Serendipity: enabling remote computing among intermittently connected mobile devices

By Cong Shi, Vasileios Lakafosis, Mostafa H. Ammar, Ellen Witte Zegura. ACM Interational Symposium on Mobile Ad Hoc Networking and Computing, 2012

375 citations recorded by the source corpus.

Subfields: Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/379a480336a30b3e9fc65a036f421e79e92066f8

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In Computer Networks and Communications

Citations in the corpus

Survey on fog computing: architecture, key technologies, applications and open issues (2017, methodology): “Furthermore, by using the idea of ”Data Sherpa”, the data from a static sensor (edge) can be transferred to a mobile smart phone (edge) with Bluetooth technology when they are proximity, and then smart phone transmit the data to fog or cloud (Varshney and Simmhan, 2017; Shi et al., 2012).”
Mobile Edge Computing: A Survey on Architecture and Computation Offloading (2017, methodology): “The other option enabling cloud computing at the edge is to perform computing directly at the UEs through ad-hoc cloud allowing several UEs in proximity to combine their computation power and, thus, process high demanding applications locally [5]–[14].”
Resource Management in Fog/Edge Computing (2018, background): “anner, (ii) sequential jobs are executed on the same device so that intermediate data does not have to be sent across the network, and (iii) there is distributed control, and jobs are loosely coupled [49]. The jobs are represented as a Directed Acyclic Graph (DAG), and the smallest component of a jo”
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].”
D2D Fogging: An Energy-Efficient and Incentive-Aware Task Offloading Framework via Network-assisted D2D Collaboration (2016, methodology): “In the D2D Fogging framework, similar to many existing work [2], [7], [14], [24], [25] we also consider the batch and stream based mobile tasks following MapReduce and Google DataFlow programming model.”