Low Latency Geo-distributed Data Analytics
By Qifan Pu, Ganesh Ananthanarayanan, Peter Bodík, Srikanth Kandula, Aditya Akella, Paramvir Victor Bahl, Ion Stoica. Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication, 2015
388 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems
View Paper: https://www.semanticscholar.org/paper/9d79370259c7287871ff2452850e2aa256015018
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Xu Chen
- Amir Salman Avestimehr
- Amirhossein Reisizadeh
- Ramtin Pedarsani
- Zhi Zhou
- Liekang Zeng
- Saurav Prakash
- En Li
In Information Systems
- Xu Chen
- Zhi Zhou
- Peter Bodík
- Amirhossein Reisizadeh
- Ramtin Pedarsani
- Ganesh Ananthanarayanan
- Matthai Philipose
- Saurav Prakash
Citations in the corpus
- Edge Intelligence: Paving the Last Mile of Artificial Intelligence With Edge Computing (2019, background): “However, when moving a tremendous amount of data across the wide area network (WAN), both monetary cost and transmission delay can be prohibitively high, and the privacy leakage can also be a major concern [5].”
- Computation Offloading Toward Edge Computing (2019, neutral): “[43] Q.”
- Coded Computation Over Heterogeneous Clusters (2019, background): “” For example, replicating the straggling task on another available node is a common approach to deal with stragglers [4], while partial data replication is also used to reduce the communication load in distributed computing [5].”
- Real-Time Video Analytics: The Killer App for Edge Computing (2017, background): “This is analogical to big data analytics whose original focus was on executing on a single cluster but now is beginning to execute across geo-distributed clusters [2].”