Self-Management in SAC and FIRE

Transcription

1 Self-Management in SAC and FIRE Future Networks Concertation Meeting Brussels, 30 September 2008 Dr. Fabrizio Sestini New Paradigms and Experimental Facilities European Commission - DG INFSO fabrizio.sestini(at)ec.europa.eu "The views expressed in this presentation are those of the author and do not necessarily reflect the views of the European Commission"

2 Self-Management From manually managed networks Manual configuration of devices To centrally managed networks Management system monitors network and interacts with routers To self-managed networks Policies are defined for a network The network itself implements the corresponding rules and verifies if the network complies to its policy setting 2

3 What is Self-Management (SM)? SM is the process by which computer systems or networks shall manage their own operation without human intervention Some initiatives launched to realize selfmanagement: Autonomic Computing (IBM, 2001) SAC (Situated and Autonomic Communications) by the EC FET (Future and Emerging Technologies) in 2004 Spin-off: the ACF (Autonomic Communication Forum), 2004 Follow-up: FIRE (Future Internet Research and Experimentation), 2006 Future Networks Projects under ICT challenge 1 (2006-) Self-Managing Future Internet: an ETSI industry specification group? 3

4 Pervasive and Trustworthy Network and Services Infrastructures Networked Media and 3D Internet Internet of Things and Enterprise Environments FIRE Experimental Facility & Experimentally-driven Research Trustworthy ICT Internet of Services, Software and Virtualisation The Network of the Future 4

5 Autonomic Computing The Autonomic Computing Initiative defines the following four functional areas towards realizing self-management : Self-Configuration: Automatic configuration of components Self-Healing: Automatic discovery, and correction of faults Self-Optimization: Automatic monitoring and control of resources to ensure the optimal functioning with respect to the defined requirements Self-Protection: Proactive identification and protection from arbitrary attacks 5

6 Situated and Autonomic Communications Situated Communication Context-awareness (i.e. local reaction wrt contextual changes), ranging from sensor networks to virtual networks of humans Considering strategic needs (socio-economic i.e. not only technological, e.g. privacy) Autonomic Communication Network elements autonomously interrelated and controlled, dynamically adapting to changing environments, and learning the desired behaviour self-configuration & organisation, self-healing, selfprotection, and self-optimization fully distributed technology independent Objective: self-organizing communication network (concept and technology) that can be situated in multiple and dynamic contexts, that is task- and knowledge-driven, and fully scalable 6

7 Closed control loop Autonomic Communication and Self-management System Knowledge analyze decide Rules / Policies (from objectives and constraints) Self-monitoring detect(*) execute Self-configuration and organization Autonomic Network element Self-management / autonomic management At any levels: from network topology to security E.g. for FCAPS network management services 7

8 SAC Projects COOPCOM COOPCOM CATNETS CATNETS HAGGLE HAGGLE Opportunistic networking (cross-layer) Cooperative and opportunistic communications Economic models for SLAs Autonomic service evolution BIONETS BIONETS New Architectures Common research issues: Security, resilience, self-* (organisation, evolution,healing, ) interaction of new paradigms with society Situated Services ANA ANA Beyond IP New network theory Internet models and measures Autonomic communication elements CASCADAS CASCADAS NET-REFOUND NET-REFOUND EVERGROW EVERGROW 8

9 SM in SAC and FIRE projects Application Service Transport Network Access Physical ANA Coop Com HAGGLE Net- Refound BIO NETS CAT NETS CASC ADAS Nano data centers ECODE Smart -Net Self -Net OPNEX RES UME NET 9

10 Self-Management in ANA ANA is developing a framework for Future Internet Architectures Different networks will implement different management structures ANA does not impose any fixed management infrastructure, but provides some initial building blocks for self-* mechanisms In ANA, multiple networks coexist (in ANA called compartments), each potentially running its own scheme ANA framework provides the ground/soil for such new network architectures generic API, to start implementing self-* capabilities 10 10

11 ANA network compartments Each network has to provide its own addressing and naming structure Appropriate self-configuration mechanisms Basic functions are provided by the ANA framework Self-configuration, self-optimization Open for new mechanisms Challenge: Federation of different networks Requires gateway, address translation, 11 routing, Application layer Generic Clean framework Slate Link layer 11

