Middleware or simulator for Autonomic Communications
S38.4030
Middleware or Simulator for
Autonomic Communications
Yang Qiu
Networking Laboratory
Helsinki University of Technology
yangqiu@cc.hut.fi
26th May, 2006
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Middleware or simulator for Autonomic Communications
S38.4030
The complexity of Autonomic
Communications
 dynamically build up the personal networking system.
– The devices, terminals or nodes are mobile.
– The devices, terminals or nodes can join in or leave dynamically.
 enable multiple services on various of networks.
– Collecting the information is costly active.
– With the increasing of scale, the collecting spend more resources.
 implement the adaptation of network.
– The adaptation of scale of sensor in network.
– The adaptation of node topology, network connectivity, and node mobility.
– The adaptation of computation and energy constraints
 build full automating the maintenance and optimization of large computer system.
– Human adjustment is very expensive.
– The work load of human adjustment will becomes very huge.
 Wireless networks need extra management.
26th May, 2006
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Middleware or simulator for Autonomic Communications
S38.4030
The Problems of Autonomic
Communications
 What do I need to support ubiquitous applications?
– Communication adaptability and extensibility
• Explicit knowledge of how communication protocols compose and interact
is required
• A semantic model capable to assure safe adaptation is needed
 Distributed systems evolve dynamically and components interact
with an environment that is not under their control
 Communication protocols provided in current middleware
frameworks are tailored to specific and usually static requirements
not suitable for dynamic environments
 Reflection has been used to achieve both separation of concerns and
dynamic adaptation to changing environments requirements
26th May, 2006
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Middleware or simulator for Autonomic Communications
S38.4030
Middleware is the key element of
autonomic communications
 Middle ware is the key element of sharing the collected information
– A self management middle ware is needed, which should implement the
collection, aggregation, maintenance, and dispersion of heterogeneous
information.
 Middle ware is the key element of building the cooperating objects,
– hidden the complexity for application development for different kinds of
communication environment.
 Middle ware is the key element of adaptation of different protocols and
nodes.
– The network needs an adaptive middle ware, which automatically discern
needed parameters settings or software usages and adjust them automatically.
 Full automation without any human efforts.
– Simply the maintenance and optimization of human effort.
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Middleware or simulator for Autonomic Communications
S38.4030
Functionality of Middleware
 Quality and quantity of collected information.
– Higher quality will lead more successfully self management.
– To collect Higher quality is a relatively more costly activity in self management process.
– Common information should be used to minimize the cost of collecting information
 Cooperating objects
– Realizes a distributed platform of interfaces and services that reside between the
applications and the devices.
– This approach is denoted as a reflective middleware.
 event and device manager
– Sensor application adaptivity and updates.
 Full automation without any human experts.
– Top-down approaching to capitalize on opportunities to optimize at system–wide level.
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Middleware or simulator for Autonomic Communications
S38.4030
Dynamic adaptive middleware and
reflective middleware
 Adaptive middleware
– Can change functional or non-functional constraints.
• Statically, it leverages the capabilities of specific platform or environment the
middleware runs in.
• Dynamically, it allows application to run with optimum system responses where the
requirements or environment is changing.
 A reflective middleware is a approach to build dynamically adaptive
middleware
– Based on Computational Reflection Concept
• Reification and Absorption
• Meta-level architectures, meta-objects and meta-object protocols.
• Structure and behavioral reflection.
– A reflective system
• Supports Causally Connected Self Representation (CCSR).
• Can reason about and act up itself. Is able to inspect and change itself during the
course of its execution (inspection & adaptation).
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Middleware or simulator for Autonomic Communications
S38.4030
reflective middleware
 Definition: Reflective Middleware is simply a middleware
system the provides inspection and adaptation of its behavior
through an appropriate CCSR
 Features
– Open model, composed of group of collaborating components.
– Support for dynamic customization of components, accessible through
meta-level interfaces.
– Gives a two or multi level view of system
• Base: application objects
• Meta level: internal representation of middleware components
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Middleware or simulator for Autonomic Communications
S38.4030
How can reflective middleware
help Autonomic Communications
A communication reflective framework
– Allows dynamic customization of communication protocols
(high adaptability and extensibility)
– Constraints composition of services and protocols in order
to prevent functional interference that could lead to an
inconsistent configuration state of the system (safe
flexibility)
– Helps to identify and reason about issues of correctness,
which may be subtle and complex
• fluctuations in the communication environment may interfere with
the execution of communication protocols and middleware services
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Middleware or simulator for Autonomic Communications
S38.4030
Example 1: The middleware of
Collective
The middleware provide the common information for
all the nodes.
– The common information should be collected only once to
minimize the cost of process.
– The Middleware of Collective is an independent
information service for self-managed middleware
platforms.
– The service provides an effective support service for the
collection and management of information.
– The Middleware is designed to reduce the effort needed to
collect the information from an environment.
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Middleware or simulator for Autonomic Communications
S38.4030
The Middleware of Collective
Service 1
(i.e. Multimedia service)
Performance
Interceptors
Network
Activity
Service 2
(i.e. Video conference)
Performance
Interceptors
Client
Feedback
Network
Activity
Service 1
(i.e. Multimedia service)
Client
Feedback
Service 2
(i.e. Video conference)
The Middleware of Collective
Performance
Interceptors
26th May, 2006
Network
Activity
Client
Feedback
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Performance
Interceptors
Network
Activity
Client
Feedback
Middleware or simulator for Autonomic Communications
S38.4030
The overview of Middleware of
Collective
The middleware is broken into following parts:
– Resource Registry. Listing of available information source.
