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Ratnadeep Bhattacharya

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Papers by Ratnadeep Bhattacharya

Research paper thumbnail of BLOC: Balancing Load with Overload Control In the Microservices Architecture

2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS)

Research paper thumbnail of Load Balancing for Microservice Service Meshes

2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)

Research paper thumbnail of Mu: An Efficient, Fair and Responsive Serverless Framework for Resource-Constrained Edge Clouds

Proceedings of the ACM Symposium on Cloud Computing, 2021

Serverless computing platforms simplify development, deployment, and automated management of modu... more Serverless computing platforms simplify development, deployment, and automated management of modular software functions. However, existing serverless platforms typically assume an over-provisioned cloud, making them a poor fit for Edge Computing environments where resources are scarce. In this paper we propose a redesigned serverless platform that comprehensively tackles the key challenges for serverless functions in a resource constrained Edge Cloud. Our Mu platform cleanly integrates the core resource management components of a serverless platform: autoscaling, load balancing, and placement. Each worker node in Mu transparently propagates metrics such as service rate and queue length in response headers, feeding this information to the load balancing system so that it can better route requests, and to our autoscaler to anticipate workload fluctuations and proactively meet SLOs. Data from the Autoscaler is then used by the placement engine to account for heterogeneity and fairness ...

Research paper thumbnail of Smart proxying for microservices

Proceedings of the 20th International Middleware Conference Doctoral Symposium, 2019

Proxies provide the networking infrastructure to the microservices architecture which has become ... more Proxies provide the networking infrastructure to the microservices architecture which has become ubiquitous in the cloud today. However, these proxies either cannot operate at line rate or are unsuitable for generic deployments. Furthermore, state-of-the-art autoscaling algorithms are still unable to account for quality of service the applications need to provide. In my dissertation I plan to explore a split proxy architecture that would be able to operate at line rate and provide autoscaling services that take into account QoS. Furthermore, such disaggregated L4/L7 processing provides a unique opportunity to embed DDoS mitigation like security features within the proxy framework.

Research paper thumbnail of BLOC: Balancing Load with Overload Control In the Microservices Architecture

2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS)

Research paper thumbnail of Load Balancing for Microservice Service Meshes

2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)

Research paper thumbnail of Mu: An Efficient, Fair and Responsive Serverless Framework for Resource-Constrained Edge Clouds

Proceedings of the ACM Symposium on Cloud Computing, 2021

Serverless computing platforms simplify development, deployment, and automated management of modu... more Serverless computing platforms simplify development, deployment, and automated management of modular software functions. However, existing serverless platforms typically assume an over-provisioned cloud, making them a poor fit for Edge Computing environments where resources are scarce. In this paper we propose a redesigned serverless platform that comprehensively tackles the key challenges for serverless functions in a resource constrained Edge Cloud. Our Mu platform cleanly integrates the core resource management components of a serverless platform: autoscaling, load balancing, and placement. Each worker node in Mu transparently propagates metrics such as service rate and queue length in response headers, feeding this information to the load balancing system so that it can better route requests, and to our autoscaler to anticipate workload fluctuations and proactively meet SLOs. Data from the Autoscaler is then used by the placement engine to account for heterogeneity and fairness ...

Research paper thumbnail of Smart proxying for microservices

Proceedings of the 20th International Middleware Conference Doctoral Symposium, 2019

Proxies provide the networking infrastructure to the microservices architecture which has become ... more Proxies provide the networking infrastructure to the microservices architecture which has become ubiquitous in the cloud today. However, these proxies either cannot operate at line rate or are unsuitable for generic deployments. Furthermore, state-of-the-art autoscaling algorithms are still unable to account for quality of service the applications need to provide. In my dissertation I plan to explore a split proxy architecture that would be able to operate at line rate and provide autoscaling services that take into account QoS. Furthermore, such disaggregated L4/L7 processing provides a unique opportunity to embed DDoS mitigation like security features within the proxy framework.

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