Post on 11-Jan-2016
Ofir IsraelGuy Paskar
An Internet TaleOnce upon a time..
Users unhappy (slow connection)ISPs unhappy (poor revenues)
Then came Broadband access...
And everybody were happy
The Villain arrivesP2P File-Sharing Applications (Kazaa,
eMule, BitTorrent, etc..)Users love it!
Good and free content, overnight downloadsISPs hate it!
Users using their entire linkInternet link utilization gone wildMore bandwidth costs more money!
But is it really a villain?Users love itDriving force for broadband adoptionIncreased revenues for ISPs
What should the ISPs do??
Some IdeasUser unfriendly ideas
Increase subscription cost
Volume-based pricing
Block/shape P2P traffic (priority for non-P2P packets)
User friendly ideasAcquire more BWNetwork caching
Today..Generally understand the problem – DONE! (?
)
Describe an analytical model to help us understand situation better
Describe one practical solution and it’s empirical results (Hint: it works)
Research Goals• Modeling framework to analyze interactions
between P2P File-Sharing users and their ISPs
• Basic insight about system dynamics• Used to evaluate different strategies to
manage P2P traffic
Meet the PlayersUser
Generates queries (P2P application finds the object and retrieves it)
Pays a subscription price, has QoS expectations
What’s popular, what’s notISP
Goal: TO MAKE MONEYSets subscription priceControls bandwidthInfluences P2P app behavior
System Settingn users inside
ISP
N users in the world
User-ISP ul., dl.
bandwidth
ISP-ISP ul., dl.
bandwidthUser generates queryGets a response from within the ISPOr from a user in another ISP
The Simple System ModelAverage query rate
Aggregate query
rate
Prob. P2P App.
locates object
Prob. Object is located
inside ISP
Unconstrained downloads from within the ISP
Model for “Internet to ISP”
link
System throughp
ut
Object retrieval prob. (QoS):
User Utility Function
Shape parameter
Object retrieval prob.
Subscription cost
Users subscribe only if:
Equivalently, if:
is the minimal service level acceptable by user i
Benefit Cost
ISP Utility Function
Revenues from subscribers’ fee
Cost per unit of BW
Fixed cost
ISP starts service only if:
Benefit Cost
Traffic LocalityProbability that there exists at least one
internal replica of object replicated r times in the system
Probability to download from internal replica
Number of files inside ISP
Number of files outside ISP
Locality parameter
Minimum BWReminder:
So:
Assuming
We get
Minimum BW
Non-linear behavior (on n)More users more locality less BW neededCan be zero if n large enough (self-
sustainability)
Dependant on multiple parameters
Self-Sustainability
Simple(?!) Model
Impact of Object Replication (r)
More replicas Better locality Lower Bd neededBmin has two roots: x1 – No users, x2 – Enough users for
self-sustainability
Impact of external QoS) (
Higher external QoS More BW needed (because there are more replicas externally)
Impact of prob. to locate objects (q)
Some ISPs drop queries. This graph shows them different.
Impact of prob. to retrieve objects internally (Gamma)
Det. by the ability to find a local object given that it exists.Can be influenced by the ISP – this graph shows it should.
Model RefinementsSimple Model
Users’ access BW are unconstrained
Object popularity is identical
Users availability identical
Refined ModelRelax these
assumptionsPropose object
popularity and replication model
Model RefinementsWe adopt a processor sharing model with
rate limit bd to describe the sharing of Bd
Now each user is limited by it’s own
BW.Queue Model
Model RefinementsWe introduce a new parameter: that
describes user patienceDenote b as the initial download rate, and
assuming the decision to abort is made at the beginning then the prob. pg to continue the transfer is:
Larger eta user claims to get a rate close to what they paid for
Bmin as a function of bd=bu with different values of gamma
Higher gamma smaller bu needed for self-sustainabilityOptimal gamma is not gamma=1 !!!For bu < 250 the BW available inside the ISP is not enough
to satisfy demanding users
Impact of asymmetric access BWs
Cost for ISP increases as ratio increases (what about ADSL??)
