| D2K_magration_strategy () |
| { |
| Functional analysis of our D2K strategy can be performed through a triplet format, |
| that is, , where I is the input to the functions, P is the process |
| to describe the internal operations, and O is the output of the functions. |
| Data_ accumulation () |
| { |
| Input: raw data at motion (flow) |
| Output: raw data at rest (storage) |
| Process: use pull/push method to accumulate data |
| If (method = push) |
| {Sensors periodically sense environment and send data to CH} |
| If (method = pull) |
| {CH injects SQL into sensor environment to extract data} |
| CH performs data validations to check the correctness of the data |
| } |
| Replica_ elimination () |
| { |
| Input: raw sensor dataset |
| Output: distinct dataset |
| Process: data matching |
| If (old data value = new data value) |
| {CH discards to store the new value and the old value remains in the CH storage} |
| If (old data value != new data value) |
| {CH stores the new data value into its storage} |
| } |
| Data_ calibration () |
| { |
| Input: distinct dataset |
| Output: valid range dataset |
| Valid data range = [lb, ub] |
| // ub defines the upper threshold value |
| // lb defines the lower threshold value |
| Process: equivalence class partitioning |
| If (ub < distinct data < lb) |
| {CH treats these data as an invalid data class} |
| If (lb <= distinct data <= ub) |
| {CH treats these data as a valid data class} |
| CH rejects the invalid data class from its storage |
| } |
| Data_ fusion () |
| { |
| Input: valid dataset |
| Output: integrated database |
| Process: database operation |
| While (arrival of valid data = true) |
| { |
| CH maps the data into the database with its access key |
| } |
| } |
| Knowledge_ filtration () |
| { |
| Input: integrated database |
| Output: control instructions to be stored in the knowledge base |
| Process: fuzzy controller operation with a FIS |
| While (availability of integrated database = true) |
| {CH permits the database into a fuzzy controller circuitry embedded |
| with a FIS to extract the useful knowledge} |
| } |
| } |
