4 research outputs found
IDENTIFYING NETWORK FAULTS IN DATA CENTERS USING A COVARIANCE MATRIX
It may be difficult to identify root causes of protocol failures or degradations in application traffic performance due to errors. Embodiments presented herein identify the exact diagnostics needed to perform a root cause analysis. In particular, a covariance clustering methodology is used to generate correlated errors, which, when passed through a partial order set-based rule engine, are used to determine the root cause of a network fault due to protocol errors
AUTO-RECOVERY OF MICRO-SERVICES IN A LARGE DISTRIBUTED APPLIANCE MODEL
In large distributed application-based systems, an ensemble of co-existing micro-services perform individual functions and communicate with other micro-services. As these interactions and individual behaviors can be complex, it may be necessary to monitor micro-services for any abnormalities. Manual monitoring of all such micro-services, or establishing individual rule-based alerts for micro-services can be time-consuming. In addition to maintaining functionality of micro-services, it is important to prevent micro-services from becoming a performance bottleneck for other micro-services. In such situations, an alert may not suffice. For example, if a micro-service serves as a data store for all other services, a bottleneck at that micro-service may affect an entire system. By performing a predictive analysis of the health of micro-services, large distributed application-based systems can incorporate either preventive or reactive healing, thereby becoming auto-corrective in nature
SECURE SMART TRAFFIC LIGHT SYSTEM USING AUXILIARY DATA IN COOPERATIVE AWARENESS MESSAGE
Current smart traffic lights (STLs) can provide access to a traffic signal, which a vehicle, such as an emergency vehicle, can manipulate through a Cooperative Awareness Message (CAM) object. However, researchers have demonstrated that STLs can be easily hacked using an abusive CAM object. To address such a weakness, techniques are presented herein that secure a STL with auxiliary data that is attached to a CAM object, which can be used by a vehicle on-board unit (OBU) and smartphones. Aspects of the presented techniques reduce the encryption and decryption overhead that is incurred when attaching a security header as part of a CAM message. Further aspects of the presented techniques ensure that the authenticity and integrity of a CAM message can be validated through a roadside infrastructure (e.g., Roadside Units (RSUs)) and STLs with the help of a central server
AUDITING CONSTRUCTION QUALITY USING SATELLITE IMAGE TELEMETRY
Currently, the construction audit process is manual and as a result may yield inferior quality assurance data collection and report generation. Such an approach may lead to a construction project having poor quality. To address such challenges, techniques are presented herein that leverage satellites and their telemetry data. Aspects of the presented techniques support the remote auditing of construction quality and aid in completing the ‘detective work’ behind fraudulent construction claims (based on different construction parameters, the composition of the materials that are employed during construction, etc.). Further aspects of the presented techniques support estimating the ceiling life of a construction project; augmenting hyperspectral analysis with regular satellite imagery, thus creating a new view that helps to identify the composition of construction materials, the dimensions of a construction project, etc.; and the automatic generation of audit reports. Aspects of the presented techniques may be employed in a number of use cases including, for example, road quality determination, rooftop quality determination, public infrastructure (such as metro rail, etc.) quality determination, etc