Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The use of Complex Event Processing (CEP) and Stream Processing (SP) systems to process high-volume, high-velocity Big Data has rened interest in procedures for managing these systems. In particular, self-management and adaptation of runtime platforms have been common research themes, as most of these systems run under dynamic conditions. Nevertheless, the research landscape in this area is still young and fragmented. Most research is performed in the context of specific systems, and it is difficult to generalize the results obtained to other contexts. To enable generic and reusable CEP/SP system management procedures and self-management policies, this research introduces the Attributed Graph Rewriting for Complex Event Processing Management ( AGeCEP ) formalism.  AGeCEP  represents queries in a language- and technology-agnostic fashion using attributed graphs. Query reconfiguration capabilities are expressed through standardized attributes, which are defined based on a novel classification of CEP query operators. By leveraging this representation,  AGeCEP  also proposes graph rewriting rules to define consistent reconfigurations of queries. To demonstrate  AGeCEP  feasibility, this research has used it to design an autonomic manager and to define a selected set of self-management policies. Finally, experiments demonstrate that  AGeCEP  can indeed be used to develop algorithms that can be integrated into diverse CEP systems.
['Wilson A. Higashino', 'Cédric Eichler', 'Miriam A. M. Capretz', 'Luiz F. Bittencourt', 'Thierry Monteil']
I am writing a research paper on a idea Attributed Graph Rewriting for Complex Event Processing Self-Management
[{"from": "human", "value": "I am writing a research paper on a idea Attributed Graph Rewriting for Complex Event Processing Self-Management"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The use of Complex Event Processing (CEP) and Stream Processing (SP) systems to process high-volume, high-velocity Big Data has rened interest in procedures for managing these systems. In particular, self-management and adaptation of runtime platforms have been common research themes, as most of these systems run under dynamic conditions. Nevertheless, the research landscape in this area is still young and fragmented. Most research is performed in the context of specific systems, and it is difficult to generalize the results obtained to other contexts. To enable generic and reusable CEP/SP system management procedures and self-management policies, this research introduces the Attributed Graph Rewriting for Complex Event Processing Management ( AGeCEP ) formalism.  AGeCEP  represents queries in a language- and technology-agnostic fashion using attributed graphs. Query reconfiguration capabilities are expressed through standardized attributes, which are defined based on a novel classification of CEP query operators. By leveraging this representation,  AGeCEP  also proposes graph rewriting rules to define consistent reconfigurations of queries. To demonstrate  AGeCEP  feasibility, this research has used it to design an autonomic manager and to define a selected set of self-management policies. Finally, experiments demonstrate that  AGeCEP  can indeed be used to develop algorithms that can be integrated into diverse CEP systems."}]