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Architectures for Autonomic Communications


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Title: Architectures for Autonomic Communications

Architectures for Autonomic Communications
  • Visa Holopainen,

What is autonomic computing (communications)
  • Continuous automatic improvement of the system
    functioning based on measured feedback and
    pre-defined goals
  • Any types of improvement goals can be set
  • Hierarchical systems possible (Managers of
  • The manager(s) can be software or hardware
  • External manager component enhances modularity
  • The conversion/mapping layer makes the system
    more platform-independent
  • The basic concept is simple, algorithms (code)
    make the difference in any particular autonomic

Why autonomic computing
  • A study made in 2002 estimates that half of all
    network outages result from configuration errors
    made by administrators 1
  • Most autonomic architectures try to tackle the
    increasing complexity of network configurations
    by adding some (complicated) distributed software
    to the network
  • Issue Will there be problems in code base
    management (security, updates, etc.)
  • The objective is to get to a point in which only
    high-level configurations are injected into the
    network and the network figures out independently
    what should be done at physical level
  • Issue more powerful configuration commands -gt
    more potential for network-wide problems
  • Solution architecture should contain reversible
    operations and should allow easy access for
    administrators if needed

AUTONOMIA An Autonomic Computing Environment, X.
Dong, S. Hariri, L. Xue, H. Chen, M. Chang, S.
Pavuluri, S. Rao, 2003
  • Provides control and management services to
    support the development and deployment of smart
    (intelligent) applications
  • Application developer can specify the
    applications autonomic requirements (e.g.
    self-optimizing and self-healing) through
    Application Management Editor (AME)
  • The next step is to utilize the Autonomic
    Middleware Service (AMS) to build the appropriate
    application execution environment that can
    dynamically control the allocated resources to
    maintain the application requirements during
    application execution
  • Self-healing
  • For each fault type (system, component or agent),
    there is a software agent (fault handler) that is
    responsible for executing the procedures
  • During the monitoring phase, the appropriate
    fault handler focuses on detecting faults once
    they occur
  • Recovery procedures are run if fault is detected
  • Self-optimization
  • Similar software agents than in self-healing

The implementation
  • The mobile agent system (MAS) for Autonomia is
    designed to provide mobile agents a uniform
    execution environment independent of the
    underlying hardware architecture and operating
  • Java/Jini platform used
  • Jini (http//
  • A network architecture for the construction of
    distributed systems where scale, rate of change
    and complexity of interactions within and between
    networks are extremely important
  • The interaction can use any type of networking
    technology such as RMI, CORBA, or SOAP

The architecture
Self-aware management of IP networks with QoS
guarantees, F. Krief, 2004
  • Self-aware management
  • Allows network to react and adapt to changes of
  • Operators can focus on defining high-level
    policies (operational objectives)
  • Faster cheaper
  • Policy-based management
  • Business policy -gt Network level policy -gt
    Low-level policy
  • Agent may transport business policies so that the
    negotiation and the decision can be carried out
    locally (no need for policy exchange protocol)
  • An architecture was described in the paper that
    implements the principles of self-aware mgmt and
    policy-based mgmt
  • Each logical component improves itself and alerts
    the component upper in the hierarchy if SLA
    cannot be satisfied without modifications to
    upper level objectives
  • The solution is said to allow the
    self-configuration, self-provisioning and
    self-monitoring of service as well as proactive
    SLA management
  • No testing, just a framework

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An automated policy-based management framework
for differentiated communication systems, N.
Samaan, A. Karmouch, 2005
  • Main theme policy based management
  • Policies can be created dynamically (in contrast
    to traditional model in which policies must be
    created statically)
  • A framework was proposed to decouple
  • The mapping of high-level policies to network
    level objectives
  • The functionality of adapting network components
  • The component that takes care of decoupling is
    Automated Policy Adaptor (APA)
  • Network operators can inject business objectives
    to APA using a Graphical User Interface
  • Users/user applications can also specify
    requirements to APA in form of policies
  • User preferences ans business goals for QoS are
    translated into network-level objectives
  • APA can modify policies at runtime based on
    feedback from the network
  • Novelty of the proposition lies in that given
    sets of objectives, constraints and policies are
    assembled at runtime -gt flexibility to network
  • Both fixed and wireless networks can be handled
    by the architecture
  • Slight increase in network throughput when APA
    was compared to static configuration (using a