Larger bu Better locality lower Bd
ConclusionsLocality is good for the ISPs
More replicas, larger querying probability, larger upload bandwidth for users’ access, larger probability to retrieve objects internally (gamma) SELF SUSTAINABILITY == GOOD
Reading slow leads to better understanding
Further ReadingOriginal paper of course:
Garetto et al, “A modeling framework to understand the tussle between ISPs and peer-to-peer file-sharing users” in Performance Evaluation, June 2007
Same as the original paper but talks about ISP-ISP connections:Wang et al, “Modeling the Peering and Routing Tussle between ISPs and P2P Applications” in the proceedings of IWQoS 2006
BREAK?
Academic WorkOracle-based vs. non-Oracle-based (e.g., with
ISP cooperation or without)Legality issues, reluctance issues
Improvements via locality researchNetwork location or Geographic location?Which method of network location?
Improvements via redirection researchCan we redirect traffic to inexpensive links?
Many more
Part 2
Taming the Torrent - A Practical Approach to Reducing Cross-ISP Traffic in Peer-to-Peer Systems
David R. Choffnes and Fabián E. Bustamante
The problem Over 66% of P2P users & growing But how do we know which peer to
choose? Which peers? Trackers provide a
random subset of peers in the torrent Random peer connections → growing ISP
operation costs. So , how do we know if a suggested peer is
inside our Isp or outside? We want to reduce cross isp transport.
Meaning use the “closest” peers. But , how can we do that?
The ISP PerspectiveP2P performance - key factor for service
upgrade & selection by usersA major engineering challenge for ISPs
≈70% of the Internet trafficBut , a lot of cross isp ,means a lot of cost for
the Isp.What can the isp do in order to fight the p2p
users?
Isp methods and its problemsISPs shape traffic directed to standard ports
P2Ps move to dynamic, non-standard portsISPs turn to deep-packet inspection to identify
& shape P2P flowsP2Ps encrypt their connections
ISPs place caches and/or spoofs TCP RST msgsLegality issues. (Some ways to overcome this – in
Israel!)
So good solution must be agreed by the p2p users!
One solution: Oracles.Suggestion – the isp’s itself will have to
implement an oracle, this oracles will guide the user which peers to choose. Help reduce cross-ISP traffic
This solution looks appealing But: Assumes P2P users & ISPs trust each other Misses incentive for user adoption Therefore not so good after all
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The authors suggestion
How does CDN work?There are some ways that a CDN works by
for example:Way 1 : I want to go to cnn.com dns lookup
, directs me to the domain name of the CDN (cnn.akamai.com) CDN sends me to the right replica.
Way 2: I want to go to cnn.com dns lookup first page from original cnn.com, directs me to CDN server sends to right replica.
Reusing CDNs’ network views Client’s request redirected to “nearby” server
Client gets web site’s DNS CNAME entry with domain name in CDN network
Hierarchy of CDN’s DNS servers direct client to nearby servers
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Internet
Web client
Client requests translation for Yahoo
Client gets CNAME entry with domain name in
Akamai
(3)
Hierarchy of CDN DNS servers
Customer DNS servers
(1)
(2)
(4) (5
) (6)
LDNS
Web replica servers
Multiple redirections to find nearby edge servers
Another web client
Client is given 2 web replica servers (fault
tolerance)
Clients and replica servers are “nearby]”
The authors suggestionSo how do we use CDN?We are going to recycle data that is already
being collected by Content Distribution Networks, and use it.
But how? By simply comparing DNS redirections.Assumptions :
Links between “nearby” hosts cross few ISPs
If two hosts are close to the same CDN replica servers, they are close to each other
Reducing cross-ISP trafficSo we can use the CDN’s data, what are the
advantages for this recycilng? Does not requires any trust between isp and
p2p usersThe infrastructure is already existAnd most importantly reduces cross isp traffic
without harming the p2p users (even improving)
An approach to reducing cross isp
Ratio MapsA ratio map represents the frequency of
redirecting to a specific replicaNumber of replicas is usually small (max 31)Keep a time window about 24 hoursHow does it looks?
