distributed computing (cs 515)csit.uob.edu.pk/images/web/staff/lecture/doc-6.2014-11... · 2015. 9....

Distributed Computing (CS 515)

Dr. Ihsan Ullah

Department of Computer Science & ITUniversity of Balochistan, Quetta

Pakistan

November 11, 2013

P2P Distributed Computing 1/91 1 / 91

Outline

1 Peer-to-Peer (P2P) networks

2 Unstructured P2P networks

3 Structured P2P networks

4 Application Layer Multicast (ALM)


Peer-to-Peer (P2P) networks

Outline






Peer-to-Peer (P2P) networks Introduction

P2P networks

Peer dictionary meaning: a person of the same age, status, or abilityas another specified person

A distributed network architecture may be called a Peer-to-Peernetwork, if the participants share a part of their own hardwareresources (processing power, storage capacity, network link capacity,printers, ...). These shared resources are necessary to provide theService and content offered by the network. They are accessible byother peers directly, without passing intermediary entities. Theparticipants of such a network are thus resource providers as well asresource requestors [Sch01]



P2P networks

Peer-to-peer systems are distributed systems consisting ofinterconnected nodes able to self-organize into network topologieswith the purpose of sharing resources such as content, CPU cycles,storage and bandwidth, capable of adapting to failures andaccommodating transient populations of nodes while maintainingacceptable connectivity and performance, without requiring theintermediation or support of a global centralized server or authority[ATS04]



P2P overlay

A virtual network over the physical one



Peer

A computer, an end-user, an application

Depends on the contextAlways an end system, but an end system is not always a peerAn end system can be a dedicated video server that is part of a CDN,or a BitTorrent client that is part of a P2P network



Peer

Leacher

A peer that is client and serverIn the context of content deliveryHas a partial copy of the content

Seader

A peer that is only serverIn the context of content deliveryHas a full copy of the content



P2P paradigm

Why P2P applications became popular in mid-2000 only?

High speed Internet connectionsPowerful end hostsThe End-to-end argument

End-to-end argument: a functionality should only be implemented ata lower layer if the achieved performance out-weighs the cost ofadditional complexity that occurs



P2P Applications

P2P applications capitalize on any resource from anybody

P2P applications can share CPU, bandwidth and storage

BitTorrent, EmuleSkypeSopCast, PPLive



Characteristics of P2P networks

Resource sharing: each peer contributes system resources to theoperation of the P2P system. Ideally this resource sharing isproportional to the peer’s use of the P2P system, but many systemssuffer from the free rider problem

Networked: all nodes are interconnected with other nodes in the P2Psystem, and the full set of nodes are members of a connected graph.When the graph is no longer connected, the overlay is said to bepartitioned

Decentralization: the behavior of the P2P system is determined bythe collective actions of peer nodes, and there is no central controlpoint. May require centralization for management such as login

Symmetry: nodes assume equal roles in the operation of the P2Psystem. In many designs this property is relaxed by the use of specialpeer roles such as super peers or relay peers



Characteristics of P2P networks

Autonomy: participation of the peer in the P2P system is determinedlocally, and there is no single administrative context for the P2Psystem

Self-organization: the organization of the P2P system increases overtime using local knowledge and local operations at each peer, and nopeer dominates the system

Scalable: a pre-requisite of operating P2P systems with millions ofsimultaneous nodes, and means that the resources used at each peerexhibit a growth rate as a function of overlay size that is less thanlinear. It also means that the response time doesn’t grow more thanlinearly as a function of overlay size

Stability: within a maximum churn rate, the P2P system should bestable, i.e., it should maintain its connected graph and be able toroute deterministically within a practical hop-count bounds



Classification of P2P networks

Two classes:

Unstructured

The overlay networks organize peers in a random graph in flat orhierarchical manners (e.g. Super-Peers layer)

Use flooding, random walks or expanding-ring Time-To-Live (TTL)search

Structured

the P2P overlay network topology is tightly controlled and contentare placed not at random peers but at specified locations that willmake subsequent queries more efficient

Distributed Hash Table (DHT)


