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In status update scenarios, the freshness of information is measured in termsof age-of-information (AoI), which essentially reflects the timeliness forreal-time applications to transmit status update messages to a remotecontroller. For some applications, computational expensive and time consumingdata processing is inevitable for status information of messages to bedisplayed. Mobile edge servers are equipped with adequate computation resourcesand they are placed close to users. Thus, mobile edge computing (MEC) can be apromising technology to reduce AoI for computation-intensive messages. In thispaper, we study the AoI for computation-intensive messages with MEC, andconsider three computing schemes: local computing, remote computing at the MECserver, and partial computing, i.e., some part of computing tasks are performedlocally, and the rest is executed at the MEC server. Zero-wait policy isadopted in all three schemes. Specifically, in local computing, a new messageis generated immediately after the previous one is revealed by computing. Whilein remote computing and partial computing, a new message is generated once theprevious one is received by the remote MEC server. With infinite queue size andexponentially distributed transmission time, closed-form average AoI forexponentially distributed computing time is derived for the three computingschemes. For deterministic computing time, the average AoI is analyzednumerically. Simulation results show that by carefully partitioning thecomputing tasks, the average AoI in partial computing is the smallest comparedto local computing and remote computing. The results also indicate numericallythe conditions on which remote computing attains smaller average AoI comparedwith local computing.

Analysis on Computation-Intensive Status Update in Mobile Edge Computing