Spectrum-Aware Mobile Computing by Seyed Eman Mahmoodi & Koduvayur Subbalakshmi & R. N. Uma

Author:Seyed Eman Mahmoodi & Koduvayur Subbalakshmi & R. N. Uma
Language: eng
Format: epub
ISBN: 9783030024116
Publisher: Springer International Publishing

5.3 Comparison with the State of Art

The performance of the CSCO is evaluated using real data from an HTC smartphone (mobile device) and NSFCloud (remote server) using two radios WiFi and LTE (the evaluation setup is detailed in Chap. 7). Data was gathered from indoor as well as outdoor wireless environments. Evaluations show that CSCO lowers energy consumption by 23–68% and reduces latency by 28–66% in comparison to the best-interface protocol, offline schemes, and mobile-only and cloud-only executions. We compare the optimal CSCO scheme with several variants of the CSCO scheme in both the indoor and outdoor environments as well as current state of the art in this field. The CSCO scheme will be compared with several other schemes including: (1) mobile-only execution where all the application components are processed in the mobile device (extreme case for mobile execution); (2) On-Off remote cloud offloading (On-Off RCO) where all components must be offloaded and at each time epoch, the offload is scheduled on the best available wireless interface (On-Off) (extreme case for cloud execution); (3) the dynamic offloading algorithm (DOA) proposed in [19], 14], a partial offline strategy which uses On-Off multi-RAT strategy; (4) HELVM proposed in [40], where a dynamic scheduler for partial offloading is studied; (5) the revised HEFT algorithm [48] for joint scheduling tasks (RHJS) on multiple cores that is proposed in [28], and (6) several variants of the CSCO work, described below: Cognitive scheduling and cloud offloading (CSCO): This is the optimal scheme for cognitive joint scheduling and offloading.

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