Cyber Entity Directory Service

1
Cyber Entity Directory Service
2
Motivation

• In BIONET a CE may only maintain a finite number
  of relations.
• These relationships stabilize based upon
  similarity and usefulness.
• If a CE attempts to locate another CE that is not
  closely related or directly useful, search may
  take a long time.
• What if a CE application provided assistance to
  the search by organizing a distributed directory?
• The CE directory provides a fast look up service
  for other Cyber entities in the hopes of making
  discovery more efficient.

3
Motivation (cont.)

• What if network is highly dynamic and is
  constantly undergoing stabilization?
• Network may be slow because too many CEs are
  searching too much of the network.
• Ex PDA / Cellphone network with PDAs and
  Cellphones constantly coming on and off of the
  network.

4
Proposed Purpose

• To provide a mechanism for fast look up of CEs
  based on a CEs published list of keywords.
• The mechanism is NOT the standard query method.
  It is meant only to enhance the relationship
  method.
• Suppose it takes 30 hops to find something in the
  directory while it takes 4 hops to find the same
  CE you are related to. Clearly the relational
  query is faster.
• Suppose it takes 30 hops to find something in the
  directory but takes 100 hops to find a CE you are
  not directly related to ( or have links
  established to ). Clearly it is better to take
  the directory.
• CEs must find a balance between relying on the
  directory and their own relationships.

5
Approach

• Build a multi-tier architecture of CEs that
  maintain a table of look-up relationships (
  Distributed Tree structure )
• Bottom level CEs maintain relationships with CEs
  located in the directory. When connecting CE
  needs a lookup, it sends the query to its
  connected bottom level CE. The bottom level CE
  then checks if it has a link to the CE we are
  searching for. If not, the query is forwarded to
  the bottom level CEs connecting midlevel CE.
• Midlevel CEs link bottom level agents to higher
  level CEs. If a query is received, it checks to
  see if it has a link to the CE requested. If it
  does it sends the request down the tree to the
  appropriate midlevel / bottom level CE.
• Top level CE communicate to each other. They
  find the correct Top level CE to send the query
  down for a given keyword/words. It then routes
  that keyword/words down to its mid and finally
  bottom level CE to locate the CE requested.
• CEs at each level distribute their knowledge base
  to so that any given CE has only a subset of the
  CE links to the next level down and only a
  constant value of links to the next level up. (
  ie Top CEs contain links to keywords (a- b) ,
  (c f ) , ( g z). Mid level contain ( aa af
  ) , (ag az ) Bottom level contain ( aaa
  aaf )
• Option Let the number of tiers / links per tier
  evolve.

6
Approach (cont.)
Top Directory CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Bottom Dir CEs
Bottom Dir CEs
Bottom Dir CEs
CE
CE
CE
CE
CE
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Approach (cont.)
Top Directory CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Bottom Dir CEs
Bottom Dir CEs
Bottom Dir CEs
CE
CE
CE
CE
CE
CE requests for CE with keyword xyz
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Approach (cont.)
Top Directory CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Bottom Dir CEs
Bottom Dir CEs
Bottom Dir CEs
CE
CE
CE
CE
CE
Bottom level CE doesnt have any links to
anything of the xyz division. Query is
forwarded up one level.
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Approach (cont.)
Top Directory CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Bottom Dir CEs
Bottom Dir CEs
Bottom Dir CEs
CE
CE
CE
CE
CE
Mid level CE has a link to divisions of xy.
Mid level CE forwards the request Down to the
link with xy
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Approach (cont.)
Top Directory CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Bottom Dir CEs
Bottom Dir CEs
Bottom Dir CEs
CE
CE
CE
CE
CE
Bottom level CE has links to xy( a j ) and
xy( k z). Link is checked for integrity And
location / relation information is sent back up
the tree.
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Approach (cont.)
Top Directory CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Mid Dir CEs
Bottom Dir CEs
Bottom Dir CEs
Bottom Dir CEs
CE
CE
CE
CE
CE
Relation / location information is forwarded to
requester
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Approach (cont.)

• Distribute the CEs over the network.
• Give CEs parameters so that they try to evenly
  distribute themselves over the network.
• Option Let the parameters evolve to avoid
  network segments that have high failure rate,
  slow response etc.
• Distribute each Node over multiple CEs in
  order to achieve fault tolerance( clustering ).
• Each node has participating CEs.
• The participating CEs form a graph to link to
  each other.
• Option Allow parameters for the number of CEs
  per node to evolve.

