ORCID Profile
0000-0001-6597-252X
Current Organisation
Nanyang Technological University
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Publisher: Elsevier BV
Date: 03-2020
Publisher: Springer Singapore
Date: 12-2017
Publisher: IEEE
Date: 11-2014
Publisher: Springer India
Date: 05-09-2016
Publisher: Springer India
Date: 2015
Publisher: Inderscience Publishers
Date: 2017
Publisher: Elsevier BV
Date: 2015
Publisher: Elsevier BV
Date: 2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2020
Publisher: MDPI AG
Date: 04-07-2019
DOI: 10.3390/S19132954
Abstract: Fog computing aims to support applications requiring low latency and high scalability by using resources at the edge level. In general, fog computing comprises several autonomous mobile or static devices that share their idle resources to run different services. The providers of these devices also need to be compensated based on their device usage. In any fog-based resource-allocation problem, both cost and performance need to be considered for generating an efficient resource-allocation plan. Estimating the cost of using fog devices prior to the resource allocation helps to minimize the cost and maximize the performance of the system. In the fog computing domain, recent research works have proposed various resource-allocation algorithms without considering the compensation to resource providers and the cost estimation of the fog resources. Moreover, the existing cost models in similar paradigms such as in the cloud are not suitable for fog environments as the scaling of different autonomous resources with heterogeneity and variety of offerings is much more complicated. To fill this gap, this study first proposes a micro-level compensation cost model and then proposes a new resource-allocation method based on the cost model, which benefits both providers and users. Experimental results show that the proposed algorithm ensures better resource-allocation performance and lowers application processing costs when compared to the existing best-fit algorithm.
Publisher: MDPI AG
Date: 03-2023
DOI: 10.3390/ELECTRONICS12051183
Abstract: Data-intensive applications are generating massive amounts of data which is stored on cloud computing platforms where distributed file systems are utilized for storage at the back end. Most users of those applications deployed on cloud computing systems read data more often than they write. Hence, enhancing the performance of read operations is an important research issue. Prefetching and caching are used as important techniques in the context of distributed file systems to improve the performance of read operations. In this research, we introduced a novel highly relevant frequent patterns (HRFP)-based algorithm that prefetches content from the distributed file system environment and stores it in the client-side caches that are present in the same environment. We have also introduced a new replacement policy and an efficient migration technique for moving the patterns from the main memory caches to the caches present in the solid-state devices based on a new metric namely the relevancy of the patterns. According to the simulation results, the proposed approach outperformed other algorithms that have been suggested in the literature by a minimum of 15% and a maximum of 53%.
Publisher: IEEE
Date: 07-2014
DOI: 10.1109/PAAP.2014.49
Publisher: Wiley
Date: 07-01-2020
DOI: 10.1002/SPE.2787
Publisher: Springer Science and Business Media LLC
Date: 09-05-2022
Publisher: Springer Science and Business Media LLC
Date: 18-08-2020
Publisher: Tsinghua University Press
Date: 12-2015
Publisher: Elsevier BV
Date: 10-2022
Publisher: Elsevier BV
Date: 2015
Publisher: MDPI AG
Date: 14-05-2021
DOI: 10.3390/ELECTRONICS10101171
Abstract: Fog computing is an emerging computing paradigm that has come into consideration for the deployment of Internet of Things (IoT) applications amongst researchers and technology industries over the last few years. Fog is highly distributed and consists of a wide number of autonomous end devices, which contribute to the processing. However, the variety of devices offered across different users are not audited. Hence, the security of Fog devices is a major concern that should come into consideration. Therefore, to provide the necessary security for Fog devices, there is a need to understand what the security concerns are with regards to Fog. All aspects of Fog security, which have not been covered by other literature works, need to be identified and aggregated. On the other hand, privacy preservation for user’s data in Fog devices and application data processed in Fog devices is another concern. To provide the appropriate level of trust and privacy, there is a need to focus on authentication, threats and access control mechanisms as well as privacy protection techniques in Fog computing. In this paper, a survey along with a taxonomy is proposed, which presents an overview of existing security concerns in the context of the Fog computing paradigm. Moreover, the Blockchain-based solutions towards a secure Fog computing environment is presented and various research challenges and directions for future research are discussed.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Elsevier BV
Date: 10-2020
Publisher: Springer India
Date: 04-09-2016
Publisher: Inderscience Publishers
Date: 2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2021
Publisher: Springer Singapore
Date: 12-2017
No related grants have been discovered for Sudheer Kumar Battula.