Unstructured P2P networks

Outline







Introduction

Do not impose any structure on the overlay networks

Usually resilient to peer dynamics, and support complex queries

But they are not efficient for locating unpopular files

Depending on system decentralization level, unstructured P2Pnetworks can be classified into:

Centralized

Distributed

Hybrid

Other approaches



Design considerations

Search efficiency and replication cost:

Data are distributedly stored at peers and each peer only holds limitedinformation about the systemImportant to design efficient search mechanisms.With more data replications in the network, a data file can be locatedmore quicklyA tradeoff between storage cost and search time

Scalability:

A P2P system may consist of hundreds of thousands of peersOften requires a fully distributed system, where peers form aself-organized network and each peer communicates with only a fewother peers



Design considerations

Resilience:

In P2P systems, a peer may arbitrarily join, leave or failA good P2P system should be resilient to such peer dynamics

Load balancing:

Peers often have heterogeneous resource (e.g., bandwidth,computational capability, storage space)A good system should be able to achieve balanced loads among peersThis can avoid overloading of hot peers, and hence improve systemscalability

Security:

Some participating peers may be selfish and unwilling to upload datato others, or some may launch attacks to disrupt the serviceA practical P2P system should be well protected to targeted attacks orfree-ridersOther considerations include peers’ privacy and confidentiality


Unstructured P2P networks Centralized approach: Napster

Napster

Napster started in fall of 1999, created by Shawn Fanning

Napster was the first P2P file sharing application

Only sharing of MP3 files was possible

First lawsuit in December 1999 from several major recordingcompanies

Got 13.6 million users in February 2001

July 2001 judge ordered Napster to shut down

Current Napster is an online music store, not P2P



Napster: communication

1 A new peer registers with thecentral server and shares a listof files

2 A registered peer sends query tothe central server

3 The central server provides theaddress of the peer containingthe content

4 The content is downloaded fromthe peer directly



Napster: strengths

Consistent view of the network

Central server always knows who is there and who is not

Fast and efficient searching

Central server always knows all available filesEfficient searching on the central server

Answer guaranteed to be correct

Nothing found means none of the current on-line peers in the networkhas the file



Napster: limitations

Downloading from a single peer only

Central server is a single point of failure

Central server needs enough computation power to handle all queries

Results unreliable

No guarantees about file contentsServer knows nothing about local situation at peers (load)Some information such as user bandwidth entered by the user, notguaranteed to be correct (i.e., not measured)


Unstructured P2P networks Distributed Approach

Gnutella

A fully distributed P2P system for file sharing

Publicly available source code

Enables the development of different client softwares (LimeWire)

Gnutella peer is called servent (Server + client)

All peers are equal



Gnutella: network joining

A new peer joining first connects to some public peers (e.g. availableon a website)

Then it sends a PING message to any peer it is connected toannounce the existence of the new peer

A Gnutella peer returns a PONG message and propagates the PINGmessage to its neighbors

A PONG message contains IP address and port of the respondingpeer, and information of files being shared

Peer periodically sends PING messages to its neighbors



Gnutella: searching

Search in Gnutella is based on flooding, which is broadcasting in theoverlay

A search query is propagated to all neighbors from the originalrequesting peer

The query is replicated and forwarded by each intermediate peer to allits neighbors

Each intermediate peer also examines its local contents and respondsto the query source on a match

Peer periodically sends PING messages to its neighbors

A time-to-live (TTL) field to reduce the number of query messages

The TTL value is decremented by one at each peer, message isdropped on TTL=0



Gnutella: strengths

By contrast to Napster, Gnutella is a dynamic, self-organized network

Each peer independently connects to and communicates with a fewother peers in the system

The system is able to contain an unlimited number of peers, if noconstraint on search efficiency

The system is highly robust to peer dynamics

If a peer leaves the system, its neighbors can connect to other peersthrough the exchange of PING and PONG messages



Gnutella: limitations

Low search efficiency: the number of query messages exponentiallyincreases with the number of overlay hops

Then a query may generate many messages, especially for unpopularfiles

The use of TTL can reduce the number of query messages but,choosing an appropriate TTL is not easy

Mltiple copies of a query may be sent to a peer by its multipleneighbors


Unstructured P2P networks Hybrid approach

FastTrack/Kazaa

Given the limitations of purely centralized and distributed networks,this approach combines the two

