Optimized Cloud Based Scheduling
феб 2018. · Studies in Computational Intelligence 759. књига · Springer
E-knjiga
99
Stranica
reportOcene i recenzije nisu verifikovane Saznajte više
O ovoj e-knjizi
This book presents an improved design for service provisioning and allocation models that are validated through running genome sequence assembly tasks in a hybrid cloud environment. It proposes approaches for addressing scheduling and performance issues in big data analytics and showcases new algorithms for hybrid cloud scheduling. Scientific sectors such as bioinformatics, astronomy, high-energy physics, and Earth science are generating a tremendous flow of data, commonly known as big data. In the context of growing demand for big data analytics, cloud computing offers an ideal platform for processing big data tasks due to its flexible scalability and adaptability. However, there are numerous problems associated with the current service provisioning and allocation models, such as inefficient scheduling algorithms, overloaded memory overheads, excessive node delays and improper error handling of tasks, all of which need to be addressed to enhance the performance of big data analytics.
Ocenite ovu e-knjigu
Javite nam svoje mišljenje.
Informacije o čitanju
Pametni telefoni i tableti
Instalirajte aplikaciju Google Play knjige za Android i iPad/iPhone. Automatski se sinhronizuje sa nalogom i omogućava vam da čitate onlajn i oflajn gde god da se nalazite.
Laptopovi i računari
Možete da slušate audio-knjige kupljene na Google Play-u pomoću veb-pregledača na računaru.
E-čitači i drugi uređaji
Da biste čitali na uređajima koje koriste e-mastilo, kao što su Kobo e-čitači, treba da preuzmete fajl i prenesete ga na uređaj. Pratite detaljna uputstva iz centra za pomoć da biste preneli fajlove u podržane e-čitače.
