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Power Management in Wireless Sensor Network

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Power Management in Wireless Sensor Network

  1. 1. Power Management in Sensor Networks Bhavik Panchal WIMC Feb 13,2014 1
  2. 2. Need for Power Management 1. Sensor nodes are battery driven and they must have a lifetime on the order of months to years. 2. Battery replacement is not an option for networks with thousands of physically embedded nodes. 3. In some cases, these networks may be required to operate solely on energy scavenged from the environment through seismic, photovoltaic, or thermal conversion. 2
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  4. 4. The wireless sensor node is node is comprised of four subsystems: i) a computing subsystem consisting of a microprocessor or micro controller, ii) a communication subsystem consisting of a short range radio for wireless communication, iii) a sensing subsystem that links the node to the physical world and consists of a group of sensors and actuators, and iv) a power supply subsystem, which houses the battery and the dc-dc converter, and powers the rest of the node. 4
  5. 5. Microcontroller Unit 1. MCUs usually support various operating modes, including Active, Idle, and Sleep modes, for power management. 2. However, transitioning between operating modes involves a power and latency overhead. 5
  6. 6. Radio In general, radios can operate in four distinct modes of operation: Transmit, Receive, Idle, and Sleep. An important observation in the case of most radios is that operating in Idle mode results in significantly high power consumption, almost equal to the power consumed in the Receive mode. As that as the radio’s operating mode changes, the transmit activity in the radio electronics causes a significant amount of power consumed. 6
  7. 7. Sensors Sources of power consumption in a sensor 1. signal sampling and conversion of physical signals to electrical ones 2. signal conditioning 3. analog-to-digital conversion In general, however, passive sensors such as temperature,consume negligible power relative to other components of sensor node. 7
  8. 8. Battery Issues The operation of batteries depends on many factors like 1. battery dimensions, 2. type of electrode material used Unfortunately, depending on the battery type (lithium ion, NiMH, NiCd, alkaline, etc.), the minimum required current consumption of sensor nodes often exceeds the rated current capacity, leading to suboptimal battery lifetime. 8
  9. 9. DC-DC CONVERTER The efficiency factor associated with the converter plays a big role in determining battery lifetime. A low efficiency factor leads to significant energy loss in the converter, reducing the amount of energy available to other sensor node components. Also, the voltage level across the battery terminals constantly decreases as it gets discharged. 9
  10. 10. Energy-Aware Software Sensor network lifetime can be significantly enhanced if the system software, including the operating system (OS), application layer, and network protocols, are all designed to be energy aware. Network-Wide Energy Optimization The network as a whole should be energy aware, for which the network-level global decisions should be energy aware. 10
  11. 11. Traffic Distribution The protocols that provide an energy efficient multihop route between source and destination does not always maximize the network lifetime. It is desirable to avoid routes through regions of the network that are running low on energy resources, thus preserving them for future. It is, in general, undesirable to continuously forward traffic via the same path, even though it minimizes the energy. 11
  12. 12. Topology Management In typical deployment scenarios, a dense network is required to ensure adequate coverage of both the sensing and multihop routing functionality, in addition to improving network fault-tolerance. Denser distributions of sensors lead to increasingly tracking results but it reduces network lifetime. 12
  13. 13. Conclusion We discussed several energy optimization and management techniques at node, link, and network level, which can lead to significant enhancement in sensor network lifetime. 13
  14. 14. References: POWER MANAGEMENT IN WIRELESS SENSOR NETWORK WITH HIGH CONSUMING SENSOR, Vana Jelicic IEEE PAPER. POWER SAVING AND ENERGY OPTIMIZATION TECHNIQUES FOR WIRELESS SENSOR NETWORK, Sandra Sendra, Jaime Lloret, Miguel García and José F. Toledo IEEE PAPER. 14

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