In FastTrack, peers with the fastest Internet connections and themost powerful computers are automatically designated as supernodes

Other nodes are called ordinary nodes

A supernode maintains information about some resource as well asconnections with other supernodes

Exploitation of heterogeneity of peers and organization of peers into ahierarchy

Kazaa is based on FastTrack


Unstructured P2P networks Hybrid approach

Kazaa: Searching

A peer wanting to search some file, sends its query to the closestsupernode

The supernode either returns some matching peers, or forwards thequery to other supernodes

At some stage, a supernode will respond with some matching nodesfrom which it can download the file

As compared with purely distributed networks like Gnutella, Kazaaachieves much lower search time

In contrast to Napster, supernodes do not form a single point offailure


Unstructured P2P networks Other Approach: BitTorrent

BitTorrent

BitTorrent is a P2P system that does not belong to any of thementioned categories

Uses a central location to coordinate data upload and downloadamong peers

To share a file f , a peer first creates a small torrent file, whichcontains metadata about f , e.g., its length, name and hashinginformation

BitTorrent cuts a file into pieces of fixed size, typically between 64KB and 4 MB each

Each piece has a checksum from the SHA1 hashing algorithm, whichis also recorded in the torrent file



BitTorrent

The torrent file contains the URL of a tracker, which keeps track ofall the peers who have file f (either partially or completely)

A peer that wants to download the file, first obtains thecorresponding torrent file

Then, it connects to the specified tracker

The tracker responds with a random list of peers which aredownloading the same file

The requesting peer then connects to these peers for downloading

Torrent files are often published on large websites

Centralization of tracker is an issue



BitTorrent

The latest BitTorrent clients implement a decentralized trackingmechanism (e.g., µTorrent)

In this mechanism, every peer acts as a mini-tracker

Peers first join a DHT network, which is inherently implemented inthe BitTorrent client

A torrent is then stored at a certain peer according to the DHTstorage method

All peers in the DHT network can search for the torrent through DHTsearch

Eliminates central trackers from the system



BitTorrent: Tit-for-Tat and Chunk Selection

BitTorrent uses tit-for-tat policy

A peer serves peers that serve it

Encourages cooperation, discourage free-riding

Use rarest first policy when downloading chunks to maximizeavailability

For the first chunk, randomly picks any, so that peer has somethingto share


Structured P2P networks

Outline







Structured overlay

A network overlay that connects nodes using a particular datastructure or protocol to ensure that node lookup or data discovery isdeterministic

The P2P overlay network topology is tightly controlled and contentsare placed not at random peers but at specified locations that willmake subsequent queries more efficient

Addressing instead of searching

Network structure determines where peers belong in the network andwhere objects are stored



Distributed Hash Tables

Hash function:

hash(x) = x mod 10

Insert numbers 0, 1, 4, 9, 16, and 25

Easy to find if a given key is present inthe table




Hash tables are fast for lookups

Idea: Distribute hash buckets topeers

Result is Distributed Hash Table(DHT)

Need efficient mechanism forfinding which peer is responsiblefor which bucket and routingbetween them




In a DHT, each node isresponsible for one or more hashbuckets

As nodes join and leave, theresponsibilities change

Nodes communicate amongthemselves to find theresponsible node

Scalable communicationsmake DHTs efficient

DHTs support all the normalhash table operations



DHT summary

Hash buckets distributed over nodes

Nodes form an overlay network

Route messages in overlay to find responsible node

Routing scheme in the overlay network is the difference betweendifferent DHTs

DHT behavior and usage:Node knows object name and wants to find it

Unique and known object names assumed

Node routes a message in overlay to the responsible nodeResponsible node replies with object

Semantics of object are application defined


Structured P2P networks DHT case studies

DHT examples

Chord

Pastry

Tapestry

CAN

Kademlia



Chord: Introduction

Chord uses SHA-1 hash function

Results in a 160-bit object/node identifierSame hash function for objects and nodes

Node ID hashed from IP address

Object ID hashed from object nameObject names somehow assumed to be known by everyone

SHA-1 gives a 160-bit identifier space

Organized in a ring which wraps around

Overlay is often called Chord ring or Chord circleNodes keep track of predecessor and successorNode registers objects on the namespace between predecessor and itself



