Energy conservation in wireless sensor networks
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Energy conservation in wireless sensor networks
- 1. Energy Conservation in Wireless Sensor Networks Under supervision: Dr. Ahmed Akl Presented by: Ahmed Reda Elshami Course Code: CC735 1CC73510/7/2013
- 2. Overview • Introduction • Challenge • Architecture of a typical WSN • Power breakdown • Basic Approaches • Taxonomy approaches • Future Work • Questions • Reference 2CC73510/7/2013
- 3. Introduction • A wireless sensor network consists of sensor nodes deployed over a geographical area for monitoring physical phenomena like temperature, humidity, vibrations and so on. 3CC73510/7/2013
- 4. Challenge • Power, Power, Power, … • Life time with two AA batteries ≈ 20 days • Processing capacity evolution VS. Battery capacity evolution 4CC73510/7/2013
- 5. Architecture of a typical wireless sensor node • sensor node is a tiny device that includes four main components MCU = Microcontroller Unit ADC = Analog Digital Converter DC-DC = Direct current to Direct current converter 5CC73510/7/2013
- 6. Power breakdown • The communication subsystem > computation subsystem • The radio energy consumption is of the same order in the reception = transmission = and idle states, while the power consumption drops of at least one order of magnitude in the sleep state. • Depending on the specific application, the sensing subsystem might be another significant source of energy consumption 6CC73510/7/2013
- 7. Basic Approaches to Energy Conservation in WSNs Basic Approaches to Energy Conservation in WSNs Duty cycling Data-driven approach Mobility approach 7CC73510/7/2013
- 8. Duty Cycling Duty Cycling Topology Control Power Management Sleep/Wakeup protocol MAC protocol with low Duty Cycle 8CC73510/7/2013
- 11. Taxonomy approaches to energy savings in sensor networks 11CC73510/7/2013
- 12. Future Work • The integration of the different approaches into a single off-the-shelf workable solution • Many real applications have shown the power consumption of the sensor is comparable to, or even greater than, the power needed by the radio. 12CC73510/7/2013
- 14. Reference • Giuseppe Anastasi, Marco Conti, Mario Di Francesco, Andrea Passarella, (2008), Energy Conservation in Wireless Sensor Networks: a Survey. Elsevier B.V 14CC73510/7/2013
Editor's Notes
- sensor nodes are generally battery-powered devices on-board processing wireless communication sensing capabilities
- Reduce energy consumption of nodes, so that the network lifetime can be extended to reasonable times external power supply sources often exhibit a non-continuous behavior so that an energy buffer is needed as well
- Sensing - for data acquisition from the physical surrounding environment Processing - for local data processing and storage Communication - for data transmission Power - supplies the energy needed by the device to perform the programmed task location finding system to determine their position a mobilizer to change their location or configuration (e.g., antenna’s orientation), and so on external power supply sources often exhibit a non-continuous behavior so that an energy buffer is needed as well
- duty cycle is defined as the fraction of time nodes are active during their lifetime Duty cycling is mainly focused on the networking subsystem the radio should be switched off as soon as there is no more data to send/receive Topology Control - By node redundancy - select only a minimum subset of nodes to remain active for maintaining connectivity otherwise sleep mode nodes selected by the topology control protocol do not need to maintain their radio continuously on. They can switch off the radio increasing the network lifetime by a factor of 2-3 compare to all nodes always on
- data acquisition schemes are mainly aimed at reducing the energy spent by the sensing subsystem. Data reduction all these techniques aim at reducing the amount of data to be delivered to the sink node In-network processing performing data aggregation(e.g., computing average of some values) at intermediate nodes between the sources and the sink. result, the amount of data is reduced while traversing the network towards the sink Data compression – encoding @ sender & decoding information @ Slink Data prediction – building model describing data evolution within certain error bounds & stored @ node and sink node
- Mobile Node part of the network infrastructure = fully controlled Mobile Node part of the environment = might be not controllable ex: if they follow strict schedule, then they have a completely predictable mobility otherwise they will have random behavior
- 2- We assume the energy consumption of the radio is > energy consumption due to data sampling or data processing, however