SSICLOPS: Developing the cloud infrastructure for tomorrow

« The Scalable and Secure Infrastructures for Cloud Operations (SSICLOPS, pronounced “cyclops”) project focuses on techniques for the management of federated private cloud infrastructures, in particular cloud networking techniques within software-defined data centres and across wide-area networks. […]

SSICLOPS will empower enterprises to create and operate high-performance private cloud infrastructure that allows flexible scaling through federation with other private clouds without compromising on their service level and security requirements. SSICLOPS federation will support the efficient integration of clouds, no matter if they are geographically collocated or spread out, belong to the same or different administrative entities or jurisdictions: in all cases, SSICLOPS will deliver maximum performance for inter-cloud communication, enforce legal and security constraints, and minimize the overall resource consumption. In such a federation, individual enterprises will be able to dynamically scale in/out their private cloud services: because they dynamically offer own spare resources (when available) and take in resources from others when needed. This allows maximizing own infrastructure utilization while minimizing excess capacity needs for each federation member.

SSICLOPS-powered private clouds will offer fine-grained monitoring and tuning capabilities along with workload planning and optimization tools to maximize the performance across a broad spectrum of workloads and across a wide operational scale, as we will demonstrate using four highly diverse use cases. The SSICLOPS solution will be based upon state-of-the-art open source products used broadly in private cloud deployments today to provide enterprises with full control over their own deployment. To realize this vision, SSICLOPS targets the following concrete objectives:

  1. To build a framework for on-demand and pro-active scale-in/out in private clouds. This framework encompasses a control pane, a data plane, and tools for supporting application development.
  2. To provide models characterizing the static and dynamic properties of workloads and topologies of federated clouds.
  3. To provide means for specifying constraints for workloads and their data.
  4. To develop an efficient and secure intra-cloud dataplane.
  5. To develop a hardened dataplane tailored to inter-cloud transport and transport towards clients
  6. To provide different application programming interfaces (API).
  7. To offer tools for measuring the performance of cloud systems.
  8. To validate the SSICLOPS results in four different scenarios. The scenarios are chosen to reflect a broad spectrum of industry and scientific use cases: Using an in-memory database, Performing high-performance computing tasks for high-energy physics workloads, Instantiating efficient and secure cloud bursting, and Network Function Virtualization.
  9. To contribute the project results as open source to the standard platforms.
  10. To contribute the technical designs to the appropriate standardization bodies and industry forums.
  11. To carry the project results into the (academic) community through publications in renowned venues for the respective tasks and to introduce the concepts, tools and open source systems broadly into academic education of future engineers and scientists.
  12. To demonstrate the commercial value. » *

More information on this project and our project partners can be found on https://ssiclops.eu/.

Consortium

The SSICLOPS Consortium consists of several European partners with expertise in various areas of communication and cloud computing. In SSICLOPS, we bundle this expertise to develop the cloud infrastructure of tomorrow.

  • Aalto University
  • Deutsche Telekom
  • F-Secure
  • Hasso Plattner Institute
  • Helsinki Institute of Physics
  • Martel Consulting
  • NEC
  • NetApp
  • Orange Polska
  • RWTH Aachen University
  • University of Cambridge
  • University Politehnica of Bucharest
  • Technical University of Munich
  • University of Pisa


Publications

Application-Agnostic Offloading of Datagram Processing. Proceedings of the 2018 30th International Teletraffic Congress (ITC 30), Sep 3 - Sep 7, 2018, Vienna, Austria. September 2018.
Giving Customers Control over Their Data: Integrating a Policy Language into the Cloud. Proceedings of the 2018 IEEE International Conference on Cloud Engineering (IC2E 2018), Apr 17 - Apr 20, 2018, Orlando, Florida, USA. April 2018.
Veiled in Clouds? Assessing the Prevalence of Cloud Computing in the Email Landscape. Proceedings of the 2017 Network Traffic Measurement and Analysis Conference (TMA 2017), Jun 21 - Jun 23, 2017, Dublin, Ireland. June 2017.
Practical Data Compliance for Cloud Storage. Proceedings of the 2017 IEEE International Conference on Cloud Engineering (IC2E 2017), Apr 4 - Apr 7, 2017, Vancouver, BC. April 2017.
CPPL: Compact Privacy Policy Language. Proceedings of the 15th Workshop on Privacy in the Electronic Society (WPES), Vienna, Austria. October 2016.
Moving Privacy-Sensitive Services from Public Clouds to Decentralized Private Clouds. Proceedings of the Second International Workshop on Legal and Technical Issues in Cloud Computing and Cloud-Supported Internet of Things (CLaw 2016), Apr 4 - Apr 8, 2016, Berlin, Germany. April 2016.
Santa: Faster Packet Delivery for Commonly Wished Replies [Poster Abstract]. Proceedings of the 43rd ACM SIGCOMM Conference (SIGCOMM ‘15), London, United Kingdom. August 2015.