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Cache Updates in a Peer-to-Peer Network of Mobile AgentsElias Leontiadis
Vassilios V. Dimakopoulos
Evaggelia Pitoura
Department of Computer Science
University of Ioannina
Greece
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Introduction Multi-Agent system (MAS)
Network of software agents Computational resources are distributed across this network The agents cooperate to fulfill a specified task
To do so, they need resources provided by other agents
Open MAS
No global knowledge of the agents in the system Thus, agents are not aware of which agent provides a particular
resource
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Resource discovering in open MAS
Approaches: Central directory
There is a single agent which holds a directory, matching resources to agents
Middle agents Some agents (middle agents) keep a fraction of the directory
Our approach:
Distributed caches: each agent keeps part of the directory Performance Failure tolerance
Issue
How to locate an agent that provides a particular resource
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Distributed cache model
Each agent maintains cache entries about k different resources of other agents
Cache entries: keep the contact information of one agent that provides the resource
The system is modeled as a directed graph G(V;E) called the cache network
If agent u v, then v is a neighbor of u
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R4: A2 R8: A6
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Cache of a1
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Searching for a resource We consider the following flood-based search methods
Plain flood Forward the query to all its neighbors for a maximum number of steps (TTL: Time-To-
Live)
Teeming Propagates the search message only to a random subset of its neighbors Φ the fixed probability of selecting a particular neighbor
Teeming with decay like teeming, but the subset gets smaller as we go deeper into the tree Φ = (1-d)level d < 1. d is called decay parameter
K-Random paths (K-walkers) The agent that initiates the search selects K random neighbors All the other agents forward the message to only one random neighbor
Plain flood Teeming 2-Random paths
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The Problem: Cache network and mobility
Mobility Agents may move (e.g. change IP) Resources may move from one agent to
another
Problem: when an agent A moves
Other agents that cached A’s resources before, now have invalid cache entries
In fact, no one knows the new location of agent A: when it moved, it didn’t inform anyone
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Old location
New location
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Cache update policies
We propose a number of update policies that combine two basic techniques: Pull-based method
Initiated by the agent that wants to update its cache Push-based method
Initiated by the agent that moves.
Since the cache entries form our overlay network, what we update is the network topology itself.
We consider the problem of cache updates in a peer-to-peer network of mobile agents
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Pull-based methodInitiated by the agent that wants to refresh a cache entry (either periodically or on-demand when it discovers that an entry is invalid)
Any flood-based search algorithm can be used Plain flood Teeming (with decay) K-Random paths
Pull methodsearch the network for an agent that knows the new location
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Push-based method
Pull cannot work alone When an agent moves, it must inform at least one
other agent about its new location
Push methodWhen an agent moves, it “pushes” a message to the network to inform other agents about its new location
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Our Update Policies Plain Push/Pull
combination with appropriate variations of flooding
Push with snooping directories combined with periodic pulls a novel variation of push, where agents that receive information about other moving agents maintain it for a short period of time
Inverted Cache with Leasingan informed push approach combined with leasing
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Plain push/pull method
Plain push
The moving agent does not know which agents need the update
It blindly floods the network with messages that contain its new location.
When an agent receives the push message: it updates its cache entries, if needed
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Plain push/pull method A wide push is needed to inform a sufficient number of agents
Large TTL and small decay
An agent may not receive the update because: Offline during push Push messages may not reach it
Larger TTL and decay values needed Disconnected network
Such agents should perform on-demand pull.
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Push with snooping directories and periodic pulling
How it works: An agent that receives a push message concerning other moving agents stores
this information in its own snooping directory It does so, even if it doesn’t need this information to update its own cache. Keeps it for a small period of time (expiration time)
So, each agent remembers the new location of every recently moved agent that came to its knowledge
Push with snooping directoriesEvery agent monitors the network and maintains a directory of recently moved agents. This directory is termed snooping directory.
