Networks, Systems and Services, Distributed Computing: Part VII

Talk 1

Speaker

Andrea Segalini (SIGNET / i3s)

Title

Towards Massive Consolidation in Data Centers with SEaMLESS

Abstract

In Data Centers (DCs), an abundance of virtual machines (VMs) remain idle due to network services awaiting for incoming connections, or due to established-and-idling sessions. These VMs lead to wastage of RAM – the scarcest resource in DCs – as they lock their allocated memory. In this talk we present SEaMLESS, a non-invasive user-space solution designed to transform fully-fledged idle VMs into lightweight and resourceless virtual network functions (VNFs) thus releasing their allocated memory and enabling a better utilization of DC resources. SEaMLESS provides fast VM restoration upon user activity detection, thereby introducing limited impact on the Quality of Experience (QoE). Our results show that SEaMLESS can consolidate hundreds of VMs as VNFs onto one single machine.

Content:

Not available

 

Talk 2

Speaker

Naoufal Mahfoudi (DIANA)

Title

Orientation Estimation Using Commodity Wi-FiC

Abstract

With MIMO, Wi-Fi led the way to the adoption of antenna array signal processing techniques for fine-grained localization using commodity hardware. These techniques, previously exclusive to specific domains of applications, will spur interest to reach beyond localization, and now allow to consider estimating the device’s orientation in space, that once required other sources of information. Wi-Fi’s popularity and the availability of metrics related to channel propagation (CSI), makes it a candidate readily available for experimentation. Accordingly, we propose the ORION system to estimate the orientation (heading and yaw) of a MIMO Wi-Fi equipped object, relying on a joint estimation of the angle of arrival and the angle of departure. Although the CSI’s phase data is plagued by several phase inconsistencies, we demonstrate that an appropriate phase compensation strategy significantly improves estimation accuracy. Our technique allows estimating orientations within millimeter-level precision.

Content:

Not available

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