Resource allocation in Mobile Edge Computing (MEC)

Point of contact


Address radio resource allocation under uncertainty with risk modeling and guaranteed Quality of Service. This will be achieved by mathematical models that describe the user demand and stochastic optimization models that deals with uncertainty.

Explore synergies of stochastic games and Multi-Access Edge Computing (MEC) in case of incomplete information including the aspects of learning, cooperation, uncertainty and social connections.

Analyse realistic scenarios where games and MEC have positive synergies, i.e., heterogeneous access, small cells, D2D communications, autonomus vehicles, vehicular networks, IoT, energy consumption, energy harvesting and mobile social networks.


Edge Computing, energy, IOT

Researchers involved or interested

A few references

Niezi Mharsi, Makhlouf Hadji: Edge computing optimization for efficient RRH-BBU assignment in cloud radio access networks. Comput. Networks 164 (2019)

Vikas Vikram Singh, Abdel Lisser: A second-order cone programming formulation for two player zero-sum games with chance constraints. Eur. J. Oper. Res. 275(3): 839-845 (2019)

P. Brown and S.E. Elayoubi, Semi-distributed Contention-based Resource Allocation for Ultra Reliable Low Latency Communications, IEEE Infocom 2020, Toronto, July 2020.

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