12 Self-Management in BIONETS The BIONETS Project looks at the functioning of biological systems for introducing innovative design & management approaches for pervasive computing environments BIONETS is centered around the concept of self-evolving services, i.e., services that are able to adapt to the environment they are in and to respond to unpredictable external changes in the absence of a centralized control BIONETS aims at introducing autonomicity through the embedding of evolutionary features in the services Self-management is one of the self-* properties achieved by self-evolving services 12

13 Self-Management in BIONETS Self-management is addressed at two levels: Micro Embedding of evolutionary features in single components (i.e., single service components & network protocols). Example: genetic-based techniques for the selfoptimization of data dissemination protocols [Alouf et al., Proc of IEEE MASS07] Macro Architecting evolutionary processes at the (eco)system level (i.e., composition of distributed ( services/protocols services, interactions of different Example: evolutionary stable equilibria in wireless networks employing different congestion control mechanisms [Altman et al., Proc. of WiOpt 2008] 13

14 SM in CASCADAS - Hybrid approach for supervision of a service ecosystem: two complementary and cooperating mechanisms Higher level composition top-down design of some patterns of components Lower level (self-) aggregation patterns/groups emerge as the results of a self-organizing behavior of basic components distributed supervision services to monitor and manage groups of components highly distributed supervision mechanism to supervise huge amount of components The two mechanisms can co-exist and co-operate: the supervision service will react to events whenever the local supervision logic is not able to cope with some contexts Example of short-medium term application: easing customers experience for Home Networking Example of long term application: handling complexities of Service Ecosystems 14

15 Self-Management in HAGGLE Haggle develops a framework for novel protocols and applications for mobile communication Introduces a new communication paradigm Builds on top of existing wireless technologies Pairwise connection between mobile devices No explicit network management required No explicit self-management implemented, but (Self-)management can be implemented with managers Dataobject manager, protocol manager, interface manager, Manager architecture allows for flexible protocols and management mechanisms 15 15

16 COOPCOM: Decentralized Transmission Strategies CoopCom is investigating new communication paradigms for portable devices by exploiting synergies between cooperative and opportunistic transmission modalities; a common scenario is one where several systems coexist in the same area and communicate using the same portion of the spectrum. this problem is seen as a non-cooperative game where each user is regarded as a player whose payoff function is the individual link rate Dynamics of such a game are studied and properties of the resulting Nash equilibria are found The region of achievable operating points is characterised both for low and high interference systems and dependence on the various system parameters is explicitly shown. 16

17 CATNETS decentralised economic self-organisation mechanisms (based on free-market principles) for resource allocation in application layer networks where client requests need to be matched with services and the latter with resources. See website for simulation results 17

18 NET-REFOUND Self-management Net-Refound is developing the theory, methods and algorithms suitable for the modelling, analysis and design of future telecommunication networks. Techniques and methods employed in the context of NET-REFOUND lead to self-managed network architectures through Game theoretic understanding of collective interactions of network elements Enforcement of autonomous operation of networked systems without the need of a central coordinator 18

19 Self-management in NET-REFOUND architectures Self-management in resource allocation through interaction with other entities in the vicinity Inherent selfishness in self-configuration taken into account by game theoretic models Optimal self-management strategy Progressive learning of network state and adjustment of interaction policy Dynamic monitoring of legitimate behavior of network entities When misbehavior detected, network self-configures itself by isolating / punishing misbehaving nodes No need for central monitoring agent Physics-inspired self-management of massively dense sensory networks Route and network connectivity configuration in accordance to physics laws (e.g. percolation theory) 19

20 experimentally-driven, multi-disciplinary research validation OPNEX ECODE N4C SmartNet Perimeter Nanodata centers ResumeNet SelfNet long-term research requirements large scale experiment. testing new paradigms at large scale VITAL++ WISEBED Testbed Testbed Federica PII OneLab2 Testbed Testbed Testbed Testbed support actions FIREWORKS PARADISO 7

21 SM in SAC and FIRE projects Application Service Transport Network Access Physical ANA Coop Com HAGGLE Net- Refound BIO NETS CAT NETS CASC ADAS Nano data centers ECODE Smart -Net Self -Net OPNEX RES UME NET 21

