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Source: Mr Ibrahim Alghamdi (i.alghamdi.1 '@' research.gla.ac.uk), Dr Christos Anagnostopoulos (christos.anagnostopoulos '@' glasgow.ac.uk), Prof Dimitrios Pezaros (dimitrios.pezaros '@' glasgow.ac.uk); Essence Research Lab, School of Computing Science, University of Glasgow; http://www.dcs.gla.ac.uk/essence/
Data Set Information: This dataset contains the turnaround execution times (in seconds) for offloaded image recognition tasks when executed in different edge servers. The edge servers are MacBook Pro Processor: 1.4 GHz Quad-Core Intel Core i5 RAM: 8 GB 2133 MHz LPDDR3, MacBook Pro Processor: 2.5 GHz Dual-Core Intel Core i5 RAM: 8 GB 1600 MHz DDR3, Ubuntu VM Using VirtualBox RAM: 2 GB and Raspberry Pi 4B Processor: a quad-core 64-bit ARM Cortex-A72 CPU RAM: 4Gb. The client (mobile edge node) was simulated as a process in one of these devices. The client sends an image to be recognized by one of the servers above, i.e. server. The turnaround execution time is the time duration once the connection is established (when the edge node starts sending the image) until it receives the recognition result from the edge server. The execution time is recorded for each edge server. Attribute Information: [1] Time: day, date, hours, minutes, second, year.
Relevant Papers: [1] I Alghamdi, C Anagnostopoulos, D Pezaros, Time-Optimized Task Offloading Decision Making in Mobile Edge Computing, 2019 Wireless Days (WD), 1-8.
Citation Request: Please cite one of the papers mentioned in the “Relevant Papers†section. |
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