Ratio maps represantation The ratio map of a peer (a) is a set of (replica
server, ratio) for peer a Specifically, if peer a is redirected toward
replica server r1 75% of the time window, and toward replica server r2 25% of the time window, then the corresponding ratio-map is
The sum of all in a given ratio map equals one
For each peer there exist a ratio map But what can we do with it?
choosing peers by ratio map2 peers has close ratio map , than we say
that they are close. ( possibly in the same network), and the ooposit
So , we need a calculation that will determine for 2 peers if they are “close” or not. Than we can check for all available peers and
choose the “closest” one For that we define cosine similarity for 2 peers
Cosine-similarity
the cosine similarity of two maps will range from 0 to 1, since the term frequencies cannot be negative
If cos_sim(a,b) = 0 , the vectors are orthogonal
if cos_sim(a,b) = 1 than they are the same
This is very close to dot product
And we determine a threshold currently 0.15 , if cos_sim(a,b)>0.15 than we recommend these peers as close
Implementation Ono, an extension to Azureus clientPerforms periodic DNS lookups on popular
CDN and create a ratio map Periodically updates the ratio-maps
Exchanging ratio maps for cos-sim(a,b): On Handshake From trackers But how do we deal with peers not using Ono?
Ono also attempts to perform DNS lookups on behalf of other peers that it encounters, to determine their ratio maps
How? Taken from Ono code : getting the other peer DNS
server And querying it
So what's now? Get ratio information from other peers that got
from tracker , and understand who is close When determine similar redirection behavior,
attempts to bias traffic towards that peer by ensuring that the connection is always on
Sends Ono information to supporting trackers(in case of supporting trackers)
But what is the cost? How much is our overhead? 18KB upstream, 36KB downstream per day Computation of cosine-similarity is easy
Important notesCDN names being used:
Initialization of ratio map:DNS on each CDN name at most once every 30
sec. for 2 min. this gives basis ratio mapAfter this phase
If the redirection info for CDN name similar to prev. query the interval between queries increases by 1 min.
Otherwise the interval is halved(to a min. of 30 sec.)
Some statistics regarding Ono Details for 2007 : > 195,000 users worldwide… collecting ~15GB of data per day
Empirical resultsOver 120,000 peers use OnoOno collects extra network data
Samples transfer rates for each connection every 5 sec.
Get RTT for endpoint using pingsGet Trace-route between end points
Note : Not easy to determine cross-ISP hops IP hops is easy and gives some measure
Empirical resualts So in practice Trace Route gives a router level views
of path between hosts. BUT an ISP can contain many routers, we wish for a metric that is closely correspond to ISP hops.
How do we get this metric? Autonomous systems , how? Although there is no 1 to 1 correlation between AS
and ISPs, the number of AS hops gives us an upper bound estimate on the number of cross-ISP hops
So in practice we generate AS level path info from our trace-routes using mapping that can be provided
Example :
Example
Empirical results
Ono finds shorter paths Median in less than half More than 20%
are only one hopaway, via less than 2%
Reducing cross-ISP trafficAverage number of AS hops to reach
Ono-recommended/random peers
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>30% of paths to Ono-recommended peers do not leave
the AS of origin
Note BT curve includes all peers, either Ono-recommended or
randomly selected
Finding nearby peers
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Two orders of magnitude difference
And, on average, 31% lower loss rates!
Improving transfer performance
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Heavy Tail – Average performance improves by 31%
Median difference is ~2KB/sEven when Ono doesn’t help, it allows BT to naturally select faster peers
DSL in England -- 4/8Mbps down, only 768Kbps up
ISP bandwidth allocation policy brings bottleneck to the access link
…with the right bandwidth allocation policyRomania: 50 Mb/s in metro-area, 4
Mb/s outside
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883% median improvement
Helpful ISPs can help themselves
57
DuscussionAbsolute network positioning system , and just
throw away the “far” peersProblem – all peers must take a part in the
service, in contrast to our method
Use just AS numbersThere are ISPs (like comcast) that have many AS
numbers, so using these numbers can restrict cross-AS traffic that is not cross-ISP traffic
Conclusion Recycling network views collected by CDNs
The method reduces cross-ISP trafficPerformance of peers is not effected(we saw
this)Scalable (the more clients adopt it, the more
accurate the bias would get)Available easily and freely
Therefore the method is good and can provide good results in reducing Cross-ISP traffic
QuestionTBD
Extras