Towards the Future Internet

Transcription

1 Towards the Future Internet Dr. Paola Grosso System and Network Engineering research group Informatics Institute

2 Vertices and edges Path finding algorithms Scale-free properties Models

3 Two features of the current Internet Best effort delivery End to end principle. H. Saltzer, D. P. Reed, and D. D. Clark. End-to-end arguments in system design. In: ACM Trans. Comput. Syst. 2, 4 (Nov. 1984)

4 Many demands. more data! more realtime! more users!

5 Optical transmission more possibilities Virtualization

6 The GLIF lightpaths around the world

7 The GLIF lightpaths around the world

8 Our research : a new model for the internet What we have now Best effort delivery End to end principle What we want How? Deterministic behavior Flexible and dynamic communication Hybrid networks More intelligence in the network Solve the computing problem (including storage and CPU) not just the communication problem Smart infrastructures Information models

9 Hybrid networks allow both packet and circuit switching Packet switching Circuit switching A good analogy is traffic on highways; With circuits, you can achieve high bandwidth and guaranteed response times for applications that need it

10 Path finding in multi-layer multi-domain networks Finding paths/circuits poses new challenges and needs research: Heterogeneous hardware (multi-layer) Technology agnostic algorithm Different control planes (multi-domain) Deal with different level of abstraction and information filtering Fully allocated is a new challenge for the algorithm! Strike a balance between efficiency and stability (dynamic reroute circuits) F. Dijkstra, J. van der Ham, P. Grosso and C. de Laat. A path finding implementation for multi-layer networks, In: Future Generation Computer Systems, Vol.25, Issue 2, Feb. 2009, pp A. Taal, P. Grosso, J. van der Ham and C de Laat Path finding strategies for multi-domain multi-layer network architectures In: Proceedings of the Cracow Grid workshop 2010

11 Path finding in multi-layer multi-domain networks Finding paths/circuits poses new challenges and needs research: Heterogeneous hardware (multi-layer) Technology agnostic algorithm Different control planes (multi-domain) Deal with different level of abstraction and information filtering Fully allocated is a new challenge for the algorithm! Strike a balance between efficiency and stability (dynamic reroute circuits) F. Dijkstra, J. van der Ham, P. Grosso and C. de Laat. A path finding implementation for multi-layer networks, In: Future Generation Computer Systems, Vol.25, Issue 2, Feb. 2009, pp A. Taal, P. Grosso, J. van der Ham and C de Laat Path finding strategies for multi-domain multi-layer network architectures In: Proceedings of the Cracow Grid workshop 2010

12 Information Modeling Define a common information model for infrastructures and services. Base it on Semantic Web. Infrastructure Projector pixelsx pixelsy Services NTTDisplayService Element * haselements 1 Device Identifier 1 * Group Description Display pixelsx pixelsy Host hostname OS providesservice providedby Cluster haselements: (Host) Node haselements:(not Node or Exchange) * 1 Service DisplayService pixelsx pixelsy StorageService totaldiskspace freediskspace StreamService capabilities maxstreams SAGEDisplayService NFSStorageService irodsstorageservice NTTStreamService SAGEStreamService Exchange haselements:(not Exchange) J. van der Ham, F. Dijkstra, P. Grosso, R. van der Pol, A. Toonk, C. de Laat A distributed topology information system for optical networks based on the semantic web, In: Elsevier Journal on Optical Switching and Networking, Volume 5, Issues 2-3, June 2008, Pages R.Koning, P.Grosso and C.de Laat Using ontologies for resource description in the CineGrid Exchange In: Future Generation Computer Systems (2010)

13 NOVI Networking Innovations Over Virtualized Infrastructures You can gain more by take all pieces of the puzzle into account. 1. describe all computing resources (networks, computing and storage facilities) 2. optimize the computing problem, instead of only its network aspect J. van der Ham, C. Papagianni, J. Steger, P.Matray, Y. Kryftis, P. Grosso and L. Lymberopoulos Challenges of an Information Model for Federating Virtualized Infrastructures In: 5th International DMTF Academic Alliance Workshop on Systems and Virtualization Management: Standards and the Cloud, Paris 24 Oct L. Lymberopoulos, P. Grosso, D. Kalogeras, C.Papagianni, C. de Laat, and V. Maglaris Ontology-based Policy Based Management for Federated Virtualised Platforms Third IFIP/IEEE International Workshop on Management of the Future Internet - May 2011

14 00:20:00 00:20:00 00:20:00 00:20:00 00:10:00 00:10:00 00:10:00 00:00:00 00:00:00 00:00:00 00:00: Job Number Job Number Job Job Number Number Demonstration of optimizing the computing problem ( Clouds ) If computing is infinite and movable, then workflows and applications can program the network. You can also introduce new metrics when creating and optimizing these infrastructures (e.g power consumption) Time (HH:MM:SS) 02:30:00 02:15:00 02:00:00 01:45:00 Time (HH:MM:SS) 01:30:00 01:15:00 01:00:00 00:45:00 00:30:00 00:15:00 00:10:00 Running timerunning time 02:30:00 Pending timepending time Time 02:15:00 02:00:00 01:45:00 01:30:00 01:15:00 01:00:00 00:45:00 00:30:00 00:15:00 Figure Figure 13: 13: Results Results of of a 30 a 30 job job workload Performance Performance on DAS3 - on 100 DAS3 Jobs- 100 Jobs 00:00:00 00:00: Job Number Job Number Grid-on-demand Job number Time (HH:MM:SS) Running Running time time 02:30:00 02:30:00Pending Pending time time 02:15:00 02:15:00 02:00:00 02:00:00 01:45:00 01:45:00 01:30:00 01:30:00 01:15:00 01:15:00 01:00:00 01:00:00 00:45:00 00:45:00 00:30:00 00:30:00 00:15:00 00:15:00 Performance Performance on Grid on Grid on Demand on Demand Jobs Jobs 00:00:00 00:00: Job Job Number Number User programmable networks Figure Figure 14: 14: Results Results of of a 100 a 100 job job workload R.Strijkers, W.Toorop, A.van Hoof, P.Grosso, A.Belloum, D.Vasuining, C. de Laat, R. Meijer AMOS: Using the Cloud for On-Demand Execution of e-science Applications In: Proc. escience2010 conf, Dec the same the same dataset dataset is used is used for for all all the the jobs jobs in in all all the the performed tests. The node node is running is running on the on the m1.large m1.large (see (see section section4.5) 4.5) instance. The dynamically head- started started compute compute nodes nodes are are c1.xlarge instances (see (see section 4.5). Total Total execution execution time time The The time time it takes it takes for for the the complete workloadto to finish as seen seen by WS-VLAM by WS-VLAM Job pending Job pending time time The The time time a job a job is pending is pending before beforeit itis isrun runas as seen by WS- VLAM VLAM Job running Job running time time The The time time a job a job is running is runninguntil until it it finishesas as seen by WS- VLAM VLAM The The graphs graphs in figure in figure 13 and 13 and figure figure confirm confirmthe the predicted results. The first 2 jobs 2 jobs for Grid for Grid on Demand on Demand in both in both the the en en job jobrun runshow showa a verydi di erent job running job running time time compared compared to the to the other other job job running running times timesin inthe the30 30and 100 job. Time Time (HH:MM:SS) Job number

15 The current Internet is a communication facility. Hybrid networks allow enormous improvements in service quality, but require new approaches to path finding algorithms and infrastructure descriptions. The Future Internet is an integrated information and application facility. We want to solve the combined allocation of communications paths, computing and storage.