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We consider a wireless distributed computing system, in which multiple mobile users, connected wirelessly through an access point, collaborate to perform a computation task. In particular, users communicate with each other via the access point to exchange their locally computed intermediate computation results, which is known as data shuffling. We propose a scalable framework for this system, in which...
We propose a framework for edge-facilitated wireless distributed computing, in which several mobile users connected to an access point collaborate for a distributed computing task. We characterize the minimum communication load, both in uplink (from users to the access point) and downlink (from access point to the users), required for distributed computing. In particular, we develop a communication...
We propose a scalable coded distributed computing framework for wireless distributed computing over a cluster of mobile users, in which the data shuffling across users are performed through an access point at the edge of the network. The proposed framework achieves a constant shuffling load that is independent of the number of participating users. The key idea is to utilize a particular repetitive...
Smart Mobile device are becoming popular platforms for information accessing, especially when coupled with recommendation system technologies. They are also treated as key tools for mobile users both for leisure and business applications. Recommendation techniques can increase the usability of mobile systems by providing more personalized and interested content. In this paper, a novel personalized...
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