Chord: Joining

A 3-bit identifier space

Existing network withnodes on 0, 1 and 4

New node wants to join



Chord: Joining

New node wants to join

Hash of the new node: 6

Known node in network:Node1

Contact Node1(providing own hash)



Chord: Joining

Messages are representedthrough arrows

New node6 contactsnode1



Chord: Joining

Node1 forwards themessage to its successor(node4)



Chord: Joining

Node4 forwards themessage to its successor(node0)



Chord: Joining

Joining is successful

Old responsible nodetransfers data thatshould be in new node

New node informs Node4about new successor



Chord: Joining

After joining andtransferring the data



Chord: Storing a value

Node 6 wants to storeobject with name ”Foo”and value 5

hash(Foo) = 2



Chord: Retrieving a value

Node 1 wants to getobject with name ”Foo”

hash(Foo) = 2

Foo is stored onnode4



Chord: Scalable routing

Routing happens by passing message to successor

What happens when there are 1 million nodes?

On average, need to route 1/2-way across the ringIn other words, 0.5 million hops! Complexity O(n)

How to make routing scalable?

Answer: Finger tables

Basic Chord keeps track of predecessor and successor

Finger tables keep track of more nodes

Allow for faster routing by jumping long way across the ringRouting scales well, but need more state information

Finger tables not needed for correctness, only performanceimprovement



Chord: Finger tables

In m-bit identifier space, node has up to m fingers

Fingers are stored in the finger table

Row i in finger table at node v contains first node s that succeeds vby at least 2i−1 on the ring (namespace, not nodes!)

In other words:

finger [i ] = u : |u| >= |v | + 2i−1 mod 2m

Distance to finger [i ] is at least 2i−1



Chord: Scalable routing

Finger intervals increase withdistance from node n

Each node only storesinformation about a smallnumber of nodes

Example has three nodes at 0,1, and 3

3-bit ID space → 3 rows offingers



Chord: Finger table example

finger[1].interval =[finger[1].start,finger[2].start)Row entry: (n + 2r ) mod 2m [n=node id, r=row number starting from 0]



Chord: Performance

Search performance of “pure” Chord O(n)

Number of nodes is n

With finger tables, need O(log n) hops to find the correct node

Fingers separated by at least 2i−1

With high probability, distance to target halves at each step

For state information, “pure” Chord has only successor andpredecessor, O(1) state

For finger tables, need m entries



Pastry: Introduction

Pastry is a DHT-based P2P object location and routing substrate

Pastry assigns a 128 bit unique identifier to each node that joins thePastry network

The identifier is chosen by hashing the node’s IP address to create aNodeId

Keys are also selected from the same identifier space

The root node for a key is the node who’s NodeId is closest to thekey among all live nodes



Pastry: Routing

Each Pastry node maintains a routing state which consists of a leafset, a routing table and a neighbor set

The leaf set is the set of nodes with L/2 numerically closest largernodeIds and L/2 numerically closest smaller nodeIds

The routing table is a matrix with a/b rows and 2b columns

a is the number of bits in the nodeId and b is a parameter with atypical value 4

The entry in row r and column c of the routing table contains anodeId that shares the first r digits with the local node’s nodeId, andhas the (r + 1)th digit equal to c

If there is no such nodeId, the entry is left empty



Pastry: Routing

a = 8, b = 2 → L = 2b = 4 and M = 2b = 4



Pastry: Node joining

Newly joining node X knows a pastry node A

X asks A to route a “join” message with key = NodeId(X)

Message targets Z, whose NodeId is numerically closest to NodeId(X)

All nodes along the path A, B, , Z send state tables to X

X initializes its state using this information

X sends its state to concerned nodes


Application Layer Multicast (ALM)

Outline






Application Layer Multicast (ALM) P2P Video streaming

Video traffic trends

Due to the availability of broadband technologies and more powerfulpersonal computers, video traffic over the Internet has enormouslyincreased



Video streaming

Streaming is the transfer of media such as audio or video over a networkas a steady and continuous stream [HB05]

Video-on-Demand (VoD)

