MAUI: making smartphones last longer with code offload

By Eduardo Cuervo, Aruna Devi Balasubramanian, Dae-ki Cho, Alec Wolman, Stefan Saroiu, Ranveer Chandra, Paramvir Victor Bahl. ACM SIGMOBILE International Conference on Mobile Systems, Applications, and Services, 2010

2,684 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, Information Systems

View Paper: https://www.semanticscholar.org/paper/0f7dd6bcaf4c2a64b3a51b7351929dab23584ea8

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Citations in the corpus

DREAM: Dynamic Resource and Task Allocation for Energy Minimization in Mobile Cloud Systems (2015, methodology): “We compare existing mobile cloud offloading and mobile cloud backup algorithms [4], [6], [13], [17] with the DREAM algorithm.”
Computation Offloading Toward Edge Computing (2019, methodology): “[5] E. Cuervo et al., “MAUI: Making smartphones last longer with code offload,” in Proc.”
Collaborative Mobile Edge Computing in 5G Networks: New Paradigms, Scenarios, and Challenges (2016, background): “…the traditional way of ofﬂoading computation to the remote cloud can lead to round-trip times that are often long and generate heavy trafﬁc on the backhaul links; the former have been shown to be consistently on the order of hundreds of milliseconds and in some cases even reaching seconds [9].”
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”
Gearing resource-poor mobile devices with powerful clouds: architectures, challenges, and applications (2013, background): “ThinkAir [7] also tries to extend MAUI and CloneCloud by further exploiting the auto-scaling feature offered by the cloud.”
A survey of mobile cloud computing: architecture, applications, and approaches (2013, methodology): “Cuervo et al.[21] proposes MAUI, a system that enables fine-grained energyaware offloading of mobile codes to a cloud.”
Mobile Augmented Reality Survey: From Where We Are to Where We Go (2017, background): “Furthermore apart from the assistance to be provided by remote cloud servers [296], [297], [298], [299] it can also be provided by nearby cloudlets [300], [301], [302], [303], or even by nearby mobile devices [304], [305], [306].”
Energy Efficient Mobile Cloud Computing Powered by Wireless Energy Transfer (2015, background): “MCO has been an active research area in computer science [3] where research has focused on designing mobile-cloud systems and software architectures [6], [7], virtual machine migration design in the cloud [8] and code partitioning techniques in the mobiles [6] for reducing the energy consumption and”
Serendipity: enabling remote computing among intermittently connected mobile devices (2012, methodology): “We simply follow the of.ine method used by both MAUI [12] and CloneCloud [11], i.e., running the programs multiple times with different input data.”
Resource Management in Fog/Edge Computing (2018, background): “Conventional mobile cloud computing [38, 42, 92] allows low-power mobile devices such as smartphones to offload their computation-intensive tasks to more powerful platforms in cloud computing.”
CloneCloud: elastic execution between mobile device and cloud (2011, methodology): “Most related is the recent work on MAUI [Cuervo 2010].”
On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration (2017, neutral): “Component-level partitioning was considered in Cuckoo [35] and a relevant system was implemented in MAUI [36].”
A Review on Distributed Application Processing Frameworks in Smart Mobile Devices for Mobile Cloud Computing (2013, background): “Partitions of the application are offloaded to remote server nodes [14], [40].”
A Distributed Truthful Auction Mechanism for Task Allocation in Mobile Cloud Computing (2018, background): “To alleviate resource scarcity of mobile devices, one effective way is to offload their complex or resourcedemanded tasks to remote cloud [5], [6], [7], [8] through pay as you go.”
Computation Offloading and Resource Allocation in Mixed Fog/Cloud Computing Systems With Min-Max Fairness Guarantee (2018, methodology): “However, most of those previous works put their emphasis either on offloading decision making [2], [10], or resource allocation [6], without a joint consideration of both.”
A Survey of Computation Offloading for Mobile Systems (2012, methodology): “We assume the size of the program is negligible, or the server may download the program from another site through a high-speed network [17].”