Cellular telephony networks have been adapted to carry Internet data traffic, but the ongoing rapid increase in data demand by the growing population of smartphones and similar mobile devices has placed heavy burdens on the ability of cellular networks to handle the data traffic. In response to this challenge, cellular operators have implemented technologies for off-loading data traffic from cellular networks onto other networks. Solutions include private offloading systems set up by cellular operators, public non-cellular wireless Internet connections by arrangement with various commercial entities, open networks established by municipalities and public areas such as shopping malls, and similar setups to accommodate mobile users.
In addition, various commercial enterprises now implement aspects of cellular offloading standards established as part of the evolving system architecture standards for mobile networks, such as Access Network Discovery and Selection Function (“ANDSF”), whose purpose is to assist user devices to discover non-cellular network access points which can be used for data communications (such as Wi-Fi), and to provide the user devices with policies (rules) regarding connections to such network access points. Commercial enterprises also maintain extensive access point maps and provide facilities and software so that user devices can automatically select access points and establish connections to them.
Connection policies for prospective access points typically involve a number of metrics, such as those related to Quality of Service (QoS), security level, backhaul quality, and bandwidth requirements. In order to be eligible for selection, a prospective access point must meet such requirements. For example: the available bitrate of a prospective access point must be sufficient to support the bitrate required by the offloaded data connection, and the prospective access point must have a current loading less than a predetermined threshold. Typically, a target function of the metrics is defined, and the choice of access point may be based on the target function. If a number of prospective access points pass the filtering of the target function, one of them may be selected at random for the access point. Alternatively, one may be selected according to a function of the various metrics used.
In one mode of operation (a “real-time” mode), the user device receives connection selection commands as needed from a server according to an established policy. In another mode of operation (an “autonomous distributed” mode), a predetermined policy is downloaded to the user device, which makes connection selection decisions according to the stored policy, such as discussed above. Maps or lists of available access points may accompany the policy.
Currently, the focus and orientation for data offloading and policy control therefor is targeted to consumer mobile devices (e.g., smartphones), and consequently is based on the environments and characteristics of the users themselves—for example: where is a user likely to go with his or her smartphone (e.g., a coffee shop, a stadium, an office building, etc.)? How long is the user's mobile device likely to remain connected to a particular access point (e.g., 10-15 minutes, 1-2 hours, etc.)? Although such considerations may not necessarily be explicitly formalized in terms of metrics for data offloading policies and decision-making, they imply an underlying context which influences the choice and handling of access point policy and selection factors. That is, data offloading policies and access point connection decisions are tailored according to the view that the mobile device is a piece of handheld equipment carried on the person of a user. Commercially, for the bulk of the mobile device market, this is a reasonable approach.
However, an important and developing area for mobile devices now centers on the vehicle market. Currently, a vehicle may be equipped with on-board integrated cellular, non-cellular wireless Internet connectivity, GPS, and infotainment capabilities. From a data perspective such a vehicle is considered as a “vehicle telematics entity” or a “connected vehicle”. Benefits of connected vehicles include: vehicle and contents tracking; fleet management; route planning and navigation, such as turn-by-turn navigation; emergency warning and safety communications; pay-as-you-drive vehicle rental and leasing arrangements; and driver monitoring and insurance compliance.
In terms of data offloading, it is important to realize that a connected vehicle itself is the data client, rather than the user (such as a driver or passenger). Unfortunately, the underlying context according to which data offloading policy and decision-making are based is that of a human user's behavior and environment. This is not necessarily applicable for vehicle data clients. It is thus highly desirable to have new methods and systems for establishing data offloading policy and making data offloading selections and decisions in cases where a vehicle is the client. This goal is met by embodiments of the present invention.