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In this paper, we consider non-clairvoyant task offloading for random tasks in mobile edge computing within the framework of combinatorial optimisation. For offline non-clairvoyant task offloading, we propose a non-clairvoyant task offloading algorithm, which is able to determine a task offloading strategy without knowing the amount of computation and communication of any task. For online non-clairvoyant task offloading, we propose a randomised online task offloading algorithm, which is able to make an offloading decision for an arrival task without knowing anything about future tasks and other tasks. For both algorithms, we analyse the probability of certain performance guarantee. We also demonstrate numerical data. To the best of the author's knowledge, this is the first paper which considers both offline and online non-clairvoyant task offloading in mobile edge computing, together with analytical results on performance guarantee with high probability. [ABSTRACT FROM AUTHOR]

As mobile devices have become the preferred tool for communication, work, and entertainment, traffic at the edge of the network is growing more rapidly than ever. To improve user experience, commodity servers are deployed in the edge to form a decentralised network of mini datacenters each serving a localised region. A challenge is how to place these servers geographically to maximise the offloading benefit and be close to the users they respectively serve. We introduce a formulation for this problem to serve applications that involve pairwise communication between mobile devices at different geolocations. We explore several heuristic solutions and compare them in an evaluation using both real-world and synthetic datasets. [ABSTRACT FROM AUTHOR]