Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Janakiram Dharanipragada"'
Autor:
Arun Raj, Janakiram Dharanipragada
Publikováno v:
Journal of Cloud Computing: Advances, Systems and Applications, Vol 6, Iss 1, Pp 1-14 (2017)
Abstract Cloud instances are vulnerable to cross-core, cross-VM attacks against the shared, inclusive last-level cache. Automated cache template attacks, in particular, are very powerful as the vulnerabilities do not need to be manually identified. S
Externí odkaz:
https://doaj.org/article/15ef007eb67e44e2b23d3cf54b9586f2
Publikováno v:
International Journal of Telemedicine and Applications, Vol 2010 (2010)
A typical telemedicine system involves a small set of hospitals providing remote healthcare services to a small section of the society using dedicated nodal centers. However, in developing nations like India where majority live in rural areas that la
Externí odkaz:
https://doaj.org/article/5e107050b0864aadaa6477d865869965
Linux containers have gained high popularity in recent times. This popularity is significantly due to various advantages of containers over Virtual Machines (VM). The containers are lightweight, occupy lesser storage, have fast boot-up time, easy to
Externí odkaz:
http://arxiv.org/abs/2009.08912
Blockchain is maintained as a global log between a network of nodes and uses cryptographic distributed protocols to synchronize the updates. As adopted by Bitcoin and Ethereum these update operations to the ledger are serialized, and executed in batc
Externí odkaz:
http://arxiv.org/abs/1910.08547
Publikováno v:
IEEE Transactions on Cloud Computing. 7:949-963
Offloading of tasks to the cloud is one of the approaches to improve the performance of distributed applications. When monetary constraints are present, selection of the tasks to be offloaded becomes important in order to ensure efficient use of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::02b965c13b84698d686fd9f4b84636e9
https://doi.org/10.1109/tcc.2017.2713776
https://doi.org/10.1109/tcc.2017.2713776
Publikováno v:
IEEE BigData
Heterogeneity could occur due to various reasons in a Hadoop cluster. This work primarily focuses on heterogeneity occurring due to varying read/write latency of disks. In case of similar disk latencies among the datanodes, balancing the blocks unifo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1f87a29be122dc64912de9eb30b712cc
https://doi.org/10.1109/bigdata.2017.8258253
https://doi.org/10.1109/bigdata.2017.8258253
Publikováno v:
Peer-to-Peer Networking and Applications. 9:193-208
In search engines, popular news events cause huge spikes in the queries related to the events. In this work, we consider the stability issues caused by these spikes in a peer-to-peer web search engine formed using voluntary resources shared by peers.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::90f287ac94523edce471f6f39183aeaf
https://doi.org/10.1007/s12083-014-0322-y
https://doi.org/10.1007/s12083-014-0322-y
Publikováno v:
CLOUD
With continuously growing data, clusters also need to grow periodically to accommodate the increased demand of data processing. This is usually done by addition of newer hardware, whose configuration might differ from the existing nodes. As a result,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bf723c4c1d519224887864f959982269
https://doi.org/10.1109/cloud.2017.63
https://doi.org/10.1109/cloud.2017.63
Publikováno v:
IEEE Transactions on Cloud Computing. 2:362-376
Today, batch processing frameworks like Hadoop MapReduce are difficult to scale to multiple clouds due to latencies involved in inter-cloud data transfer and synchronization overheads during shuffle-phase. This inhibits the MapReduce framework from g
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::79acc98eb890c90011dc97030e90edbe
https://doi.org/10.1109/tcc.2014.2316810
https://doi.org/10.1109/tcc.2014.2316810
Publikováno v:
Concurrency and Computation: Practice and Experience. 26:561-585
SUMMARY It is difficult to express the parallelism present in complex computations by using existing higher level abstractions such as MapReduce and Dryad. These computations include applications from wide variety of domains, like Artificial Intellig
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::19a7c7b07c8ba9adf137302fcfb5cd34
https://doi.org/10.1002/cpe.3018
https://doi.org/10.1002/cpe.3018