QoS monitoring in real-time streaming overlays based on lock-free data structures

Peer-to-peer streaming is a well-known technology for the large-scale distribution of real-time audio/video contents. Delay requirements are very strict in interactive real-time scenarios (such as synchronous distance learning), where playback lag should be of the order of seconds. Playback continuity is another key aspect in these cases: in presence of peer churning and network congestion, a peer-to-peer overlay should quickly rearrange connections among receiving nodes to avoid freezing phenomena that may compromise audio/video understanding. For this reason, we designed a QoS monitoring algorithm that quickly detects broken or congested links: each receiving node is able to independently decide whether it should switch to a secondary sending node, called “fallback node”. The architecture takes advantage of a multithreaded design based on lock-free data structures, which improve the performance by avoiding synchronization among threads. We will show the good responsiveness of the proposed approach on machines with different computational capabilities: measured times prove both departures of nodes and QoS degradations are promptly detected and clients can quickly restore a stream reception. According to PSNR and SSIM, two well-known full-reference video quality metrics, QoE remains acceptable on receiving nodes of our resilient overlay also in presence of swap procedures.

A Comparative Study of a Client Based Vendor Neutral Cloud QoS Monitoring Tool and Cloud Providers’ Platform Integrated QoS Monitoring Tools

Cloud service providers have a QoS monitoring capability integrated in their cloud platforms. This is to aid in monitoring the performance of the platform as well as for Service Level Agreement confirmation to the clients. Unfortunately this arrangement serves the interest of the cloud provider more than the cloud client since the service providers gauge their services using their own tools. This paper performs a comparative study on the capabilities of the client based vendor neutral QoS tool, developed from a vendor neutral QoS monitoring model against the cloud provider integrated QoS monitoring tools. The comparison was done on four global SaaS cloud service providers, namely SalesForce, Google, Hubspot and Shopify. From the comparative study, it emerged that the client based vendor neutral tool has more capabilities than the cloud provider integrated tools since it has the capability to monitor three key QoS metrics, namely service response time, service availability and service stability as opposed to the cloud providers’ tools which only have one quantitative capability. Further the vendor neutral model can be used across any cloud platform that is accessible via the web browser. This provides a capability for cross platform performance comparison for the various cloud providers. This can aid in decision making with regards to which cloud service provider to procure based on the desired performance.