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Serverless computing is a buzzword that is being used commonly in the world of technology and among developers and businesses. Using the Function-as-a-Service (FaaS) model of serverless, one can easily deploy their applications to the cloud and go live in a matter of days, it facilitates the developers to focus on their core business logic and the backend process such as managing the infrastructure, scaling of the application, updation of software and other dependencies is handled by the Cloud Service Provider. One of the features of serverless computing is ability to scale the containers to zero, which results in a problem called cold start. The challenging part is to reduce the cold start latency without the consumption of extra resources. In this paper, we use SARIMA (Seasonal Auto Regressive Integrated Moving Average), one of the classical time series forecasting models to predict the time at which the incoming request comes, and accordingly increase or decrease the amount of required containers to minimize the resource wastage, thus reducing the function launching time. Finally, we implement PBA (Prediction Based Autoscaler) and compare it with the default HPA (Horizontal Pod Autoscaler), which comes inbuilt with kubernetes. The results showed that PBA performs fairly better than the default HPA, while reducing the wastage of resources.

With the increasing adoption of private blockchain platforms, consortia operating in various sectors such as trade, finance, logistics, etc., are becoming common. Despite having the benefits of a completely decentralized architecture which supports transparency and distributed control, existing private blockchains limit the data, assets, and processes within its closed boundary, which restricts secure and verifiable service provisioning to the end-consumers. Thus, platforms such as e-commerce with multiple sellers or cloud federation with a collection of cloud service providers cannot be decentralized with the existing blockchain platforms. This paper proposes a decentralized gateway architecture interfacing private blockchain with end-users by leveraging the unique combination of public and private blockchain platforms through interoperation. Through the use case of decentralized cloud federations, we have demonstrated the viability of the solution. Our testbed implementation with Ethereum and Hyperledger Fabric, with three service providers, shows that such consortium can operate within an acceptable response latency while scaling up to 64 parallel requests per second for cloud infrastructure provisioning. Further analysis over the Mininet emulation platform indicates that the platform can scale well with minimal impact over the latency as the number of participating service providers increases., Comment: 10 pages, 12 figures, accepted for publication in IEEE INFOCOM 2021

Serverless computing has gained a significant traction in recent times because of its simplicity of development, deployment and fine-grained billing. However, while implementing complex services comprising databases, file stores, or more than one serverless function, the performance in terms of latency of serving requests often degrades severely. In this work, we analyze different serverless architectures with AWS Lambda services and compare their performance in terms of latency with a traditional virtual machine (VM) based approach. We observe that database access latency in serverless architecture is almost 14 times than that in VM based setup. Further, we introduce some caching strategies which can improve the response time significantly, and compare their performance.