Interactive, Constraint-Network Prognostics and Diagnostics To Control Errors and Conflicts (IPDN)

Abstract

Methods for interactively preventing and detecting conflicts and errors (CEs) through prognostics and diagnostics. Centralized and Decentralized Conflict and Error Prevention and Detection (CEPD) Logic is developed for prognostics and diagnostics over three types of real-world constraint networks: random networks (RN), scale-free networks (SFN), and Bose-Einstein condensation networks (BECN). A method is provided for selecting an appropriate CEPD algorithm from a plurality of algorithms having either centralized or decentralized CEPD logic, based on analysis of the characteristics of the CEPD algorithms and the characteristics of the constraint network.

1 . A system, comprising:
 two or more cooperative units, wherein the two or more cooperative units periodically exhibit conflicts and errors,   at least one control unit configured to;
 receive a list of parameters associated with the cooperative units and interactions between the cooperative units; 
 perform conflict and error detection, including:
 a) providing a list of at least two constraints, each constraint defining a task to be accomplished or a requirement to be satisfied by one or more cooperative units by a first time; 
 b) identifying one or more constraints from the list, which need to be satisfied by a defined time; 
 c) identifying for each identified constraint whether any conflict or error exists, where a conflict occurs whenever an inconsistency between two or more cooperative units occurs, and an error is associated with any condition that is inconsistent with the list of parameters; 
 d) marking the constraints for which an error or conflict has been identified; 
 e) incrementing a mark count for each cooperative unit associated with each marked constraint; 
 
 perform at least one of diagnosis and prognosis based at least in part on the marked constraints. 
   
     
     
         2 . The system of  claim 1 , wherein the at least one control unit is further configured to perform diagnosis, including:
 f) identifying each constraint having a first predefined relationship with each constraint marked in d); and   g) marking the constraints identified in f).   
     
     
         3 . The system of  claim 2 , wherein the predetermined relationship includes a condition wherein a time associated with the identified constraint is the same or earlier than a time associated with the constraint marked in step d). 
     
     
         4 . The system of  claim 3 , wherein the at least control unit is further configured to perform prognosis, including:
 h) identifying each constraint having a second predefined relationship with each constraint marked in d); and   i) marking the constraints identified in h).   
     
     
         5 . The system of  claim 2 , wherein the predetermined relationship includes a condition wherein a time associated with the identified constraint is later than a time associated with the constraint marked in step d). 
     
     
         6 . The system of  claim 1 , wherein the at least one control unit is further configured to:
 create and update at least one constraint (C) table using the list of parameters associated with the cooperative units and interactions between the cooperative units; and   use the constraint table in step e) to identify each cooperative unit associated with each constraint marked in step d).   
     
     
         7 . The method of  claim 6 , wherein the at least one control unit is further configured to:
 model dependencies between constraints to form at least one relationship (R) table using the C table and the list of parameters associated with a system of cooperative units and interactions between the cooperative units; and   use the at least one R table in performing the at least one of diagnosis and prognosis in the at least one control unit.   
     
     
         8 . The system of  claim 7 , wherein the at least one control unit is further configured to establish and update a constraint network encompassing the constraints and their dependencies using the C and R tables, wherein each node in the constraint network is represented by a constraint and links between nodes represent relationships between constraints. 
     
     
         9 . The system of  claim 1 , wherein the at least one control unit further stores a relationship (R) table of defined relationships between constraints, and wherein
 the at least control unit is configured to use the at least one R table in performing the at least one of diagnosis and prognosis in the at least one control unit.   
     
     
         10 . The system of  claim 9 , wherein the R table includes at least one inclusive relationship between a first pair of constraints, and the R table includes at least one mutually exclusive relationship between a second pair of constraints. 
     
     
         11 . The system of  claim 1 , wherein the at least one control unit is further configured to mark in a different manner the constraints for which an error or conflict has not been identified. 
     
     
         12 . The system of  claim 1 , wherein the at least one control unit is further configured to cause visualization of steps a), b) and c) and enable interactions between users based at least in part on using Petri nets or other state transition graphs. 
     
     
         13 . A system, comprising:
 two or more cooperative units, wherein the two or more cooperative units periodically exhibit conflicts and errors,   at least one control unit storing a relationship (R) table identifying relationships between constraints, the at least one control unit configured to;
 receive a list of parameters associated with the cooperative units and interactions between the cooperative units; 
 perform conflict and error detection, including:
 a) providing a list of at least two constraints, each constraint defining a task to be accomplished or a requirement to be satisfied by one or more cooperative units by a first time; 
 b) identifying one or more constraints from the list, which need to be satisfied by a defined time; 
 c) identifying for each identified constraint whether any conflict or error exists, where a conflict occurs whenever an inconsistency between two or more cooperative units occurs, and an error is associated with any condition that is inconsistent with the list of parameters; 
 d) marking the constraints for which an error or conflict has been identified; 
 e) incrementing a mark count for each cooperative unit associated with each marked constraint; 
 f) for at least one constraint marked in step d, mark another constraint based on the R table; 
 
 perform at least one of diagnosis and prognosis based at least in part on the marked constraints. 
   
     
     
         14 . The system of  claim 13 , wherein the R table includes at least one mutually exclusive relationship between a pair of constraints. 
     
     
         15 . The system of  claim 13 , wherein the R table includes at least one inclusive relationship between a first pair of constraints. 
     
     
         16 . The system of  claim 16 , wherein the R table includes at least one mutually exclusive relationship between a second pair of constraints. 
     
     
         17 . The system of  claim 16 , wherein the at least one control unit is configured to use the R table in performing the at least one of diagnosis and prognosis in the at least one control unit. 
     
     
         18 . The system of  claim 13 , wherein the at least one control unit is configured to use the R table in performing the at least one of diagnosis and prognosis in the at least one control unit.