Energy and Latency Control for Edge Computing in Dense V2X Networks

This study focuses on edge computing in dense millimeter wave vehicle-to-everything (V2X) networks. A control problem is formulated to minimize the energy consumption under delay constraint resulting from vehicle mobility. A tractable algorithm is proposed to solve this problem by optimizing the offloaded computing tasks and transmit power of vehicles and road side units. The proposed dynamic solution can well coordinate the interference without requiring global channel state information, and makes a tradeoff between energy consumption and task computing latency.

[1]  Theodore S. Rappaport,et al.  Millimeter Wave Mobile Communications for 5G Cellular: It Will Work! , 2013, IEEE Access.

[2]  François Baccelli,et al.  Stochastic geometry and wireless networks , 2009 .

[3]  Robert W. Heath,et al.  Beam design for beam switching based millimeter wave vehicle-to-infrastructure communications , 2016, 2016 IEEE International Conference on Communications (ICC).

[4]  K. B. Letaief,et al.  A Survey on Mobile Edge Computing: The Communication Perspective , 2017, IEEE Communications Surveys & Tutorials.

[5]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[6]  François Baccelli,et al.  Stochastic Geometry and Wireless Networks, Volume 1: Theory , 2009, Found. Trends Netw..

[7]  Yusheng Ji,et al.  AVE: Autonomous Vehicular Edge Computing Framework with ACO-Based Scheduling , 2017, IEEE Transactions on Vehicular Technology.

[8]  Francisco Facchinei,et al.  Asynchronous parallel nonconvex large-scale optimization , 2017, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).