22 ECODE - Driving Concept Concept: augment existing routing/control paradigm of lower-level data collection and decision making process, with a cognitive component that enables system and network to Learn about its own behavior and environment over time Analyze problems, tunes its operation and increases its functionality and performance Current router design Router with cognitive engine Learned rules Cognitive and decisions Engine KIB Control Routing info Routing Engine RIB Control Routing info Routing info data Routing Engine decisions RIB Packet Forwarding Engine FIB Packet Data Packet Forwarding Engine FIB Data 22

23 SELF-NET SELF-MANAGEMENT OF COGNITIVE FUTURE INTERNET ELEMENTS Motivation Current Internet model Clear separation of concerns between protocol layers Intelligence moved to the edges The existent protocol pool targeting user and control plane operations with less emphasis on management tasks Self-NET aims to : Introduce, design and validate an innovative paradigm for cognitive self-managed elements of the Future Internet 23 1

24 Self-management: Core Concept for SELF-NET Self-NET Concepts Design and specification of the Future Internet by proposing the operation of self-managed Future Internet elements around a novel feedbackcontrol cycle Introduction of a novel hierarchical cognitive cycle approach for the self-management of interworking network compartments and individual network elements Research and development of knowledge-based decision making and goal-oriented task triggering within self-managed FI elements and self-organised network islands. 24

25 SELF-NET: SELF-X Methods Self-Awareness y Self-Configuration y Proactively compensating/overcoming foreseen events (deduction) Self-Optimization y Responding to unplanned events Self-Protection y Accommodating new operational aspects Self-Healing y Continuous knowledge-building to assess situation and operational status Constantly pursuing optimality (maintenance, performance etc.) Self-Organization y y Higher order Collaborative management apparatus 25

26 SELF-NET: Approach to self-management Self-NET Technical Objectives Modularization of functionalities throughout the legacy IP protocol stack and dynamic recomposition of IP operations M D E M M D E D E A peer-to-peer style distribution of responsibilities among self-governed elements of the Future Internet, therefore overcoming current client-server models 26

27 SMART-Net Self-management approaches SMART-Net project doesn t study specifically self-management techniques The objective is to apply such techniques and engineer them to enable the introduction of new generation of Wireless Mesh Networks Self-management - Self-organization - Self-configuration -Self-optimization -Self-healing SMART-Net features - Wireless Mesh Networking (MAC / NET layers) - Link management with smart antennas (PHY / MAC layers) - Mobility management with smart antennas (PHY / MAC layers) - Multi-RAT operations including routing (NET layer) - Cooperative techniques (PHY / MAC layers) - Security enhancements (MAC layer) 27

28 OPNEX relation to self-management Network architectures to be devised under OPNEX are inherently self-managed since: They do not depend on traffic parameters or network and topology statistics They observe only local network state and traffic They use local easy-to-perform self-adaptation rules that rely on observation of local network state variables and traffic They compensate for wireless channel, traffic and topology variations They operate without need of a central supervising agent managing the operation of various parts 28

29 OPNEX: Self-management across layers Self-management spans several communication layers PHY: self-adaptation of transmission parameters and topology control Access: dynamic adjustment of medium access parameters based on local network state Network: end-to-end multi-hop routing through local decentralized adaptations Transport: automatic optimized flow control at each node 29

30 OPNEX: Impact of Self-management Self-managed operation allows for fast tracking of network states and low-overhead (yet accurate) local adaptation rules that compensate for multi-hop wireless network variations Judicious dynamic transmission and topology adaptation results in sophisticated self-management of scarce energy resources, thus leading to energyefficient network operation 30

31 RESUMENET: Resilient Networking Strategy - D 2 R 2 +DR Real-time Control Loop Defend Detect Remediate Recover System Enhancement Diagnose Refine ResumeNet validates strategy and provides guidelines for practitioners 31

32 RESUMENET: Resilience Metrics Application based service space Two-dimensional state space Network resilience Acceptable Impaired Unacceptable Network state transitions under challenges S 0 S 1 S 2 S i Normal operation S 1 with resilience without resilience aggregate network state S 2 Partially degraded Network operational space S 3 S 3 Severely degraded Reliability, availability Performance measures Jitter, Delay Topology properties Service resilience Reliability, availability Response time Response quality Customer satisfaction 32 32