The APA architecture
The testing scenario (in simulator)
  • Initially, 40, 30, and 30 of the available
    bandwidth are set for EF, AF, and BE,
    respectively, for domains A, B, and C
  • Traffic was generated from D to A with sending
    rate of 6 Mb/s, while A is moving from domain A
    to B at t50, and then from B to C at t80
  • As the user moves from one domain to the other,
    the policy P is translated to different
    network-level objectives by the APA at domain A
    depending on the location of the user.
  • See the paper for detailed testing parameters

Simulation results
  • Throughput comparison between the statically
    configured network and the proposed scheme. (a)
    Achieved throughput in case of static
  • (b) Achieved throughput in case of APA.

An Architecture for Coordinating Multiple
Self-Management Systems, S. Cheng, A. Huang, D.
Garlan, B. Schmerl, P. Steenkiste, 2004
  • Some possible self-management systems and their
  • Self-configuring system
  • Adapt automatically to changes in the environment
  • Self-healing system
  • Discover, diagnose and react to disruptions
  • Self-optimizing system
  • Monitor and tune resources automatically
  • Self-protecting system
  • Anticipate, detect, identify and protect itself
    from attacks
  • How to deal with (possibly) conflicting decisions
    coming from different self-management modules?
  • Solution separate logical layers for data
    presentation (translation) and system access

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Rainbow Architecture-Based Self-Adaptation with
Reusable Infrastructure, D. Garlan, S. Cheng, A.
Huang, B. Schmerl, P. Steenkiste, 2004
  • Mechanisms that support self-adaptation currently
    exist in the form of programming language
    features such as exceptions and in algorithms
    such as fault tolerant protocols
  • These mechanisms are often highly specific to the
    application and tightly bound to the code. As a
    result, self-adaptation in todays systems is
    costly to build, difficult to modify, and usually
    provides only localized treatment of system
  • The Rainbow-architecture tries to solve two
  • How to handle a wide variety of systems using
    external control
  • How to make 1) in a cost-effective manner
  • The solution re-usable infrastructure with a
    mechanism to customize the infrastructure to
    particular applications needs

Reusable Rainbow units
  • System-layer infrastructure
  • Low-level system information can be published by
    or queried from the probes. Additionally, a
    resource discovery mechanism can be queried for
    new resources based on resource type and other
  • Architecture-layer infrastructure
  • Gauges aggregate information from the probes and
    update the appropriate properties in the
    architectural model
  • Translation infrastructure
  • Translation repository maintains translations

Architectural style
  • While reusable infrastructure helps reduce the
    costs of adding self-adaptation to systems, it is
    also possible to leverage commonalities in system
    architecture to encapsulate adaptation knowledge
    for various system classes
  • To capture system commonalities, Rainbow adapts
    the notion of an architectural style
  • An architectural style characterizes a family of
    systems related by shared structural and semantic

Case study 1 Client-server system
  • The client and server components are implemented
    in Java and provide remote method invocation
    (RMI) interfaces for the effectors to use in
    performing adaptation operations
  • Clients connected to a server group send requests
    to the groups shared request queue, and servers
    that belong to the group grab requests from the
  • Focus on response time that clients percieve
  • Architectural style created for the system
    (Client.responseTime, Server.load,
    ServerGroup.load, Link.bandwidth,
    ServerGroup.addServer(), Client.move(),)
  • If response time for a client is too long, the
    Adaptation Engine executes a response strategy
    (move client to another group, add server to
    group, )