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Push with snooping directories example
a1
Snooping dir-a1 moved to …
Snooping dir-a1 moved to …
Snooping dir-a1 moved to …
Snooping dir-a1 moved to …
Snooping dir-a1 moved to …
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Push with snooping directories and periodic pulling
All agents perform periodic pulls
Periodically, they search the network for agents in their cache that have recently moved and update the cache, if necessary
Why periodic pulling? To take advantage of the snooping directories:
if we pull after a long time, information about old moves might have already been deleted
Time between two subsequent pulls < expiration time of entries in the snooping directories
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Push with snooping directories and periodic pulling: Discussion
This method allows the use of narrower push/pull flooding Less message overhead
For example:
If agents pull periodically from their two-hop neighborhood: All the nodes that are two-hop away from push-informed agents will
eventually receive the update when they pull. So, it is sufficient to push-inform just one agent in each two-hop neighborhood
We prefer to use a k-walkers algorithm for pushing We spawn K-walkers and we require that all agents be two-hops
away from the walk-paths at the most
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Inverted cache push/pull
Every agent keeps a list of the agents to which it is known, called inverted cache.
When the agent moves, it informs the agents found in its inverted cache to update their plain cache in its plain cache to update their inverted directory
By knowing where to send the updates Avoid flooding Low message overhead
Drawback: When an agent adds/replaces/deletes a resource from its cache, a message has to be sent to the resource owner.
A B C A
B
C
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Inverted cache push/pull
IssueStoring the entire inverted cache directory may not always be preferable,
as there may exist popular agents/resources
Solution Only a limited directory may be maintained The inverted cache strategy can be combined with leasing
The agents that are not informed could use on-demand pull.
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Inverted cache push/pull: Leasing
Every entry in the cache gets a lease time issued by the resource owner
After the expiration the resource owner may delete the entry from its inverted cache, without ever informing the leaser
We could control the size of inverted cache directory through lease times Shorter lease times smaller inverted cache directories
Lease timeTime interval, during which the resource owner guarantees that it will notify the leaser in case the former moves.
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Experimental results Evaluation using a simulator
Create a random graph Each agent shares some resources Some resources (few) are more popular than others Initially, all agents have valid cache entries
The simulation runs for a number of turns: At each turn, an agent can
Move Search for a resource (on demand pull if necessary) Make a cache replacement etc.
We keep statistics Push/pull messages Percentage of valid cache entries Average directory sizes Number of steps needed for the update to propagate
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Simulation
There are 1000 agents owning 3000 resources. We run the simulation for 250 turns.
We are mainly interested in: The percentage of valid cache entries during the simulation The message overhead produced by
Pull Push Cache replacements
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Plain push/pull Extend of flooding and percentage of valid cache entries
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narrowmediumwidefull
decay TTL
narrow 0.4 4
medium 0.3 5
wide 0.2 5
full 0 5
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Plain push/pullExtend of flooding and message overhead
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Push with snooping directories and periodic pull Extend of flooding and percentage of valid cache entries
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Push with snooping directoriesand periodic pull Extend of flooding and message overhead
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Plain push/pull vs. snooping
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Inverted cache push/pullwith leasesLease time duration and percentage of valid cache entries
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smallmediumlargevery large
Lease time
small 5
medium 25
large 50
Very large 100
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Inverted cache push/pullReplace frequency and message overhead
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high medium low
Cache replacement frequency
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replacementpullpush
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Comparison Plain push/pull
Should be used only when we do not want to use any additional memory for cache update methods
Can be used in an unreliable environment (on-demand pull) Achieves satisfactory results when using wide flooding High message overhead: It should be avoided when we have high mobility
Push with snooping directories and periodic pull Achieves the same cache quality with plain push/pull but with significantly less
message overhead. Uses additional memory
Inverted cache with leasing Negligible push message overhead One-hop update propagation Replacing a cache entry requires contacting the resource owner
Unsuitable for systems with high replacement ratio. Directory size can become quite large for popular agents Not appropriate for unreliable open MAS
Agents rely on each other to be updated Agents must be online to maintain a valid inverted cache
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Conclusions We considered the problem of cache updates in a peer-to-peer network of mobile
agents Each agent maintains in its cache information about other agents When agents move, cached entries about them become obsolete
We propose a number of update policies that combine pull-based techniques, that are initiated by the agent that wants to update its cache push-based methods, that are initiated by the agent that moves.
Push/pull variations We propose a novel variation of push, where agents that receive information about other
moving agents maintain it for a short period of time in a snooping directory We propose an Informed push approach and we combine it with leasing (inverted cache)
Our experimental results designate Snooping directory leads to the attainment of the same cache consistency compared with
plain push/pull but with ten times less message overhead Inverted cache method is message-cost effective but only when cache replacements are not
too frequent
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Future work
Mobile agents resemble mobile (wireless) nodes in ad-hoc networks: apply our policies to message routing and resource discovery in these networks
File replicas in p2p systems apply our policies to keep replicas consistent