IMPROVING RESPONSIVENESS BY LOCALITY IN DISTRIBUTED VIRTUAL ENVIRONMENTS

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IMPROVING RESPONSIVENESSBY LOCALITY IN
DISTRIBUTED VIRTUAL ENVIRONMENTS

• Luca Genovali, Laura Ricci, Fabrizio Baiardi
• Lucca Institute for Advanced Studies
• Department of Computer Science
• University of Pisa, Italy
• ECMS 2007-Prague 4-6th June 2007

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PRESENTATION OUTLINE

• DVE an overview
• Consistency Models, Perceptive Consistency
• Local Lag
• Our proposal the MultiLags approach
• Experimental results

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DISTRIBUTED VIRTUAL ENVIRONMENTS

• Distributed Virtual Environments (DVE) A
  Virtual Environment including a set of Avatars
• Interacting within a virtual world.
• Hosted by geographically distributed computers.
• Usually controlled by the users
• Instances of DVE are
• Large scale combat simulations.
• Massively Multiplayer Online Games (MMOG).
• Distributed simulations of complex physical
  models
• based upon domain decomposition approach.

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DVE RELATED ISSUES

• Issues related to the definition of a large-scale
  DVE
• Consistency
• Scalability
• Performance/Responsiveness
• Persistency
• Reliability
• Security

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CONSISTENCY MODELS

• Causality
• Concurrency
• Simultaneity
• Instantaneity

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PERCEPTIVE CONSISTENCY

• Perceptive Consistency a wall-clock time based
  model integrating
• Simultaneity if two actions occurs
  simultaneously, then all the hosts perceive them
  at the same instant of time.
• Each host perceives at t ? any action occurring
  at time t
• It requires clocks synchronization but it
  guarantees a total order of events (a tiebreaker
  may be introduced to order simultaneous events)
• ? Response Time (typical values 100- 400
  millisec) These values guarantee that humans
  cannot perceive the delay ?, because of their
  perceptive limits

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THE LOCAL LAG TECHNIQUE

• Local lag a technque to implement perceptive
  consistency
• Basic idea rendering of events is delayed by
  any host of an interval of
• time ?, (local lag) in order
• to hide the delay due to network latencies in the
  notification of events to other hosts.
• to guarantee event simultaneity
• Problems to be solved
• Instantaneusness is maintained provided that ?
  is kept small
• If ? is statically defined
• it may be overestimated because of latency
  jitter
• Overestimation of ? decreases the responsiveness
  of the application and favours cheating.

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THE LOCAL LAG TECHNIQUE IMPLEMENTATION

• Each event e is associated with a timestamp T t
  ?, where
• t is the wall clock time corresponding to the
  generation of e
• ? is the value of the local lag
• An event e
• on the local host is stored and rendered at T
• on the remote hosts
• if e is received on time e is rendered at T
• if e is received after T e is discarded

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OUR PROPOSAL THE MULTILAGS APPROACH

• Multilags extends the local lag approach by
• Dynamic definition of the value of ?
• Multiple values for ? are associated to different
  groups of interacting hosts
• Dynamic definition of ?
• ? is dinamically updated according to network
  conditions. It is increased if the network is
  congestioned, it is decreased if the latency is
  low
• Multiple values of ?
• DVE locality each DVE entity interacts with a
  subset other entities of the DVE only
• Groups of interacting entities may exploit
  different values of ? .

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DVE LOCALITY AREA OF INTEREST

• Area of Interest (AOI) of a DVE entity e it
  includes entities which may interact with e
• Mobile Area of Interest
• Area surronding the avatars position.
• Dynamically updated as the avatar moves.
• Static AOI
• Tightly bounded to a particular portion of
  virtual environment, not to a particular avatar
• May be dinamically modified
• Area of Interest generally exploited to define
  scalable DVEs overlay topologies

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STATIC AOI THE MULTILAGS APPROACH

• Static AOI
• a distinct value of ?i for each static region ri
• ?i
• is exploited by any entity in ri
• depends upon the state of network connections
  among the players belonging ri.
• Each entity updates ?i when it moves to a new
  region
• ?i Caching
• ?i Prefetching

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DYNAMIC AOI THE MULTILAGS APPROACH

• Dynamic AOI detecting groups of mutually
  interacting entities
• Definition
• belongs to relation
• A belongs to B ?
• A belongs to the AOI of B.
• A group S of interacting entitities is a set of
  entities such that belongs to on S is equal to
  its transitive and symmetric closure.
• Complex dynamic tests to verify this condition
  in a distributed environment.

S
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OUR PROPOSAL

• Our solution exploits static AOIs
• A multicast group for each region
• The value of ? is updated according to the
  interactions among the entities in a region
• ? is updated
• periodically, while the entity stays in a region
• anytime the entity moves to a new region

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MULTILAGS IMPLEMENTATION

• The value of ? is dynamically computed by each
  host according to its Local Network View (LNV)
• Local Network View information collected by H
  on the network status. It depends upon
• the number of late messages with respect to their
  timestamps
• the number of lost messages
• Each host may
• perceive different LNV
• compute a distinct values of ?
• but.... all the interacting entities must exploit
  the same value of ? to guarantee simultaneousness
  and correct event ordering

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MULTILAGS IMPLEMENTATION

• A set of interacting hosts executes a protocol to
  reach a distributed consensus on a common value
  of ?
• Each host
• updates its LNV at each message reception
• broadcasts its LNV to all the interacting
  entities. Heartbeat messages may be exploited
• update local lag periodically combines its LNV
  with those received from the interacting hosts in
  order to refine the value of the local lag

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MULTILAGS IMPLEMENTATION
Sending operations

• Each event sent by an entity E is associated with
• the local lag
• the LNV of E
• When an host P receives a messages
• Computes the delay/...of the message with respect
  to its timestamp
• Updates P LNV

Receiving operations
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MULTILAGS IMPLEMENTATION

• A fully distributed consensus may introduce
  inconsistencies because distinct hosts may
• perceive different values of LNV due to packet
  loss
• execute the procedure at different instants of
  time
• Definition of a coordinator
• computes the new value of the local lag and send
  this value to all the interacting hosts
• coordination selection based upon the IP
  address
• SPMD-like code

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LOCAL LAG DYNAMIC UPDATE
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EXPERIMENTAL RESULTS

• Testing Environment 16 hosts, connected by a
  local network.
• The DVE is partitioned into four rectangular
  regions
• Wide area network conditions simulation network
  delays generated according to an exponential
  distribution.
• A distinct average latency has been associated to
  each region.
• The values associated with the regions 03 are,
  respectively, 80,120,160,200 ms.
• Update Local Lag is executed every 5 seconds. The
  response time is incr\decr by 10 msec. The
  initial value of the response time is 100 msec.

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EXPERIMENTAL RESULTS AVERAGE DRIFT
2
0
1
3
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EXPERIMENTAL RESULTS NUMBER OF ERRORS
0
2
1
3
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DEADLINE BASED CONSISTENCY MODELS

• ?- Sequential/Causal Consistency
• Introduces the notion of physical time
• Simultaneity is not captured.
• Reading in Time A Read operation R on a
• object X executed at time T(R) occurs in time if
  it returns the value written by operation W at
  time T(W) and no intermediate writes occur in the
  system in the interval of time T(W), T(R)-?,
  where ? is a parameter characterizing the
  model.
• An implementation of the models requires physical
  clocks synchronization (ex via NTP)