Receiver-driven

Users can request for any video, any time

Extended buffering

Live video streaming

Source-driven

Broadcasts the newly generated content

Limited buffering



Video streaming architectures

With router support

IP multicastScalability, security and lackof a business modelTelco-managed IPTV uses IPmulticastLimited to private networksand expensive

Without router supportWithout end-systems support (Centralized C/S, CDN)

Scalability and cost (Servers and upload bandwidth)

With end-systems support (P2P)



P2P live video streaming

End-hosts (peers) form aself-organizing network

Peers share their uploadbandwidth through relayingcontent to each other

Uses the existing IP infrastructure

Easy to deploy with low cost

Programmable end-hosts

Potentially scalable



Group managment methods

Isolated-channel systems

Build a separate overlay for each channel

Channel switch is departure from the overlay

Overlay highly dynamic, low peer population in less popular channels

Cross-channel systems

Allow peers watching different channels to exist in the same overlay

Peers also forward the streams they do not actually watch

Channel switch and low peer pooulation in less popular channels iscontolled

Management complexity and load



P2P live video delivery methods


Application Layer Multicast (ALM) P2P stream delivery methods

Single tree approach



Single tree approach

The simplest form of push-based protocols that build a separate treefor each group of users

The root node sends the stream to its children and the processcontinues up to the leaf nodes

Efficient in terms of timely delivery of the video content



Single tree approach: challenges

A low capacity peer, if placed at a high level in the tree, will impactthe QoS for the downstream users;

Loops must be avoided during the tree construction

Churn greatly impacts the performance of single tree systems, sincean abrupt departure or failure of a node disrupts the streamavailability to all its offspring peers;

A large number of leaf nodes cannot share their upload bandwidth,because they have no child peers

Example: Scribe, Narada



Scribe

An application-level multicast system that is built upon Pastry

To create a Scribe group, a random Pastry key known as ScribegroupId is chosen

Pastry routes a message for creating a multicast group towards thenode having a nodeId numerically closest to the groupId

That node becomes the root of the multicast group

Groups are managed in a fully decentralized way

Interested nodes become members of the group by routing a JOINmessage towards the root

The intermediate nodes that receive the JOIN message, add therequesting node as a child for the group and if currently, it is not themember of the group itself, it sends further a JOIN request towardsthe root



Scribe

Multicast messages are disseminated from the root towards the leafnodes forming a tree structure

The routing properties of Pastry ensure that the tree is loop-free

The children receive the implicit heartbeat messages from the parentswith the multicast data while the children send explicit refreshmessages to the parents to indicate their presence



Scribe



Multi-tree approach



Multi-tree approach

Forms several trees to disseminate a video stream

The source node splits the video stream into sub-streams and diffuseseach of them onto a separate tree

A video coding mechanism such as Multiple Description Coding(MDC) or Layered Coding (LC)

Example: SplitSteram



Multi-tree approach

One node can join all the trees to receive a full quality video or lessnumber of trees according to its capacity

A leaf node in one tree becomes the forwarding node in another tree

A node which is not a leaf node in at least one tree will share itsupload bandwidth

A low capacity node can contribute up to its potential

The failure or abrupt departure of a node only disrupts the availabilityof the substream it is forwarding to its descendants



Multi-tree approach: challenges

Peers dynamaics still an issue: the disruption of a substream impactsthe streaming quality

Maintaining multiple trees and the use of coding schemes put anextra overhead on the system



SplitStream

Builds multiple trees for one multicast group by using Scribe

Trees are interior-node-disjoint: a set of trees, in which each node isan interior node in at most one tree and a leaf node in all other trees

To do so, SplitStream creates trees in such a way that the identifierfor each tree, called the stripId, differs in the most significant digit

The source node divides the content into smaller parts called stripsand sends them on different trees

Peers interested in particular strips join the trees corresponding tothose strips

The failure or departure of an upstream peer causes the loss of onlyone strip for its downstream peers



Pull-based approach



Pull-based approach

In contrast to push-based systems the content delivery is controlledby receiver peers

Video stream is divided into smaller pieces, called chunks, and a peerpulls them from multiple neighbors at the same time

Each node in a pull-based system maintains a set of partners

Each node periodically exchanges its chunks availability informationwith its partners

