Abstract:
Machine-to-machine (M2M) communications are bringing new challenges to congestion control in the Internet of Things. One key issue is to facilitate the proper functioning...Show MoreMetadata
Abstract:
Machine-to-machine (M2M) communications are bringing new challenges to congestion control in the Internet of Things. One key issue is to facilitate the proper functioning of a wide range of M2M applications with drastically different throughput demands. Traditional Internet congestion control algorithms aim at sharing bandwidth among traffic flows equally, limiting their suitability for M2M communications. To maintain comparable levels of QoS of heterogeneous M2M applications when congestion is present, we propose a distributed congestion control algorithm which allocates transmission rates to M2M flows in proportion to their demands, through the use of a simple technique which we call “proportional additive increase”. To ease M2M application development, we make a further attempt to stabilize the throughputs of M2M flows controlled by the algorithm. We present simulation results to illustrate the effectiveness of the algorithm in achieving the desired rate allocation, as well as the challenge we face in stabilizing throughputs.
Date of Conference: 07-10 April 2013
Date Added to IEEE Xplore: 15 July 2013
ISBN Information: