Signaling messages occur at a deep layer in the network, and therefore are not directly observable. This means that we must rely on other metrics to determine the efficacy of technologies for optimizing mobile traffic with respect to signaling activity. Those metrics should correspond directly to the network resources that are overburdened by the excessive background traffic generated by chatty mobile apps.

For today’s blog we will focus on two related measures: the number of connections and time connected. Let’s define what we mean by these terms. First, it’s important to note that when we say “number of connections” we mean device connections rather than application connections. Specifically, a connection occurs when the device radio moves from idle (lowest radio power state) to connected (higher power state), triggered by a network transaction when the radio is idle. Once the device is connected, multiple network transactions can occur as long at the radio remains in a connected state. Similarly, “time connected” means total time during which a device radio remains in the connected state, and is therefore occupying network capacity.

Each time a device connects to the network, it is using up signaling capacity as the network processes the request. Too many devices trying to connect at once can overwhelm the network’s ability to process these requests. Each device connection results in multiple signaling messages, so the number of connections and time connected serve as useful proxies for the volume of signaling activity – which as we said, cannot be observed directly. It should be noted that the ratio between signaling messages and connections varies depending upon the underlying network technology.

The key thing to remember about “number of connections” and “time connected” as metrics is that they correspond directly to the benefit derived by mobile carriers when they deploy Open Channel Traffic Optimization. These measures allow us to effectively track the ability of the software to ease the burden on critical network resources, thus helping mobile carriers to achieve greater network efficiency and lower infrastructure costs.  Specifically, measuring the difference in the number of connections and time connected with and without the software activated allows us to quantify its impact.

If you have read this far, you are probably wondering how effective Open Channel Traffic Optimization is at reducing the number of connections and time connected. To discover the answer, we invite you to download our new white paper, titled “Open Channel Traffic Optimization Carrier Field Trial Results”.

Incidentally, there is also a strong causal relationship between the amount of time that the device spends in a connected state and battery consumption.  We will discuss that relationship in a future blog post.