are some differences in how friendly applications behave towards the cellular network, how much sig- nalling they generate, how much payload they transfer or how much battery they consume. LTE Small Cell Optimization OS1: Strict bacground traffic control 100,000 10,000 OS2: Less strict bacground traffic control 10,000 Figure 16.18 Background traffic activity with different operating systems Probably the two main factors which impact the performance of IM applications are the frequency of keep-alive messages during standby periods and the compression ratio of attach- ments during active usage of the application. First, from a signalling point of view, keep-alive intervals between 15 and 30 minutes generate only moderate load to the network, but intervals around 5 minutes or lower can considered too aggressive and potentially harmful for cell capacity and standby battery life of the UE. Second, from a payload point of view, there is a significant impact from the strategy used regarding compression of pictures and videos. Some of the most popular applications tend to highly compress the content before transmitting, which makes them very efficient from a network perspective while keeping reasonably good quality when watching the pictures in smartphone's display. However, some applications do very little or no compression in Average number of background data transactions per hour os baseline App A App B App C activated activated activated Figure 16.19 Number of LTE packet calls (eRABs) per hour Smartphone Optimization Table 16.1 Example messaging performance Power Average size of Type of Total delay consumption original message message Application (seconds) IM APP1 ~6200 bytes IM APP2 ~750 bytes IM APP3 ~1150 bytes Picture IM APP1 16.34 ~800 kbytes Picture IM APP2 12.98 ~88 kbytes Picture IM APP3 11.70 ~215 kbytes the UE before uploading the picture to its servers, which creates high uplink traffic and increases the time it takes to upload the picture, the amount of data consumed and the load of the cell. Compression 