling and Simulation of a Novel Relay Node Based Secure Routing Protocol Using Multiple Mobile Sink for Wireless Sensor Networks
"... Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Data gathering and optimal path selection for wireless sensor networks (WSN) using existing protocols result in collision. Increase in collision further in ..."
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Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Data gathering and optimal path selection for wireless sensor networks (WSN) using existing protocols result in collision. Increase in collision further increases the possibility of packet drop. Thus there is a necessity to eliminate collision during data aggregation. Increasing the efficiency is the need of the hour with maximum security. This paper is an effort to come up with a reliable and energy efficientWSN routing and secure protocol withminimum delay.This technique is named as relay node based secure routing protocol for multiple mobile sink (RSRPMS). This protocol finds the rendezvous point for optimal transmission of data using a “splitting tree ” technique in tree-shaped network topology and then to determine all the subsequent positions of a sink the “Biased RandomWalk ” model is used. In case of an event, the sink gathers the data from all sources, when they are in the sensing range of rendezvous point.Otherwise relay node is selected from its neighbor to transfer packets from rendezvous point to sink. A symmetric key cryptography is used for secure transmission. The proposed relay node based secure routing protocol for multiple mobile sink (RSRPMS) is experimented and simulation results are compared with Intelligent Agent-Based Routing (IAR) protocol to prove that there is increase in the network lifetime compared with other routing protocols. 1.
ADistributed Optimal Lexicographic Max-min Rate Allocation in Solar Powered Wireless Sensor Networks
"... Understanding the optimal usage of fluctuating renewable energy in Wireless Sensor Networks (WSNs) is complex. Lexicographic Max-min (LM) rate allocation is a good solution, but is non-trivial for multi-hop WSNs, as both fairness and sensing rates have to be optimized through the exploration of all ..."
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Understanding the optimal usage of fluctuating renewable energy in Wireless Sensor Networks (WSNs) is complex. Lexicographic Max-min (LM) rate allocation is a good solution, but is non-trivial for multi-hop WSNs, as both fairness and sensing rates have to be optimized through the exploration of all possible forwarding routes in the network. All current optimal approaches to this problem are centralized and off-line, suffering from low scalability and large computational complexity; typically solving O(N2) linear programming problems for N-node WSNs. This paper presents the rst optimal distributed solution to this problem with much lower complexity. We apply it to Solar Powered WSNs (SP-WSNs) to achieve both LM optimality and sustainable operation. Based on realistic models of both time-varying solar power and photovoltaic-battery hardware, we propose an optimization framework that integrates a local power management algorithm with a global distributed LM rate allocation scheme. The optimality, convergence, and efficiency of our approaches are formally proven. We also evaluate our algorithms via experiments on both solar-powered MicaZ motes and extensive simulations using real solar energy data and practical power parameter settings. The results verify our theoretical analysis and demonstrate how our approach outperforms both the state-of-the-art centralized optimal and distributed heuristic solutions.
