QoS-Aware Orchestration of Network Intensive Software Utilities within Software Defined Data Centres

Abstract

Although the cloud computing domain is progressing rapidly, the deployment of various network intensive software utilities in the cloud is still a challenging task. The Quality of Service (QoS) for various gaming, simulations, video-conferencing, video-streaming or even file uploading tasks may be significantly affected by the quality and geolocation of the selected underlying computing resources, which are available only when the specific functionality is required. This study presents a new architecture for geographic orchestration of network intensive software components which is designed for high QoS. Key elements of this architecture are a Global Cluster Manager (GCM) operating within Software Defined Data Centres (SDDCs), a runtime QoS Monitoring System, and a QoS Modeller and Decision Maker for automated orchestration of software utilities. The implemented system automatically selects the best geographically available computing resource within the SDDC according to the developed QoS model of the software component. This architecture is event-driven as the services are deployed and destroyed in real-time for every usage event. The utility of the implemented orchestration technology is verified qualitatively, and in relation to the potential gains of selected QoS metrics by using two network intensive software utilities implemented as containers: an HTTP(S) file upload service and a Jitsi Meet videoconferencing service. The study shows potential for QoS improvements in comparison to existing orchestration systems.

Trust management in a blockchain based fog computing platform with trustless smart oracles

“…A recent study investigated various QoS aspects of video streaming applications when the application server is implemented by using Docker containers and orchestrated by using Kubernetes [21]. This approach makes it possible to establish video streaming applications on the fly.…”

“…Edge nodes are responsible for rapid data acquisition and data normalisation; Fog nodes are responsible for data processing, compression and transformation and Cloud storage repositories store the data upon request. The orchestration capability is realised by using Kubernetes and is thoroughly described elsewhere [21]. Before using any of these infrastructures in the other layers of the architecture, they are first verified on the blockchain if they satisfy trust including QoS requirements.…”

Formal Quality of Service assurances, ranking and verification of cloud deployment options with a probabilistic model checking method

“…Existing studies have investigated the selection of optimal IaaS providers with respect to the expected QoS, for example, studies related to load balancing [22,23,24,25], resource management and allocation [26,27,28,29], resource provisioning [30,31,32] or service deployment and management systems [33,15].…”

“…This is achieved through a clear separation of the application design, deployment and operational (runtime) phases. Advanced software engineering workbenches support the composition of applications from existing microservices, discovery and negotiations of computing resources with Infrastructure-as-a-Service (IaaS) cloud providers, Service Level Agreements, deployment and runtime orchestration in multi-cloud environments [11,12,13,14,15]. The software engineering process is cloud agnostic in the sense that a cloud application can be designed and developed before an IaaS offer is selected [16].…”

QVIA-SDN: Towards QoS-Aware Virtual Infrastructure Allocation on SDN-based Clouds

“…Using SDN to implement virtualized cloud data centers is still challenging as it introduces new dimensions to management such as flow forwarding delay, dynamic virtual topology creation, bandwidth sharing, CPU isolation on switches, and forwarding table sharing [32] [33] [27]. SDN is innovative but can increase the latency as the path that a flow traverses may grow.…”