In Network Processing and Data Aggregation in

2) Use of Multiple parents: Due to the broadcast nature of radio, data redundancy isvery often and while from one perspective this provides more reliability, on the otherhand in MAX-MIN a node may be counted multiple times. A possible solution to thisproblem is to send part of the aggregate to one parent and the rest to the other. In thatway, there is the benefit that the variance of the multiple parent COUNT is much less,although its expected value is the same. In other words, a single loss will affect less thecomputed value.3) Hypothesis Testing: The above optimizations still require an input from every nodeof a network in order to compute an aggregate. Sometimes we need to hear from aparticular sensor its sensed value in order to figure out if it will affect the value of theaggregate. The node decides locally whether contributing its reading and the readings ofits children will affect the value of the aggregate.For the case of MIN(or MAX) hypothesis testing can be done even with snooping orpipelined aggregate over the k-first levels of the aggregate tree.For COUNT/SUM/AVERAGE the user defines an error_bound. If the value of theleaf is within the defined error_bound, then is remains silent and its parent keeps the oldapproximate answer, else the child forwards its own value to its parent.3.4.2 Multipath TechniquesRecently the research community of WSNs has turned its interest from the tree basedaggregation schemes to multi-path graphs where multiple edges can exist between twonodes. This field is continuously gaining more attention and the reason for this is the factthat the data which is sent from a sensor to the others can be easily lost due to the largecommunication error rate of wireless communication.The rationale behind multi-path graph is as follows: instead of requiring from eachnode to send its accumulated partial result to its single parent in an aggregation tree, themulti-path approach exploits the characteristics of the wireless broadcast medium byforcing each node to broadcast its partial result to multiple neighbors. Furthermore, thisapproach sends the same minimal number of messages as the tree approach (i.e., onetransmission per node), which makes it energy-efficient. Also it is very robust in means