Earned Value Analysis for real time wireless sensor network

As Wireless Sensor Network (WSN) is spread across wide geographically area, global end-to-end estimates of control parameters can't predict timely reporting of data. However, as packet progresses over multihop WSN, routing decisions may have to be adapted according to changed environment parameters/conditions. Many algorithms lack dynamic adaptability to changed environment conditions. Real Time WSN need to trade off latency, path traversed in number of hops and energy cost as per dynamically changing conditions. Earned Value Management (EVM) is project management technique to trade-off schedule, cost and quality constraint. As part of this work, it is hereby suggested to adapt routing decision at each hop based on Earned Value Management of latency, energy cost and path traversed in number of hops at that time. At initial step, End-to-end estimated values for latency, energy cost and path traversed in number of hops are allocated for each flow. Estimate to complete (ETC) values for all parameters are calculated at each hop and used to decide how much is estimated remaining value of all parameters to reach at the destination. Based on ETC values, routing decisions can be adapted. At the end of delivery, variance with planned value is calculated. This value can be used to refine end-to-end estimates. The whole process can be divided into following steps: Estimate End-to-end values for latency, energy cost, number of hops, Estimate to complete (ETC) - Calculate Estimated Values for latency, energy cost, number of hops to reach at destination., Adapt or refine the control parameters such as speed or transmission power as per ETC values for latency, energy cost, number of hops. If destination can't be reached by adapting control parameters, packets are dropped., Calculate Variance with respect to planned values and refine end-to-end estimates Using Earned Value technique helps in tracking the actual progress made till current time. It helps in taking corrective action early; hence it is more cost effective. It also helps in effective usage of limited resources of WSN by dropping packets which can't reach destination within desired latency.