Based on this information, a node decides to download the contentfrom one or more partners through an explicit request

Example: DoNet/CoolSteaming



Pull-based approach

Pros

Provide more resilience against peers’ dynamics because one peerreceives the content from multiple other peers at the same time

Each peer gets more chance to utilize its upload bandwidth byforwarding the content to other peers

Cons

The advertisement of chunks availability information, explicit requestfrom the receivers for data and packets delivery involves three roundsof communication for a group of packets to be delivered

Incurs delays and increases the communication overhead

Before advertising the availability of packets, a peer waits until anumber of packets are buffered, which causes further delays



DONet/CoolStreaming

A data-driven approach which means that the availability of datadecides its flow rather than a fixed structure

Each DONet node maintains a partner list to keep a partial view ofthe network and a member list to exchange data

To manage these lists and exchange data, each node has three keymodules: membership manager, partnership manager and thescheduler

The membership manager enables nodes to maintain a partial view ofother members

The partnership manager allows to establish and maintain thepartnership with other nodes for data exchange

The scheduler schedules video segments to be fetched from thepartners



DONet/CoolStreaming

A newly joining node, first contacts the origin node, and the originnode chooses a deputy node from its cache

The deputy node provides the list of member nodes

The new node can select its partners from this list

In a case of graceful departure, the departing node will inform itspartners of its departure

In a case of failure the partner node will detect the failure due to theabsence of buffer map message and will issue a departure message onbehalf of the failed node



DONet/CoolStreaming

DONet divides the video stream into segments and maintains abuffer, which can hold 120 segments

Each node continuously exchange its buffer’s information indicatingthe availability of segments with its partner nodes

This information is encoded within 120 bits called Buffer Map (BM),where a 1 shows the availability and a 0 shows the unavailability ofsegments

The scheduling algorithm schedules the segments retrieval from thepartner nodes based on the buffer map, bandwidth and response timeof the partners, and playback deadlines of the local node



Hybrid approach

Attempt to combine the resilience of pull-based and efficiency ofpush-based protocols

Each peer operates in both pull and push modes



Hybrid approach

Generally, a peer use pull mode for an initial period of time afterjoining and then subscribes to a particular peer that pushes thestream to it

During push operation, pull mode is also used to retrieve missingpackets

The push mode in these systems attempts to ensure the timelydelivery of the content while the pull mode provides resilience againstchurn

The challenge here is the choice of the node from whom to receivethe packets through push mode

A stable node, with a good upload contribution ?

Example: mTreebone, GridMedia



GridMedia

GridMedia is a P2P video streaming system incorporating the hybridpush/pull strategy for content delivery

Each GridMedia node operates in pull mode at startup

Afterwards, a node subscribes to pushing packets from a providernode for a specified interval of time

The choice of the provider node that will push packets is based on thetraffic received from a node in the previous interval

The probability that a node will be chosen as a provider through pushmethod is equal to the percentage of traffic received from that node

Meanwhile, the lost packets are pulled from the neighbors



GridMedia

To avoid the transmission of duplicate packets through push and pullmodes, both receiver and sender use the following mechanism

The receiver records the received packet with maximum sequencenumber and if it detects that a packet, whose sequence number lagsbehind from the recorded maximum sequence number by a specifiedthreshold, it pulls it from other neighbors

The sender keeps track of the packet with maximum sequencenumber pushed to a neighbor

If the sender itself receives a packet whose sequence number lagsbehind the recorded maximum sequence number of the pushed packetby some specified threshold, it does not push it to the receiver

The specified threshold at the receiver is kept greater than or equal tothe threshold specified at the sender to control duplication


References

Stephanos Androutsellis-Theotokis and Diomidis Spinellis.

A survey of peer-to-peer content distribution technologies.ACM Comput. Surv., 36(4):335–371, 2004.

Markus Hofmann and Leland R. Beaumont.

Content Networking: Architecture, Protocols, and Practice.Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 2005.

R. Schollmeier.

A definition of peer-to-peer networking for the classification of peer-to-peer architectures and applications.In Proceedings of the First International Conference on Peer-to-Peer Computing, P2P ’01, pages 101–102, Washington,DC, USA, 2001. IEEE Computer Society.


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