BwShare: Efficient Bandwidth Guarantee in Cloud with Transparent Share Adaptation Abstract   Bandwidth guarantee (BwG) is a highly desired feature in cloud data centers for enabling tenants (i.e., users) to achieve predictable performances. However, such a function currently is not commonly available in clouds since it potentially lowers the utilization efficiency of the network fabric (i.e., denoted network efficiency). The reasons lie in two aspects. First, tenants often present a timevarying andor spatiallyvarying bandwidth demands. Second, the current cloud network architecture makes it hard to enable tenants to reuse unused bandwidth guarantees efficiently. To tackle these challenges, we propose BwShare, a novel bandwidth guarantee scheme in cloud data centers that can effectively improve the network efficiency at both the guaranteed level and the besteffort level in a synergized manner, while current approaches only adopt one of them. Such a design goal is achieved through two components: an adaptive bandwidth guarantee adaptation module (i.e., BGAdaptor) and a transparent work conservation module (i.e., WCEnabler). BGAdaptor improves the network efficiency at the guaranteed level by adjusting bandwidth guarantees among VMs of the same tenant based on traffic monitoring. WCEnabler works at the besteffort level by enabling VMs to reuse idled bandwidth efficiently and freely without disrupting bandwidth guarantees. The two modules can also facilitate each otherxe2x80x99s performance. Extensive experiments show that BwShare can effectively improve the network efficiency while providing the function of bandwidth guarantee in cloud data centers.

Affinity AwareScheduling of Live Migration of Virtual Machines Under Maintenance Scenarios During maintenance and disaster recovery scenarios, Virtual Machine (VM) intersite migrations usually take place over limited bandwidthxe2x80x93typically Wide Area Network (WAN)xe2x80x93which is highly affected by the amount of interVM traffic that becomes separated during the migration process. This causes both a degradation of the Quality of Service (QoS) of intercommunicating VMs and an increase in the total migration time due to congestion of the migration link. We consider the problem of scheduling VM migration in those scenarios. In the first stage, we resort to graph partitioning theory in order to partition the VMs into groups with high intragroup communication. In the second stage, we devise an affinitybased scheduling algorithm for controlling the order of the migration groups by considering their intergroup traffic. Comprehensive reallife experimental results and simulations show that our approach in some cases is able to decrease the volume of separated traffic by a factor larger than 60%.