Faculty Publications
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Item Shipping code towards data in an inter-region serverless environment to leverage latency(Springer, 2023) Sethi, B.; Addya, S.K.; Bhutada, J.; Ghosh, S.K.Serverless computing emerges as a new standard to build cloud applications, where developers write compact functions that respond to events in the cloud infrastructure. Several cloud service industries started adopting serverless for deploying their applications. But one key limitation in serverless computing is that it disregards the significance of data. In the age of big data, when applications run around a huge volume, to transfer data from the data side to the computation side to co-allocate the data and code, leads to high latency. All existing serverless architectures are based on the data shipping architecture. In this paper, we present an inter-region code shipping architecture for serverless, that enables the code to flow from computation side to the data side where the size of the code is negligible compared to the data size. We tested our proposed architecture over a real-time cloud platform Amazon Web Services with the integration of the Fission serverless tool. The evaluation of the proposed code shipping architecture shows for a data file size of 64 MB, the latency in the proposed code shipping architecture is 8.36 ms and in existing data shipped architecture is found to be 16.8 ms. Hence, the proposed architecture achieves a speedup of 2x on the round latency for high data sizes in a serverless environment. We define round latency to be the duration to read and write back the data in the storage. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.Item ESMA: Towards elevating system happiness in a decentralized serverless edge computing framework(Academic Press Inc., 2024) Datta, S.; Addya, S.K.; Ghosh, S.K.Due to the rapid growth in the adoption of numerous technologies, such as smartphones and the Internet of Things (IoT), edge and serverless computing have started gaining momentum in today's computing infrastructure. It has led to the production of huge amounts of data and has also resulted in increased network traffic, which if not managed well can cause network congestion. To address this and maintain the quality of service (QoS), in this work, a novel dispatch (destination selection) algorithm called Egalitarian Stable Matching Algorithm (ESMA) for faster data processing has been developed while also considering the best use of server resources in a decentralized Serverless-Edge environment. This will allow us to effectively utilize the enormous volumes of data that are generated. The proposed algorithm has been able to achieve lower overall dissatisfaction scores for the entire system. Individually, the client's happiness as well as the server's happiness have improved over the baseline. Moreover, there has been a drop of 25.7% in the total execution time and the total network resources consumed are lower as compared to the baseline algorithm as well as random-allocation algorithm. © 2023 Elsevier Inc.