Towards a Model-Driven Architecture for
Autonomic Systems, D. Gracanin, S. Bohner, M.
Hinchey, 2004
  • Agents (program code) running on Java virtual
  • Virtual machines are located in nodes of the
  • Tasks sent between agents
  • One must locate the most suitable agent for the
  • COUGAAR supports hierarchical task decomposition
  • COUGAAR provides facilities to measure and
    propagate performance metrics collected at all
    levels of the architecture
  • Platform specific measurements are taken by the
    computer system level instrumentation and are
    translated into device-independent values.
  • Measured data is used by a Servlet (web) and
    adaptation engine
  • provides adaptive control through the Adaptivity
    Engine that makes use of the measurements
    collected by the metrics service
  • COUGAAR agents
  • An agent consists primarily of a blackboard and a
    set of plugins. The blackboard is essentially a
    container of objects that adheres to
    publish/subscribe semantics
  • Agents can move from one node to another through

Autonomic WWW Server Management with Distributed
Resources, T. Araki, 2004
  • Problem Computing resources arent share
    effectively across organization boundaries (only
    within organizations)
  • Solution A working and tested concept that
    provides means to share computing (server)
    resources across organization boundaries
  • Computing resources are rented from different
    organizations (new business model)
  • Supports J2EE systems
  • Main component Autonomic Web Server Manager
  • Monitors QoS (response time to client requests)
  • Autonomically manages the computational resources
    (addition, removal) based on the response time

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Hierarchical Model-based Autonomic Control of
Software Systems, M. Litoiu, M. Woodside, T.
Zheng, 2005
  • A system to
  • Autonomically react to workload changes
  • Search for resource-optimal configurations
  • Used in
  • Information- and transaction-based software
  • E-commerce, insurance claim submission, web
    banking, etc.
  • Provisioning Controller
  • Adds and removes hardware components to the
    system at runtime (for example web servers to a
  • Application Contoller
  • Balances resources and workload across system
  • Component Controller
  • Adjusts components run time parameters to
    achieve desired QoS level

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A Framework for Self-Management of Hybrid
Wireless Networks Using Autonomic Computing
Principles, C. Shen, D. Pesch, J. Irvine, 2005
  • Hybrid Wireless Networks
  • Scalable and adaptive wireless network
    architecture utilizing a mixture of cellular and
    ad hoc multi-hop routing (less base stations
  • Drawbacks routing complexity, radio resource
    heterogenity, network infrastructure design
    growth -gt difficult to manage
  • A framework proposition for the autonomic
    management of hybrid wireless networks
  • In the paper the authors state that they are
    going to use Artificial Intelligence techiques
    (neural networks, fuzzy logic and Q-learning) in
    the management of hybrid wireless networks to
    ease the management burden
  • Q-learning
  • A variant of reinforcement learning
  • Autonomy is supposed to be implemented at MAC,
    routing and application levels independently
  • No algorithms, implementation or testing is

Autonomic system for mobility support in 4G
networks, P. Vidales, J. Baliosian, J. Serrat, G.
Mapp, F. Stajano, A. Hopper, 2005
  • Excellent paper with detailed description of the
  • Access technologies in 4G networks will be
    heterogenous (Satellite, UMTS, IEEE 802.16a, IEEE
    802.11, etc.)
  • Heterogenous networks introduce additional
  • Many different types of available access points,
    handover triggered by multiple events, execution
    methods depend on context, etc.
  • More intelligence needed to handle these
  • An architecture called PROTON was presented
  • The architecture is supposed to
  • know itself, its environment and context
  • Configure and reconfigure itself under varying
    and unpredictable conditions
  • Optimizes its functionality constantly
  • Architecture divided to network- and host side

Network side components
  • A policy specification language is used by
    operator to insert policies to the network side
    of the architecture through the policy editor
  • Model Deployment Module sends suitable policies
    to mobile devices Policy master that acts as a
  • Sending is done by sending a Java object through
  • An example of a policy Mobile devices that are
    treveling at speeds over 90 km/h should never
    connect lo lower level access point (like from
    GSM cell to WLAN-hotspot)

Host-side components
  • Sentinels retreive dynamic data (like the speed
    of the node from GPS) and generate events based
    on the data
  • Policy master
  • receives events (like Transition-to-pedestrian-spe
    ed-event) from sentinels
  • Decides the possible actions to execute
  • Sends these actions to the Enforcement Layer
  • Enforcement Layer acts as a PEP
  • The Enforcement Layer captures router
    advertisements before they reach the
    IPv6-handover-module and hand only legal
    information to the hadover procedure

Example sentinel code
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