Download Decentralized Location Services

Ongoing Work on Peer-toPeer Networks
May 25, 2017
Prof. Ben Y. Zhao
ravenben@cs.ucsb.edu
Large-scale Network Applications
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Context
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trend: applications increasing in scale (clients, distribution)
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examples: wide-area real-time multicast (PayPerView), data
dissemination (PointCast), large distributed FS
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mutual sharing of data, inter-node communication
Challenges as networks scale
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how does A find a particular piece of data?
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start with simple name (complex queries later)
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how does node A send message to B?
IP addresses are too static, need app-level location independent names
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how do we make communication reliable?
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
2
Adding Name-based Structure to Networks
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No network structure
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any node can connect to any node: flexible
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scalability issue: too many routing table entries
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need more flexible naming, IP address too static
Trade off flexibility for scalability
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name all nodes with application level nodeIDs
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route incrementally to destination
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use nodeID as measure of routing progress
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
3
Outline
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Motivation
Protocols
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routing: Chord, Tapestry/Pastry, etc…
dynamic algorithms
Application Interfaces
Ongoing Work
Wrap-up
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
4
Structured Peer-to-Peer Overlays
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Assign random nodeIDs and keys from secure hash
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incrementally route towards destination ID
each node has small set of outgoing routes, e.g. prefix routing
ID: ABCE
ABC0
To: ABCD
AB5F
A930
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
5
What’s in a Protocol?
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Definition of name-proximity
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Size of routing table
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worst case routing performance (in overlay hops, not IP)
Network locality
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amount of state kept by each node as f (N), N = network size
# of overlay routing hops
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each hop gets you “closer” to destination ID
prefix routing, numerical closeness, hamming distance
does choice of neighbor consider network distance
impact on “actual” performance of P2P routing
Application Interface
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
6
Chord
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NodeIDs are numbers on ring
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Closeness defined by numerical
proximity
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Finger table
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keep routes for next node
namespace
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routing table size: log2 n
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n = total # of nodes
0
2i
away in
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iterative hops from source
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at most log2 n hops
128
896
256
768
Routing
Ongoing work in P2P Networks
Node 0/1024
640
384
512
ravenben@cs.ucsb.edu
7
Chord II
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Pros
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Cons
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simplicity
limited flexibility in routing
neighbor choices unrelated to network proximity
* but can be optimized over time
Application Interface:
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distributed hash table (DHash)
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
8
Tapestry / Pastry
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incremental prefix routing
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Node 0/1024
0
routing table
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11110XXX00XX
000X0000
128
896
keep nodes matching at least i
digits to destination
256
768
table size: b * logb n
routing
640
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recursive routing from source
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at most logb n hops
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
384
512
9
Routing in Detail
Example: Octal digits, 212 namespace, 2175  0157
2175
0880
0123
0154
0157
0 1
0 1
0 1
0 1
0 1
2
2
2
2
2
3 4 5
3 4 5
3 4 5
3 4 5
3 4 5
Neighbor 2175
Map
For “2175” (Octal)
6 7
6 7
6 7
6 7
6 7
0xxx
20xx
210x
2170
1xxx 0880
----
211x
2171
----
22xx
212x
2172
3xxx
23xx
213x 0123
2173
4xxx
24xx
214x
2174
5xxx 0154
25xx
215x
----
6xxx
26xx
216x
2176
7xxx
27xx
----
2177
0157
4
3
2
1
Routing Levels
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
10
Tapestry / Pastry II
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Pros
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Cons
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large flexibility in neighbor choice
choose nodes closest in physical distance
can tune routing table size and routing hops using
parameter b
more complex than Chord to implement
Application Interface
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Tapestry: decentralized object location
Pastry: distributed hash table
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
11
Lots and Lots of Protocols
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Other designs: Kademlia, Coral, etc…
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For network locality
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SkipNet / Skip graphs
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LAND
For theory
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Viceroy (dynamic adaptation of butterfly network)
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Symphony
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Ulysseus
For performance
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One-hop / Two-hop Routing (static hierarchy)
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Brocade (two layered approach for WAN routing)
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XRing / ZRing
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
12
Questions?
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
13
Outline
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Motivation
Protocols
Application Interfaces
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distributed hash tables
decentralized object location
multi-tiered interfaces
Ongoing Work
Wrap-up
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
14
How Do We Use Them?
