Abstract
Energy constrained systems such as sensor networks can increase their usable lifetimes by extracting energy from their environment. However, environmental energy will typically not be spread homogeneously over the spread of the network. We argue that significant improvements in usable system lifetime can be achieved if the task allocation is aligned with the spatio-temporal characteristics of energy availability. To the best of our knowledge, this problem has not been addressed before. We present a distributed framework for the sensor network to adaptively learn its energy environment and give localized algorithms to use this information for task sharing among nodes. Our framework allows the system to exploit its energy resources more efficiently, thus increasing its lifetime. These gains are in addition to those from utilizing sleep modes and residual energy based scheduling mechanisms. Performance studies for an experimental energy environment show up to 200% improvement in lifetime.
Keywords
USableExploitComputer scienceWireless sensor networkEnergy harvestingEnergy (signal processing)Distributed computingScheduling (production processes)Task (project management)Efficient energy useResidualReal-time computingComputer networkEngineeringComputer security
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Publication Info
- Year
- 2003
- Type
- article
- Pages
- 481-481
- Citations
- 276
- Access
- Closed
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Cite This
Aman Kansal,
Mani Srivastava
(2003).
An environmental energy harvesting framework for sensor networks.
, 481-481.
https://doi.org/10.1145/871506.871624
Identifiers
- DOI
- 10.1145/871506.871624