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Mobile edge computing (MEC) is a promising solution to meet the latency requirement for delay-sensitive services in a 5G radio access network (RAN). Its key idea is to deploy computing and storage capacities at the edge of the RAN to quickly provision content and processing capacities as required by the users. Efficient content caching and delivery are key issues to ensure the success of this technique. This paper proposes a zone-based cooperative content caching and delivery scheme for a RAN supporting MEC (MEC-RAN), where the RAN is modelled as a zone and is further sub-divided into multiple sub-zones. Content items are cooperatively cached and delivered among multiple sub-zones. The caching problem is formulated as a mixed integer linear programming model. We also develop a heuristic cooperative content caching strategy to decide the content items to be cached in each MEC server. This novel strategy divides the storage space in each MEC server into two parts. The first part caches locally popular contents and the second part is used to cooperatively cache zone-wide popular items. We study the proposed scheme both through simulations and implementation on a testbed that consists of a subnetwork on our campus and commercial cloud service from Ali-Cloud. Both of these show that the proposed zone-based scheme performs better than other typical caching strategies in terms of average content delivery latency and balanced loading of the MEC servers.INDEX TERMS Content delivery network, mobile edge computing, optimal caching strategy, zone-based cooperative content caching.

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We propose and experimentally demonstrate modulation format-independent optical performance monitoring (OPM) based on a multi-task artificial neural network (MT-ANN). Optical power measurements at a series of center wavelengths adjusted using a widely tunable optical bandpass filter (OBPF) are used as the input features for a MT-ANN to simultaneously realize high-precision optical signal-to-noise ratio (OSNR) and launch power monitoring and baud rate identification (BRI). This technique is insensitive to chromatic dispersion (CD) and polarization mode dispersion (PMD). The experimental verification in a 9-channel WDM system shows that for 10 Gbaud QPSK and 32 Gbaud PDM-16QAM signals with OSNR in the range of 1–30 dB, the OSNR mean absolute error (MAE) and root mean square error (RMSE) are 0.28 dB and 0.48 dB, respectively. For launch power in the range of 0–8 dBm, the MAE and RMSE of the launch power monitoring are 0.034 dB and 0.066 dB, respectively, and the identification accuracy for both baud rates is 100%. Furthermore, this technique utilizes a single MT-ANN instead of three ANNs to realize the simultaneous monitoring of three OPM parameters, which greatly reduces the cost and complexity.

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