Edge-centric Computing: Vision and Challenges

By P. López, Alberto Montresor, Dick H. J. Epema, Anwitaman Datta, T. Higashino, Adriana Iamnitchi, M. Barcellos, Pascal Felber, Etienne Riviere. 2015

939 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Computer Science Applications

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

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Citations in the corpus

Practical Distributed Learning: Secure Machine Learning with Communication-Efficient Local Updates (2019, background): “There is growing literature on the practical applications of edge and fog computing (Garcia Lopez et al., 2015; Hong et al., 2013) in various scenarios such as smart home or sensor networks.”
Federated Multi-Task Learning (2017, background): “Computing SQL-like queries across distributed, low-powered nodes is a decades-long area of research that has been explored under the purview of query processing in sensor networks, computing at the edge, and fog computing [31, 11, 32, 7, 17, 14].”
Federated Learning: Challenges, Methods, and Future Directions (2019, background): “es across distributed, low-powered devices is a decades-long area of research that has been explored under the purview of query processing in sensor networks, computing at the edge, and fog computing [12, 29, 40, 49, 74]. Recent works have also considered training machine learning models centrally b”
Asynchronous Federated Optimization (2019, background): “Edge computing (Garcia Lopez et al., 2015; Hong et al., 2013) is increasingly applied in various scenarios such as smart home, wearable devices, and sensor networks.”
Survey on Multi-Access Edge Computing for Internet of Things Realization (2018, background): “MEC enables caching, data processing and analytics to be done closer the source of the data and reduces the burden on centralized cloud servers and core networks [22].”
Challenges and Opportunities in Edge Computing (2016, background): “‘beyond the clouds’ towards the edge of the network as shown in Figure 1, referred to as edge computing [3], [4], but also known as fog computing [5], [6] or cloudlet computing [7], [8].”
Computation Offloading Toward Edge Computing (2019, background): “By extensive deployment of massive edge nodes, such as cloudlets [19], base stations, and micro DCs, edge computing builds hierarchical computing layers: mobile devices, edge nodes, and the cloud, forming the edge-centric computing [20], [21].”
A New Deep Learning-Based Food Recognition System for Dietary Assessment on An Edge Computing Service Infrastructure (2018, background): “The last (but not the least) related research area is edge computing service infrastructure [22], [23], [24], [25], [26].”
All One Needs to Know about Fog Computing and Related Edge Computing Paradigms: A Complete Survey (2018, background): “The authors of [43], in a survey study, advocate for edge-centric computing, a more decentralized paradigm that utilizes peer to peer (P2P) networking at the edge of the network while maintaining access to the cloud.”
From Cloud to Fog Computing: A Review and a Conceptual Live VM Migration Framework (2017, background): “Smart city was described in [54] as a public space in the edge that optimizes energy consumption and improve the quality of life of citizens.”
Information-Centric Network-Based Vehicular Communications: Overview and Research Opportunities (2018, background): “Edge computing [31] is deployed to bring computing resources near data subscribers.”
SLSGD: Secure and Efficient Distributed On-device Machine Learning (2019, background): “ered attacks targeting federated learning [3,9,4], but do not propose defense techniques with provable convergence. There is growing literature on the practical applications of edge and fog computing [10,14] in various scenarios such as smart home or sensor networks. More and more big-data applicati”
On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration (2017, neutral): “Another aspect of application-awareness and content optimization is the impact of social networks as valuable sensors of the human activity [72].”
A Survey on Network Methodologies for Real-Time Analytics of Massive IoT Data and Open Research Issues (2017, background): “This may decrease the data process delay, which is important for the real-time IoT analytics [145].”
Data Security and Privacy-Preserving in Edge Computing Paradigm: Survey and Open Issues (2018, background): “Such dilemma urges us to move forward to the era of the Internet of Everything (IoE) [6], [7], which not only produces but also processes the massive data at the edge of the network.”
Applications of Blockchains in the Internet of Things: A Comprehensive Survey (2019, background): “In the evolution of IoT, the network edge is getting more functionality as compared to the cloud, as seen in fog and mist architectures [85].”
Network Slicing and Softwarization: A Survey on Principles, Enabling Technologies, and Solutions (2018, background): “intelligence and control as advocated by [8] and [93].”