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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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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Pull search example

Old location

New location

Agents knows the new location

Agent that pulls

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Pull search example

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Pull search example

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Pull search example

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Pull search example

Replies Directly

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Pull search example

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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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Push example

New location

Needs the update

Needs the update

Needs the update

Old location

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Push example

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Push example

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Push example

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Push example

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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

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Push with snooping directories example

Snooping dir-a1 moved to …

Snooping dir-a1 moved to …

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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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Push with snooping directories

Changed location

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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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decay TTL

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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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Inverted cache push/pullReplace frequency and message overhead

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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

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Thank you

More detailswww.cs.uoi.gr/~ilias/dcache/