Age-of-information (AoI) is a novel metric that measures the freshness of information in status update scenarios. It is essential for real-time applications to transmit status update packets to the destination node as timely as possible. However, for some applications, status information embedded in the packets is not revealed until complicated data processing, which is computational expensive and time consuming. As the mobile edge server has sufficient computational resource and is placed close to users, mobile edge computing (MEC) is expected to reduce age for computation-intensive messages. In this paper, we study the AoI for computation-intensive data in MEC, and consider two computing schemes: local computing by user itself and remote computing at MEC server. The two computing models are unified into a two-node tandem queuing model. Zero-wait policy is adopted, i.e., a new message is generated once the previous one leaves the first node. We consider exponentially distributed service time and infinite queue size, and hence, the second node can be seen as an First-Come-First-Served (FCFS) M/M/1 system. Closed-form average AoIs are derived for the two computing schemes. The region where remote computing outperforms local computing is characterized. Simulation results show that there exists an optimal transmission rate so that remote computing is better than local computing for a largest range.
The AoI performance was also analyzed for mobile edge computing (MEC) networks with computation-intensive tasks, where both the local and remote computing strategies were considered REF .
Age-of- Information for Computation- Intensive Messages in Mobile Edge Computing
2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)
2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)
Computer Science