Wi-Fi Cloud Solution

Manage a large number of Wi-Fi users efficiently with detailed behavioral analysis to achieve service excellence. Alibaba Cloud Wi-Fi solution helps public Wi-Fi service providers manage their users efficiently by storing and analyzing massive amounts of data using Alibaba Cloud and big data infrastructure.

Recommended Solution Architecture

Solution description

  1. 1. Wi-Fi access authentication:
  2. Users are required to undergo relevant authentication after entering Wi-Fi coverage areas. The Wi-Fi access point will upload the user's mobile phone information to the cloud Wi-Fi platform, which dispatches the authentication requests to the corresponding ECS authentication servers through the server load balancer, saving the user login information by integrating with ApsaraDB for Memcache. Once the authentication is complete, the user is able to access the Wi-Fi network.
  3. 2. Users' web behavior:
  4. To facilitate analysis and supervision of users' web behavior, the Wi-Fi access point is required to upload users' web behavior to the on-cloud Wi-Fi platform before being stored in the database. The web behavior data is forwarded to different data-collecting ECS servers through the server load balancer, with the data-collecting servers writing the data to the backend databases. ApsaraDB for RDS can be used to save the data. If the data size is too large for a single database to handle, Alibaba Cloud Distributed Relational Database Service is recommended.
  5. 3. Data-oriented marketing:
  6. Wi-Fi service providers analyze users' web behavior and launch marketing campaigns based on the analysis results, cashing in on Wi-Fi data. Alibaba Cloud offers the open data processing service (ODPS) for storing and processing the mass web history data of users. The results of data analysis will be customized and pushed by the ECS servers. Marketing content carrying images can be saved in the Object Storage Service (OSS) and distributed with CDN to Wi-Fi connected phones.

Solution Driven

Defects in Traditional IT Modes
Flexible and low cost
For entrepreneurs engaging in Wi-Fi businesses, searching for machine rooms, renting racks, purchasing servers and installing systems in the initial start-up phase of a business proves to be highly costly, in terms of both the time and capital involved. In addition, it is difficult to quickly expand the network, server and database resources as the business grows.
Server, network and database resources are ready for use out of the box, can be activated after just a few minutes, and be flexibly re-sized based on the development of the business. The IT costs, operation and maintenance workforce and system deployment time are reduced by 50%, 80% and 90% respectively compared with those in traditional IT models.
Difficulties in the storage and querying of mass data
High-quality network
Based on the requirements for industry supervision and business development, users' recent access records will be saved for querying in specific scenarios. In traditional IT models, the storage of mass data resulted in high costs, but offered poor performance in querying.
Alibaba Cloud data centers in every region provide multi-line BGP network access. Optimal network quality is guaranteed for Wi-Fi access points connecting to the cloud Wi-Fi platform from either a fixed or mobile network. Alibaba Cloud is gradually rolling out more overseas data centers to support the global business expansion of Wi-Fi service providers.
Weak analytical capability of big data
Mass data processing
Wi-Fi users' web access records and tracking mass data are accumulated by Wi-Fi service providers. However, most Wi-Fi service providers lack the capability to analyze this big data, making it difficult to conduct an in-depth analysis of Wi-Fi users, or cash in on Wi-Fi data.
Alibaba Cloud Distributed Relational Database Service is capable of effectively resolving the issues surrounding the storage and querying of mass quantities of users' web behavior data. Alibaba Cloud's open data processing service (ODPS), on the other hand, can effectively solve the difficulties of storing and analyzing mass amounts of history data.