Context-Aware Resource Allocation to Improve the Quality of Service of Heterogeneous Traffic

By supporting advanced multimedia applications and multitasking, recent Smartphone operation systems offer great flexibility to the users but make these devices even more difficult to serve. Now, operators of cellular networks face a situation where many applications and services generate highly heterogeneous and bursty traffic patterns. To cope with this challenge, we introduce Context-Aware Ressource Allocation (CARA). This new approach enables a scheduler to exploit new information from the users' environment, thereby, allocating its resources more efficiently. We demonstrate CARA's high performance and feasibility by studying it as network utility maximization problem. Comparing our results to traditional proportional fair scheduling clearly shows that knowing more about a user's context is worth the effort.