13
Approach (cont.)
Top Level Node for (A F)
CE 2
CE 4
CE 1
CE 5
CE 3
To Node (AA CD)
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Approach (cont.)
(A F)
(AA CD)
To next level down
To next level down.
15
Approach (cont.)

• Make the application an extension of BIONET that
  CEs chose to participate in rather than be
  forced to.
• If CEs can satisfy all their needs effectively
  without the directory, then they can exclude
  themselves from the directory. This leaves fewer
  CEs in the directory, thus reducing search
  resources overall.
• Either chosen at runtime by evolution or at
  compile time by application / CE designers

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Approach (cont.)

• Option Allow base level CEs to maintain
  relationship areas. ie. Relate to a single CE
  and through that CE it relates to all neighbors.
  Max relationship distance as an evolution
  parameter.
• Option Allow directory CEs to modify random
  relationships of CEs in applications to be more
  efficient.
• Option Aid CE clustering. When a CE is born, it
  automatically invokes the directory service to
  find similar CEs are then linked via
  relationships to the new CE. This facilitates CE
  clustering at CE inception.
• Not needed for CE reproduction. CEs that
  reproduce can automatically give their offspring
  good relationships.
• However, in a mobile device network, CEs may be
  spontaniously born in areas where similar CEs may
  not exist.

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Approach (cont.)

• Use the directory as an alternative to
  relationship searching. Ex Use the directory one
  time then establish a relationship to the node
  that provides the service required. This way
  relationships would still be the defacto search
  method, the directory just facilitates fast
  lookup when needed.

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Alternate Solutions

• Allow only BIONET relationships and current
  discovery mechanisms to handle discovery.
• Does not allow for rapid lookup of unrelated
  entities.
• Build a distributed directory at the BIONET
  platform level rather than implement it with CEs
• Inherently similar to the concept of using CEs.
  However, CEs may benefit from evolution that the
  platform level application would not.

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Alternate Solutions

• Distributed Consistent Hashing ( Chord protocol
  applied to BIONET. http//pdos.ics.mit.edu/chord/
  )
• Provides good upperbound on both maximum number
  of links to other agents as well as search time.
  approx O(log( n ))
• Does not allow anonymity of services
• n agents requires nlog(n) total relationships in
  the system.

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Alternate Solutions (cont.)

• Adapt a graph theory approach like the HITS or
  HyperClass algorithm for webcrawling.
• Must be implemented at the CE level so all CEs
  are a part of the directory, not just a subset.
• Similar to Freenet, but instead of node becoming
  good at searching an area, a node gets ranked on
  how well it searches.

J. Kleinberg, S.R. Kumar, P. Raghavan, S.
Rajagopalan, and A. Tomkins, The web as a graph
Measurements, models and methods, Proceedings of
the International Conference on Combinatorics and
Computing 1999.
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Advantages

• Applications that wish to be diverse may
  implement a protocol to talk to the CE directory
  service. This would link highly mobile and
  diverse agents together, while leaving relatively
  stagnant agents out of the directory, keeping the
  size of the directory limited and thus faster.

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Advantages (cont.)

• Rapid discovery for service emergence.
• Since CEs for an application exist on the
  network, why not allow other applications to use
  those components as well?
• Applications that wish to reuse components must
  locate those components quickly and efficiently.

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Advantages (cont.)

• Since the application is itself part of BIONET,
  it undergoes evolution and natural selection.
  This will act as the default load balancing
  mechanism in the system.
• Could be implemented in an anonymous fashion by
  using hash functions rather than direct key
  values.
• Since the applications sole purpose is fast
  lookup, it exists in a symbiotic relationship
  with the BIONET. Ie If the application thrives
  so does BIONET because fast discovery is possible.

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Challenges

• Investigate scalability of the concept and
  related issues.
• How to keep the directory from monopolizing
  Bionet time.
• Investigate good graph algorithms to distribute
  nodes in the network. They must provide
• Fault tolerance If a given CE goes down for a
  node, the other CEs must take over for it and
  reestablish relationships for it.
• Efficiency The network will be dynamic so they
  must exchange information efficiently.
• Investigate evolutionary parameters of the
  system.
• Which parameters should be fixed? Which
  parameters should evolve?

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Goals

• To provide a directory service for rapid location
  of Cyber Entities within the BIONET architecture.
• To distribute the directory in a fashion such
  that it is both fault tolerant and efficient.
• Evaluate alternate solutions to the proposed
  directory as both Agent based, and platform based
  algorithms.
• Test the effectiveness of BIONET evolution in
  combination with routing algorithms.