– Local Service Container. Information collection and
analysis entities located within the platform.
– Remote Source Container. Offers facilities to hook-in
external and legacy information sources to the platform.
– Container Services. Support services for both local and
remote containers within The Collective. Services include
persistence, transaction and distribution.
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Middleware or simulator for Autonomic Communications
S38.4030
The Middleware Deployment
options
 The most straightforward deployment is as a standalone server to manage
information consumers and producers within self-managed systems.
 Another way is to distribute the service in multiple physical sites each
containing large collections of self-managed systems.
– A key benefit of the service is its capability to interconnect to share information
between multiple services and locations.
 There are a number of projects do possess comprehensive information
capabilities and represent and manage it in a variety of manners.
–
–
–
–
K-Components
Open ORB
The Quality Objects (QuO)
SNMP
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Middleware or simulator for Autonomic Communications
S38.4030
Example 2: the middleware for
Cooperating Objects
 The middleware must have a conceptual model of its current
state and the preferences of the user.
 If we want the network works seamlessly in both
environments of client-server and ad-hoc. the “server” needs to
be distributed among all members of the ad-hoc community. It
leads the system to operate on the peer-to-peer paradigm.
 It’s possible to implement it with necessary enhancements on
existing results, particularly from the IETF and OMG.
–
–
–
–
IP
Wireless CORBA
Super Distributed Objects
Model Driven Architecture
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Middleware or simulator for Autonomic Communications
S38.4030
Example 3: the middleware of
Impala
The middleware of Impala must provide the longterm management of the sensor application software.
– By adopting a middleware layer that can update and adapt
applications dynamically, new protocols can be plugged in
at any time, and switches between protocols can be
performed at will.
The Impala uses a middleware layer that is intended
to act as an operating system, resource manager, and
event filter on top the specific applications which can
be installed and run.
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Middleware or simulator for Autonomic Communications
S38.4030
The Middleware of Impala
 There are 3 middleware of Impala:
– The Application Adapter adapts the application protocols to different runtime conditions
to improve performance, energy-efficiency and robustness.
– The Application Updater receives and propagates software updates through the wireless
transceiver and installs them on the node.
– The Event Filter captures and dispatches events to the above system units and initiates
chains of processing.
Application
Initialize
Application
Terminate
The Middleware of Update
updater
Application
Query
Send Done
Handler
Packet
Handler
Timer
Handler
Timer
Handler
The Middleware of
Application Adapter
The Middleware of Event Filter
Device
Event
26th May, 2006
Send Done
Event
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Packet
Event
Time
Event
Data
Event
Middleware or simulator for Autonomic Communications
S38.4030
The system-wide autonomic
computing
 The middleware does not provide the a top-down approach to
developing autonomic systems.
– such an approach fails to address the effects of interactions
between various components and does not capitalize on
opportunities to optimize at a system-wide level.
 In order to enable the network systems incrementally tune
themselves based on observed usage patterns and enable the
network systems to adapt to changes in connectivity due to
system failures and/or component upgrades.
– Machine learning, it’s the fundamental challenges.
– A top-down approaching way of developing autonomic systems. The
autonomic components of entire system should work well, not just
independently, but in concert with other such components.
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Middleware or simulator for Autonomic Communications
S38.4030
The Study is still needed for
system-wide autonomic computing
 A high-level simulator can be used to facilitate the study of machine learning in a
complex network systems.
– A high-level simulator is needed, it is capable of modeling the relevant types of
interactions among the many different components of a computer system.
– But detailed simulators exist for individual system components, such as networks,
databases, etc. Till now there is no simulator that models system-wide interactions.
– Therefore, a study system must simulate the way of a computer network processes from
a high-level perspective.
 Example: The simulator of Job Routing and Scheduling
– The simulator is very general purpose and can be used to represent many different kinds
of networks of the Job Routing and.
• Simulator includes the following the components:
–
–
–
–
–
–
–
26th May, 2006
Nodes
Users
Machines
Links
Packets
Jobs
steps
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Middleware or simulator for Autonomic Communications
S38.4030
The simulator of Job Routing and
Scheduling
 The simulator provides a valuable test bed for new approaches to
autonomic computing. Because:
– The simulator is very general, it can be used to represent a wide variety of
computer systems with arbitrary topology.
– The simulator is highly modular which makes it easy to insert intelligent agents
to control any aspect of the system’s behavior.
– The simulator captures many of the real world problems associated with
complex computer systems while retaining the simplicity that makes
experimental research feasible.
– The simulator provides evidences of the value of combining intelligent,
adaptive agents at more than one level of the system:
• machine learning methods offer a substantial advantage in optimizing the
performance of computer networks.
• the best performance is achieved only by placing intelligent, adaptive agents at more
than one level of the system.
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Middleware or simulator for Autonomic Communications
S38.4030
Conclusion
 The reflective middleware can be used for Collective and
Cooperating Objects.
 Multi-layered Middleware supports multiple applications by
adopting an event-based modular programming model and
providing a friendly programming interface. And Multilayered middleware also provide a lightweight system layer to
perform dynamic application adaptation based on parameters
and device failures and automatic application updates based on
a specialized software management and transmission
mechanism.
 The middleware does not provide the system-level
optimization.
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