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Key-based Routing layer
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Large sparse ID space N
(160 bits: 0 – 2160 represented as base b)
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Nodes in overlay network have nodeIDs  N
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Given k  N, overlay deterministically maps k
to its root node (a live node in the network)
Main routing call
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route (key, msg)
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Route message to node currently responsible for key
Leveraging KBR
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storage: pick a node by name to store data
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routing: route messages between nodes by nodeID
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
15
Storage: Distributed Hash Tables
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P2P layer = a hash table
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write (key, data)
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key is object ID
store data at k nodes closest in name to key
k is system parameter (replication factor)
data = read (key)
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read data from any of k nodes close to key
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
16
DHT II
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Pros
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simplicity, just store and forget
rely on storage layer to keep data available across changes
in node membership
servers generally distance in network and faultindependent
Cons
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P2P layer controls parameters
where data is stored, how many replicas
one size rarely fits all
lack of network locality
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
17
Storage: Decentralized Object Location
routeobj(k)
routeobj(k)
backbone
k
publish(k)
k
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let application choose where to store data
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P2P layer provides directory service to locate objects
redirect data traffic using log(n) in-network redirection pointers
ravenben@cs.ucsb.edu
average # of pointers/machine:
log(n) * avg files/machine
Ongoing work in 
P2P Networks
18
DOLR II
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Pros
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application has control over data placement
can optimize location, replication factor for
performance
Cons
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directory pointers require state in network
additional complexity in managing data
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
19
Outline
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Motivation
Protocols
Application Interfaces
Ongoing Work
Wrap-up
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
20
Many Structured P2P Applications
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Data storage
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Search on P2P
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service discovery, P2P databases
Routing
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file systems, FS backup, stegnographic FS
Web Caches, CDNs, DNS services
application-level multicast, pub/sub
resilient routing tunnels
Others
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spam-filtering, collaborative network measurement,
machine fault diagnosis
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
21
But Few (if any) Are Deployed
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Deployment outside of research networks
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Consider some factors
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still file-sharing based (Kenosis/BitTorrent, E-Donkey)
Why? Is P2P only good for file-sharing?
killer app with real user demand
usability (software engineering)
incentives vs. per user cost
security
How do we do about this?
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
22
Addressing P2P Security
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The problem
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lots of users, spread over wide-area, multiple network domains
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no uniform security policy or management capability
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result: expect compromised nodes in normal operation
Existing work
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secure routing: trade off efficiency for improved resilience against collusion
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prognosis is bleak
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one against many (colluding attackers)
An alternative
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balance the scale: many against many
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form trusted groups to collaboratively stave off attackers
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incrementally build trust groups with anonymous verification
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
23
P2P Security cont.
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Mechanisms
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highly dynamic collaborative reputation system
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anonymous communication in P2P
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todo
under development: Cashmere
Policies / algorithms
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how to perform anonymous verification
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how to derive / adapt online reputations
A related topic
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what are the weaknesses of current P2P systems
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what are the main methods of attack?
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how do we perform / protect against these attacks?
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
24
Finding the Right Incentive/Cost Model
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Deployment
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current focus on infrastructure services
need useful, light-weight apps for home users
Design and implement Quartz
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lightweight p2p data sharing system
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store your most critical files (<100MB) online
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use simple application-specific handlers to provide fast data
synchronization (a la CVS)
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synchronize your HTML bookmarks across machines
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synchronize your papers, homework files, financial records
end to end encryption
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
25
Other Directions
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Understanding unstructured P2P systems
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understanding content-based centralization and its
implications
edge-based measurements of Freenet
studies of Maze, an academic P2P system from China
More P2P applications
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Reliable and efficient event propagation
(large-scale distributed gaming)
P2P Ebay, (secure online commerce)
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
26
Other Directions cont.
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Applying decentralized algorithms elsewhere
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routing and data management in sensor and ad-hoc
networks
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reduce routing state and flooding traffic
energy efficient data aggregation in sensor nets
spectrum allocation and MAC-layer device coordination
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
27
Outline
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Motivation
Protocols
Application Interfaces
Ongoing Work
Wrap-up
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
28
Finally…
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Structured Peer-to-Peer Networks are useful (& fun)
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holds promise for self-maintaining decentralized networks at Internet
scales
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relevance to numerous areas in CS
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sensor networks, ad-hoc routing, security, theory
For more information …
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see the webpage for my Winter 290
http://www.cs.ucsb.edu/~ravenben/classes/290F

see papers from IPTPS:
http://iptps05.cs.cornell.edu/
http://iptps04.cs.ucsd.edu
http://iptps03.cs.berkeley.edu
Ongoing work in P2P Networks
ravenben@cs.ucsb.edu
29