Not Every Bit Counts: A Resource Allocation Problem for Data Gathering in Machine-to-Machine Communications
Many applications involving Machine-To-Machine (M2M) communications are characterized by the large amount of data to transport. To address the "Big data" problem introduced by these M2M applications, the authors argue in this paper that instead of focusing on serving individual machines with better quality, one should focus on solutions that can better serve the data itself. To substantiate this concept, they consider the scenario of data gathering in a wide area by machines that are connected to a central aggregator through direct wireless links. The aggregator has limited radio resources to allocate to machines for uplink transmission of collected data, and hence the problem arises as to how the resources can be effectively utilized for supporting such an M2M application.