TY - JOUR
T1 - On distributed scheduling with heterogeneously delayed network-state information
AU - Reddy, Akula Aneesh
AU - Banerjee, Siddhartha
AU - Gopalan, Aditya
AU - Shakkottai, Sanjay
AU - Ying, Lei
N1 - Funding Information:
Acknowledgements This work was partially supported by NSF grants CNS-0721380, CNS-0831756, CNS-1017549, the DARPA ITMANET program, and DTRA grant HDTRA1-09-1-0055. We thank the anonymous reviewers for their valuable comments and suggestions.
PY - 2012/10
Y1 - 2012/10
N2 - We study the problem of distributed scheduling in wireless networks, where each node makes individual scheduling decisions based on heterogeneously delayed network state information (NSI). This leads to inconsistency in the views of the network across nodes, which, coupled with interference, makes it challenging to schedule for high throughputs. We characterize the network throughput region for this setup, and develop optimal scheduling policies to achieve the same. Our scheduling policies have a threshold-based structure and, moreover, require the nodes to use only the "smallest critical subset" of the available delayed NSI to make decisions. In addition, using Markov chain mixing techniques, we quantify the impact of delayed NSI on the throughput region. This not only highlights the value of extra NSI for scheduling, but also characterizes the loss in throughput incurred by lower complexity scheduling policies which use homogeneously delayed NSI.
AB - We study the problem of distributed scheduling in wireless networks, where each node makes individual scheduling decisions based on heterogeneously delayed network state information (NSI). This leads to inconsistency in the views of the network across nodes, which, coupled with interference, makes it challenging to schedule for high throughputs. We characterize the network throughput region for this setup, and develop optimal scheduling policies to achieve the same. Our scheduling policies have a threshold-based structure and, moreover, require the nodes to use only the "smallest critical subset" of the available delayed NSI to make decisions. In addition, using Markov chain mixing techniques, we quantify the impact of delayed NSI on the throughput region. This not only highlights the value of extra NSI for scheduling, but also characterizes the loss in throughput incurred by lower complexity scheduling policies which use homogeneously delayed NSI.
KW - Delayed information
KW - Scheduling algorithms
KW - Wireless networks
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U2 - 10.1007/s11134-012-9312-z
DO - 10.1007/s11134-012-9312-z
M3 - Article
AN - SCOPUS:84868207781
SN - 0257-0130
VL - 72
SP - 193
EP - 218
JO - Queueing Systems
JF - Queueing Systems
IS - 3-4
ER -