scalability and resilience of multi-tenant distributed clouds in the big services era
TRANSCRIPT
Scalability and Resilience of Multi-Tenant Distributed Clouds in the Big Services Era
Pradeeban Kathiravelu1,2, Tihana Galina Grbac3, Peter Van Roy2, Luís Veiga1
1INESC-ID Lisboa / Instituto Superior Técnico, Portugal. 2Université catholique de Louvain, Belgium.3University of Rijeka, Croatia.
Introduction Data-centric big services with complex workloads.
Geographically distributed big data to be processed.
Resource availabilities at remote locations; for example,
Distributed clouds with resources in multiple regions.
Volunteer computing leverages idle client resources.
Edge computing with execution close to the end users.
Critical flows - End-to-end delivery guarantees.
Challenges Differentiated Quality of Service (QoS) in cloud networks!
Discriminate flows with redundancy in data and execution paths?
Motivation Network level performance based on service level inputs.
Scalability and Resilience for big services in distributed clouds.
SDN for Distributed Clouds Cross-layer optimization of multi-tenant cloud networks
Leveraging Software-Defined Networking (SDN) and middleboxes.
Our Approach
1. SMART (SDN Middlebox Architecture for Reliable Transfers)
SMART: Network Resilience with Differentiated SLAs.
Policies and tenant preferences:
● Service Level / Application Layer → Network (Figure 1).
Timely delivery of priority flows:
Dynamically diverting them to a less congested path.
Cloning subflows of higher priority flows.
An adaptive approach in cloning and diverting of the flows.
An approach motivated by FlowTags Middlebox
Tag the network flows with service level inputs.
Solution Architecture
A cross-layer architecture and communication.
Ensuring differentiated QoS.
A context-aware approach in load balancing the network.
servers supporting multihoming, connected topologies, …
Extend beyond data centers:
network nodes → virtual executions.
Blurring the borders between the networks and the
applications.
Contributions
* These results have been partly discussed in our recent publications: ICWS (2016), CoopIS (2015, 2016), NCA (2016), IM (2017), IC2E (2016), and SDS (2015, 2016, 2017).
Questions and Comments? [email protected]
2. Mayan (Componentizing Data-Centric Big Services In the Internet)
An Inter-cloud framework to componentize big services.
Execute them as a network-aware distributed service
composition.
Modelling, Scalability, and Orchestration.
Use the best-fit execution path among available alternatives.
Web services and microservices as the building blocks of
the big services.
Solution Architecture A scalable resilient framework for big service execution.
Services as building blocks of the composition of big services
(Figure 2).
Message-Oriented Middleware (MOM) for inter-domain
communications.
Contributions
Synergy of network and service levels in decision making.
A federated controller deployment for inter-cloud networks.
Componentizing big services as service compositions.
Scalability and resilience for multi-tenant distributed clouds.
Conclusion
Increased QoS and Speedup with network-aware scalability.
Performance growth = f(problem size, workflow as services).
Federated deployment of SDN controller clusters.