TY - GEN
T1 - DistTM
T2 - 2016 IFIP Networking Conference (IFIP Networking) and Workshops, IFIP Networking 2016
AU - Hark, Rhaban
AU - Stingl, Dominik
AU - Richerzhagen, Nils
AU - Nahrstedt, Klara
AU - Steinmetz, Ralf
N1 - Publisher Copyright:
© 2016 IFIP.
PY - 2016/6/21
Y1 - 2016/6/21
N2 - Recently, several works propose monitoring approaches for the emerged paradigm of Software-defined Networking. These provide a couple of ideas to retrieve various information about the network state leveraging new concepts for monitoring data collection at flow-level. As existing approaches reduce their scope to networks with a single controller, even sophisticated approaches ignore a potentially great efficiency gap, due to redundant flow measurements by multiple controllers in adjacent networks. To show a possibility how to close this efficiency gap, we propose a solution for collaborative traffic matrix estimation, termed DISTTM. It exploits the property that flows traverse multiple networks and are monitored by several controllers. Through collaboration, the resulting monitoring tasks are coordinated and distributed among participating controllers to capture relevant information about all traversing flows, omitting redundant data collection. Conducted simulations reveal that DistTM operates efficiently: the monitoring traffic is significantly reduced, while the traffic matrix entry staleness is slightly affected. Furthermore, DistTM provides different schemes for a fair load balancing on controllers and switches while taking different influencing aspects into consideration.
AB - Recently, several works propose monitoring approaches for the emerged paradigm of Software-defined Networking. These provide a couple of ideas to retrieve various information about the network state leveraging new concepts for monitoring data collection at flow-level. As existing approaches reduce their scope to networks with a single controller, even sophisticated approaches ignore a potentially great efficiency gap, due to redundant flow measurements by multiple controllers in adjacent networks. To show a possibility how to close this efficiency gap, we propose a solution for collaborative traffic matrix estimation, termed DISTTM. It exploits the property that flows traverse multiple networks and are monitored by several controllers. Through collaboration, the resulting monitoring tasks are coordinated and distributed among participating controllers to capture relevant information about all traversing flows, omitting redundant data collection. Conducted simulations reveal that DistTM operates efficiently: the monitoring traffic is significantly reduced, while the traffic matrix entry staleness is slightly affected. Furthermore, DistTM provides different schemes for a fair load balancing on controllers and switches while taking different influencing aspects into consideration.
UR - http://www.scopus.com/inward/record.url?scp=84982283744&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84982283744&partnerID=8YFLogxK
U2 - 10.1109/IFIPNetworking.2016.7497233
DO - 10.1109/IFIPNetworking.2016.7497233
M3 - Conference contribution
AN - SCOPUS:84982283744
T3 - 2016 IFIP Networking Conference (IFIP Networking) and Workshops, IFIP Networking 2016
SP - 82
EP - 90
BT - 2016 IFIP Networking Conference (IFIP Networking) and Workshops, IFIP Networking 2016
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 17 May 2016 through 19 May 2016
ER -