SelfOrganizing Adaptive Networks

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Self-Organizing Adaptive Networks

• Hari Balakrishnan
• MIT Laboratory for Computer Science
• http//inat.lcs.mit.edu/
• hari_at_lcs.mit.edu

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Some Trends

• Heterogeneous data types
• Multimedia, telepresence, games
• Wireless and mobility
• Lots of new technologies
• Embedded computers, devices, sensors
• Networks everywhere, network everything!

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Imagine...
Services in our environment
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Challenges

• Heterogeneity
• Devices, hand-helds, mobiles, sensors
• Wireless wired links
• Variety of applications, data and services
• Dynamism and spontaneous operation
• Need rapid deployment and organization
• Highly decentralized fault-tolerant
• Must make management easy!

Need self-organization and adaptation
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Current View of Networks
Clients

• Mostly static topology services
• Applications cannot learn about network
• High management cost
• Failures happen!

Routers
Servers
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Towards the Future
Providers
Servers
Entertainment
Sensors
People
Consumers
Handheld
Coffee
Efficiently configure topology match providers
with consumers Learn and adapt well to
heterogeneity and network conditions
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Intentional Naming System
Names express desired properties they are
intentional

• Names are query expressions
• Attribute-value matches
• Range queries
• Wildcard matches

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Naming Architecture
camera510.lcs.mit.edu
Lookup
image

• Intentional Name Resolvers
• form a distributed overlay

Integrate resolution and message routing
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Details

• Separate into inter-domain and intra-domain
  components
• Architect intentional names around virtual spaces
• Robust name resolution routing based on soft
  state
• Dynamic views to track dynamic data attributes

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Benefits

• Mobility (of people and services)
• Service location and resource discovery
• Group communication
• Server replication data caching
• Device networking
• Take efforts like JiniTM and Universal Plug
  PlayTM to the next level

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Adaptation
Application heterogeneity
Network heterogeneity

• Overload causes congestion wireless links often
  degrade performance
• Solution new approaches to congestion management
  and wireless protocols

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Security and Privacy

• Moving from a packet-centric abstraction to a
  service-, device-, and people-centric one
• Domains define trust regions
• But all name resolvers cannot be trusted
• Location information may need to be private
• Data has to be secure (easier)
• Challenge privacy without compromising
  performance or function

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Research Areas

• Intentional Naming System
• End-to-end adaptation framework
• Congestion Manager
• RadioActive networks
• Better than best-effort networks
• Security and privacy protocols
• Lots of new applications

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Applications

• WIND Wireless Networks of Devices
• Ad hoc collaborative environments
• Adaptive sensor applications
• Self-configuring network topologies
• Adaptive applications (e.g., audio, video,
  telepresence)
• Service location resource discovery
• Dynamic replica placement and selection
• Home network architectures

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The Future Networks That Learn

• Better application and user control over networks
• Dynamism, mobility, spontaneity, robustness and
  adaptation
• Integration with the real world

Self-organization middleware and adaptation
protocols are key to making this a reality