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Power management in energy harvesting sensor networks
- Networked and Embedded Systems Laboratory, UCLA
, 2006
"... Power management is an important concern in sensor networks, because a tethered energy in-frastructure is usually not available and an obvious concern is to use the available battery energy efficiently. However, in some of the sensor networking applications, an additional facility is available to am ..."
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Cited by 232 (3 self)
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Power management is an important concern in sensor networks, because a tethered energy in-frastructure is usually not available and an obvious concern is to use the available battery energy efficiently. However, in some of the sensor networking applications, an additional facility is available to ameliorate the energy problem: harvesting energy from the environment. Certain considerations in using an energy harvesting source are fundamentally different from that in using a battery, be-cause, rather than a limit on the maximum energy, it has a limit on the maximum rate at which the energy can be used. Further, the harvested energy availability typically varies with time in a nondeterministic manner. While a deterministic metric, such as residual battery, suffices to charac-terize the energy availability in the case of batteries, a more sophisticated characterization may be required for a harvesting source. Another issue that becomes important in networked systems with multiple harvesting nodes is that different nodes may have different harvesting opportunity. In a distributed application, the same end-user performance may be achieved using different workload allocations, and resultant energy consumptions at multiple nodes. In this case, it is important to align the workload allocation with the energy availability at the harvesting nodes. We consider the above issues in power management for energy-harvesting sensor networks. We develop abstractions
Design considerations for solar energy harvesting wireless embedded systems
- IEEE SPOTS
, 2005
"... Sustainable operation of battery powered wireless embedded systems (such as sensor nodes) is a key challenge, and considerable research effort has been devoted to energy optimization of such systems. Environmental energy harvesting, in particular solar based, has emerged as a viable technique to sup ..."
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Cited by 182 (6 self)
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Sustainable operation of battery powered wireless embedded systems (such as sensor nodes) is a key challenge, and considerable research effort has been devoted to energy optimization of such systems. Environmental energy harvesting, in particular solar based, has emerged as a viable technique to supplement battery supplies. However, designing an efficient solar harvesting system to realize the potential benefits of energy harvesting requires an in-depth understanding of several factors. For example, solar energy supply is highly time varying and may not always be sufficient to power the embedded system. Harvesting compo-nents, such as solar panels, and energy storage elements, such as batteries or ultracapacitors, have different voltage-current characteristics, which must be matched to each other as well as the energy requirements of the system to maximize harvesting efficiency. Further, battery non-idealities, such as self-discharge and round trip efficiency, directly affect energy usage and storage decisions. The ability of the system to modulate its power consumption by selectively deactivating its sub-components also impacts the overall power management architecture. This paper describes key issues and tradeoffs which arise in the design of solar energy harvesting, wireless embedded systems and presents the design, implementation, and performance evaluation of Heliomote, our prototype that addresses several of these issues. Experimental results demonstrate that Heliomote, which behaves as a plug-in to the Berkeley/Crossbow motes and autonomously manages energy harvesting and storage, enables near-perpetual, harvesting aware operation of the sensor node.
Optimal Energy Management Policies for Energy Harvesting Sensor Nodes
"... We study a sensor node with an energy harvesting source. The generated energy can be stored in a buffer. The sensor node periodically senses a random field and generates a packet. These packets are stored in a queue and transmitted using the energy available at that time. We obtain energy management ..."
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Cited by 132 (4 self)
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We study a sensor node with an energy harvesting source. The generated energy can be stored in a buffer. The sensor node periodically senses a random field and generates a packet. These packets are stored in a queue and transmitted using the energy available at that time. We obtain energy management policies that are throughput optimal, i.e., the data queue stays stable for the largest possible data rate. Next we obtain energy management policies which minimize the mean delay in the queue. We also compare performance of several easily implementable sub-optimal energy management policies. A greedy policy is identified which, in low SNR regime, is throughput optimal and also minimizes mean delay.
Energy harvesting sensor nodes: Survey and implications
- Department of Computer Science and Engineering
, 2008
"... Sensor networks with battery-powered nodes can seldom simultaneously meet the design goals of lifetime, cost, sensing reliability and sensing and transmission coverage. Energy-harvesting, converting ambient energy to electrical energy, has emerged as an alternative to power sensor nodes. By exploiti ..."
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Cited by 125 (0 self)
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Sensor networks with battery-powered nodes can seldom simultaneously meet the design goals of lifetime, cost, sensing reliability and sensing and transmission coverage. Energy-harvesting, converting ambient energy to electrical energy, has emerged as an alternative to power sensor nodes. By exploiting recharge opportunities and tuning performance parameters based on current and expected energy levels, energy harvesting sensor nodes have the potential to address the conflicting design goals of lifetime and performance. This paper surveys various aspects of energy harvesting sensor systems — architecture, energy sources and storage technologies and examples of harvesting-based nodes and applications. The study also discusses the implications of recharge opportunities on sensor node operation and design of sensor network solutions. 1
Performance aware tasking for environmentally powered sensor networks
, 2004
"... The use of environmental energy is now emerging as a feasible energy source for embedded and wireless computing systems such as sensor networks where manual recharging or replacement of batteries is not practical. However, energy supply from environmental sources is highly variable with time. Furthe ..."
