Stochastic Power Modeling of Wireless Sensor Networks for Mission Critical Systems

Wireless Sensor nodes consist of communication devices, physical devices (environmental Sensors), processing unit, memory and radio. Optimizing the power consumed by the sensor nodes is always a challenge. The power consumed during communication is high. Therefore, optimizing the power and energy during communication is really necessary. This paper addresses this issue by implementing stochastic power model of wireless sensor nodes to handle any Mission Critical Systems (MCS). Mission Critical Systems are systems that handle tasks and accomplish the real-time deadlines. If a deadline is not met, something catastrophe may occur and the sensor nodes sleep during critical times which will lead to an unstable system. So instead of going to sleep state, the state changes to idle state to handle critical tasks. In this paper, the motes are characterized using Semi Markov Decision Process (SMDP). Various policies were framed for Non-Critical and Mission Critical Systems. Mission Critical Systems uses nodes that meet the deadlines, thereby, optimizing the power and energy used. Our experimental setup improves the energy efficiency of MCS by at least 25%. The model is validated using Crossbow Sensor motes. Also, the model selects the action in the node in order to suggest the best policy for better energy optimization. The SMDP modeling is solved by Dynamic programming using the value iteration function with discounted rewards. Our results have shown that the nodes can go from active to sleep state for non-critical applications and active to semi-sleep state for mission critical application. Our performance results have shown that 25% more power saving is achieved.

@article{Krishna2018,
  title     = {Stochastic Power Modeling of Wireless Sensor Networks for Mission Critical Systems},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {9},
  number    = {1},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {P. Venkata Krishna and T. S. Pradeepkumar and Mohammad S. Obaidat and V. Saritha},
  doi       = {10.14569/SpecialIssue.2018.0901135},
  url       = {https://doi.org/10.14569/SpecialIssue.2018.0901135}
}