000204921 001__ 204921
000204921 005__ 20181203023735.0
000204921 0247_ $$2doi$$a10.1109/TNET.2016.2587579
000204921 02470 $$2ISI$$a000395867000027
000204921 037__ $$aARTICLE
000204921 245__ $$aImproved Utility-based Congestion Control for Low-Delay Communication
000204921 269__ $$a2017
000204921 260__ $$aPiscataway$$bIeee-Inst Electrical Electronics Engineers Inc$$c2017
000204921 300__ $$a14
000204921 336__ $$aJournal Articles
000204921 520__ $$aDue to the presence of buffers in the inner network nodes, each congestion event leads to buffer queueing and thus to an increasing end-to-end delay. In the case of delay sensitive applications, a large delay might not be acceptable and a solution to properly manage congestion events while maintaining a low end-to-end delay is required. Delay-based congestion algorithms are a viable solution as they target to limit the experienced end-to-end delay. Unfortunately, they do not perform well when sharing the bandwidth with congestion control algorithms not regulated by delay constraints (e.g., loss-based algorithms). Our target is to fill this gap, proposing a novel congestion control algorithm for delay-constrained communication over best effort packet switched networks. The proposed algorithm is able to maintain a bounded queueing delay when competing with other delay-based flows, and avoid starvation when competing with loss-based flows. We adopt the well-known price-based distributed mechanism as congestion control, but: 1) we introduce a novel non-linear mapping between the experienced delay and the price function and 2) we combine both delay and loss information into a single price term based on packet interarrival measurements. We then provide a stability analysis for our novel algorithm and we show its performance in the simulation results carried out in the NS3 framework. Simulation results demonstrate that the proposed algorithm is able to: achieve good intra-protocol fairness properties, control efficiently the end-to-end delay, and finally, protect the flow from starvation when other flows cause the queuing delay to grow excessively.
000204921 6531_ $$aDelay-sensitive communication
000204921 6531_ $$acongestion control
000204921 6531_ $$anetwork utility maximization
000204921 700__ $$0248090$$aD'Aronco, Stefano$$g238825
000204921 700__ $$0246986$$aToni, Laura$$g229538
000204921 700__ $$aMena, Sergio
000204921 700__ $$aZhu, Xiaoqing
000204921 700__ $$0241061$$aFrossard, Pascal$$g101475
000204921 773__ $$j25$$k1$$q349-362$$tIEEE/ACM Transactions on Networking
000204921 8564_ $$uhttps://arxiv.org/abs/1506.02799$$zURL
000204921 909C0 $$0252393$$pLTS4$$xU10851
000204921 909CO $$ooai:infoscience.tind.io:204921$$pSTI$$pGLOBAL_SET$$particle
000204921 917Z8 $$x229538
000204921 917Z8 $$x238825
000204921 917Z8 $$x238825
000204921 917Z8 $$x238825
000204921 917Z8 $$x148230
000204921 937__ $$aEPFL-ARTICLE-204921
000204921 973__ $$aEPFL$$rREVIEWED$$sPUBLISHED
000204921 980__ $$aARTICLE