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http://hdl.handle.net/10603/426158
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DC Field | Value | Language |
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dc.coverage.spatial | ||
dc.date.accessioned | 2022-12-17T08:00:32Z | - |
dc.date.available | 2022-12-17T08:00:32Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/426158 | - |
dc.description.abstract | With the ever-growing technological expansion in the world, distributed comput ing is becoming popular and widely used in several fields. From scientific research to everyday life applications, everywhere we are using distributed computing and enjoying the benefits of this computing paradigm. Distributed computing helps im prove the performance of large-scale projects by combining the power of multiple computing devices. Distributed systems are the backbone of distributed computing. A distributed system is a collection of multiple independent computing components or nodes that work together to attain a common goal and appear as a single co herent system to the user. These independent nodes are connected through a net work, and they perform the tasks of the system with collaboration. In a distributed system, to complete an enormous task fast, the task is partitioned into a set of possible sub-tasks and allocated to multiple nodes. Then the nodes execute their assigned sub-tasks in a concurrent and consistent manner to complete the task in a faster way. The banking system, manufacturing industry, artificial intelligence, e-commerce, transport, health care, agriculture, defense systems have been using distributed computing for a long time. Various modern technologies like smart city, blockchain, cloud computing, edge computing, and so on are constructed based on the concept of decentralized systems. Recently, distributed machine learning and deep learning technologies are inclined to adopt the concept of distributed systems to fulfill their need for a reliable, high-performance, and large-scale computational platform. Though a distributed system is supposed to be scalable, cost-effective, fault-tolerant, highly available and reliable, and provides a high-performance com puting environment, several issues and challenges are also associated with such a system. System management, synchronization, consistency maintenance, and ef ficient resource utilization are some significant issues. newline | |
dc.format.extent | 183 | |
dc.language | English | |
dc.relation | ||
dc.rights | university | |
dc.title | Some observations on leader election algorithms for distributed systems | |
dc.title.alternative | ||
dc.creator.researcher | Biswas, Amit | |
dc.subject.keyword | Computer Science | |
dc.subject.keyword | Computer Science Interdisciplinary Applications | |
dc.subject.keyword | Engineering and Technology | |
dc.description.note | ||
dc.contributor.guide | Tripathi, Anil Kumar | |
dc.publisher.place | Varanasi | |
dc.publisher.university | Indian Institute of Technology IIT (BHU), Varanasi | |
dc.publisher.institution | Computer Science and Engineering | |
dc.date.registered | 2017 | |
dc.date.completed | 2021 | |
dc.date.awarded | 2021 | |
dc.format.dimensions | ||
dc.format.accompanyingmaterial | DVD | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Computer Science and Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title page.pdf | Attached File | 380.46 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 270.9 kB | Adobe PDF | View/Open | |
03_content page.pdf | 213.31 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 79.25 kB | Adobe PDF | View/Open | |
05_chapter 01.pdf | 377.68 kB | Adobe PDF | View/Open | |
06_chapter 02.pdf | 380.46 kB | Adobe PDF | View/Open | |
07_chapter 03.pdf | 1.04 MB | Adobe PDF | View/Open | |
08_chapter 04.pdf | 1.05 MB | Adobe PDF | View/Open | |
09_chapter 05.pdf | 747.06 kB | Adobe PDF | View/Open | |
10_chapter 06.pdf | 775.95 kB | Adobe PDF | View/Open | |
11_chapter 07.pdf | 136.06 kB | Adobe PDF | View/Open | |
12_annexures.pdf | 120.83 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 495.64 kB | Adobe PDF | View/Open |
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