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Cited by 83 (4 self)
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The use of environmental energy is now emerging as a feasible energy source for embedded and wireless computing systems such as sensor networks where manual recharging or replacement of batteries is not practical. However, energy supply from environmental sources is highly variable with time. Further, for a distributed system, the energy available at its various locations will be different. These variations strongly influence the way in which environmental energy is used. We present a harvesting theory for determining performance in such systems. First we present a model for characterizing environmental sources. Second, we state and prove two harvesting theorems that help determine the sustainable performance level from a particular source. This theory leads to practical techniques for scheduling processes in energy harvesting systems. Third, we present our implementation of a real embedded system that runs on solar energy and uses our harvesting techniques. The system adjusts its performance level in response to available resources. Fourth, we propose a localized algorithm for increasing the performance of a distributed system by adapting the process scheduling to the spatio-temporal characteristics of the environmental energy in the distributed system. While our theoretical intuition is based on certain abstractions, all the scheduling methods we present are motivated solely from the experimental behavior and resource constraints of practical sensor networking systems.
The design and evaluation of a hybrid sensor network for cane-toad monitoring
, 2005
"... in Sensor Networks (IPSN/SPOTS) [Hu et al. 2005]. The paper features newer results on improving the lifetime of the sensor network for cane-toad monitoring through harvesting-aware sensor duty cycling algorithms. ..."
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Cited by 76 (8 self)
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in Sensor Networks (IPSN/SPOTS) [Hu et al. 2005]. The paper features newer results on improving the lifetime of the sensor network for cane-toad monitoring through harvesting-aware sensor duty cycling algorithms.
Adaptive control of duty cycling in energy-harvesting wireless sensor networks
- IN: SECON 2007. 4TH ANNUAL IEEE COMMUNICATIONS SOCIETY CONFERENCE ON SENSOR, MESH AND AD HOC COMMUNICATIONS AND NETWORKS
, 2007
"... Increasingly many wireless sensor network deployments are using harvested environmental energy to extend system lifetime. Because the temporal profiles of such energy sources exhibit great variability due to dynamic weather patterns, an important problem is designing an adaptive duty-cycling mechan ..."
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Cited by 53 (1 self)
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Increasingly many wireless sensor network deployments are using harvested environmental energy to extend system lifetime. Because the temporal profiles of such energy sources exhibit great variability due to dynamic weather patterns, an important problem is designing an adaptive duty-cycling mechanism that allows sensor nodes to maintain their power supply at sufficient levels (energy neutral operation) by adapting to changing environmental conditions. Existing techniques to address this problem are minimally adaptive and assume a priori knowledge of the energy profile. While such approaches are reasonable in environments that exhibit low variance, we find that it is highly inefficient in more variable scenarios. We introduce a new technique for solving this problem based on results from adaptive control theory and show that we achieve better performance than previous approaches on a broader class of energy source data sets. Additionally, we include a tunable mechanism for reducing the variance of the node’s duty cycle over time, which is an important feature in tasks such as event monitoring. We obtain reductions in variance as great as two-thirds without compromising task performance or ability to maintain energy neutral operation.
Asymptotically optimal power-aware routing for multihop wireless networks with renewable energy sources
- in Proceedings of IEEE INFOCOM
, 2005
"... Abstract — In this paper, we model and characterize the performance of multihop radio networks in the presence of energy constraints, and design routing algorithms to optimally utilize the available energy. The energy model allows vastly different energy sources in heterogeneous environments. The pr ..."
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Cited by 53 (4 self)
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Abstract — In this paper, we model and characterize the performance of multihop radio networks in the presence of energy constraints, and design routing algorithms to optimally utilize the available energy. The energy model allows vastly different energy sources in heterogeneous environments. The proposed algorithm is shown to achieve a competitive ratio (i.e., the ratio of the performance of any off-line algorithm that has knowledge of all past and future packet arrivals to the performance of our online algorithm) that is asymptotically optimal with respect to the number of nodes in the network. The algorithm assumes no statistical information on packet arrivals and can easily be incorporated into existing routing frameworks (e.g., proactive or on-demand methodologies) in a distributed fashion. Simulation results confirm that the algorithm performs very well in terms of maximizing the throughput of an energy-constrained network. Further, a new thresholdbased scheme is proposed to reduce the routing overhead while incurring only minimum performance degradation.
On broadcast authentication in wireless sensor networks
- In International Conference on Wireless Algorithms, Systems, and Applications (WASA 2006
, 2006
"... Abstract — Broadcast authentication is a critical security service in wireless sensor networks (WSNs), as it allows the mobile users of WSNs to broadcast messages to multiple sensor nodes in a secure way. Although symmetric-keybased solutions such as µTESLA and multilevel µTESLA have been proposed, ..."
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Cited by 45 (5 self)
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Abstract — Broadcast authentication is a critical security service in wireless sensor networks (WSNs), as it allows the mobile users of WSNs to broadcast messages to multiple sensor nodes in a secure way. Although symmetric-keybased solutions such as µTESLA and multilevel µTESLA have been proposed, they all suffer from severe energydepletion attacks resulting from the nature of delayed message authentication. This paper presents several efficient public-key-based schemes to achieve immediate broadcast authentication and thus avoid the security flaw inherent in the µTESLA-like schemes. Our schemes are built upon the unique integration of several cryptographic techniques, including the Bloom filter, the partial message recovery signature scheme and the Merkle hash tree. We prove the effectiveness and efficiency of the proposed schemes by a comprehensive quantitative analysis of their energy consumption in both computation and communication. I.
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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Cited by 44 (12 self)
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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.
