Balancing performance, energy, and quality in pervasive computing

By Jason Flinn, Soyoung Park, Mahadev Satyanarayanan. Proceedings 22nd International Conference on Distributed Computing Systems, 2002

326 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/370f6cfee2015c6650749f8eb9e74c57095aa50e

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Citations in the corpus

Heterogeneity in Mobile Cloud Computing: Taxonomy and Open Challenges (2014, background): “Proposals similar to Spectra [4] and Scavenger [5] are aimed to augment mobile devices leveraging cyber foraging.”
Odessa: enabling interactive perception applications on mobile devices (2011, methodology): “The application partitioning is done either statically at compile time by Wishbone [23] and Coign [14], dynamically based on programmer specified partitions as in Spectra [11] and Tactics [3], or dynamically based on a run-time optimizer that uses integer-linear programming (as in MAUI [9] and Clone”
A Review on Distributed Application Processing Frameworks in Smart Mobile Devices for Mobile Cloud Computing (2013, background): “Examples of such applications include natural language translators [1]-[2], speech recognizers [1]-[3], optical character recognizers, image processors [4]-[5], online games, video processing [6] and wearable devices for patients such as wearable device with a head-up display in the form of eyeglass”
Communicating While Computing: Distributed mobile cloud computing over 5G heterogeneous networks (2014, background): “Examples of this class are: Spectra [11], Chroma [12], and Cuckoo [13].”
Cloud-Based Augmentation for Mobile Devices: Motivation, Taxonomies, and Open Challenges (2013, background): “Although surrogates in traditional augmentation approaches [8]–[10], [12] could increase computing capabilities of mobile”
Predictive Resource Management for Wearable Computing (2003, methodology): “In previous work, we described Spectra [14], a remote execution subsystem layered on the multi-fidelity framewor k described here.”
Computation Offloading Toward Edge Computing (2019, methodology): “1) Task Execution in MCC: Most of the earliest computation offloading systems use the process-level isolation technology to support task execution [107], including Chroma [88] and Spectra [123].”
MAUI: making smartphones last longer with code offload (2010, background): “As processors are getting faster, screens are getting sharper, and devices are equipped with more sensors, a smartphone s ability to consume energy far outpaces the battery s ability to provide it.”
Volley: Automated Data Placement for Geo-Distributed Cloud Services (2010, methodology): “Systems such as Spectra [13], Slingshot [40], MagnetOS [27], Pleaides [23] and Wishbone [33] explored data placement in a wireless context, either be-tween mobile clients and more powerful servers, or in ad hoc and sensor networks.”