node lookup in p2p networks

Node Lookup in P2P Networks

Node lookup in p2p networks

• Section 5.2.11 in the textbook.• In a p2p network, each node may provide

some kind of service for other nodes and also will ask other node for service.

• The problem is to locate a node who provides the service I need.

• In our project there is a central server who assigns nodes to others.


• P2P networks may have a very large number of nodes, such that a single central server may not be able to handle.

• Besides, there are legal issues.• So, how to design lookup mechanism, such that I

can find the node providing the service I need?• For simplicity, let’s use the same model as in our

project – Each node may have some files, and the job is to find a node with the file I need.


• Any suggestions?• Ask the nodes in the network one-by-one?• Flood the network?


• Two costs you have to consider. – The lookup time– The number of messages sent

• Assume that there is only one node with the file I need, what is the cost for – Linear search?– Flood?– Are they any good?

The key idea

• There is really not so much you can do if the network does not have a structure.

• Introduce structure to the network. • Distributed Hash Table (DHT).

Chord

• Each node has a unique ID– By hashing its IP address by SHA-1 to get a 160-bit

ID.• Each file also has a unique ID, called key. – By hashing the file name by SHA-1 to get a 160-bit

ID.

Chord

• Successor of a key x or ID x. – Arrange the node as a circle. Start at x and travel

clockwise. The first (real) node you visit is the successor of F.

Chord

• successor(F) is the node in charge of telling other people where to get F.

• If a node has file F, he tells successor(F) that he has F.

• So, if you can find successor(F), meaning that the IP address of it, you are done.

Chord

• How to find successor(F)?• Any suggestions?

Chord

• You know your location on the circle. You know the location of successor(F) on the circle.

• If every node keeps the IP address of its neighbor on the circle, need to do a linear search.

Chord

• But you control what nodes should remember.• What do you want the nodes to remember,

such that your searching time is small and your number of message is small?

Chord

• What Chord does is this. – remembering the successors of m locations if the

node ID and key are m bits.

• Consider a node with ID k. The ith entry of his finger table is the IP address of the successor of k+2i mod 2m.

• Given this, how do you design the routing algorithm?

Chord

• Start with k as the routing point (RP). • If RP < F < successor(RP), successor(RP) =

successor(F) and you are done because you know the IP address of successor(RP).

• Else, let the next RP be the one in the RP’s finger table that is the closest predecessor of F. Repeat.

Chord

• Chord needs O(m) routing steps.• The reason is every time, roughly speaking,

the distance from the RP to the key is at least halved.– WLOG, suppose the current RP is 0, and F is

between 2i and 2i+1. So if there is at least one valid node between 2i and F, we will go to the first such point, distance is halved.

Routers

These high-end, carrier-grade 7600 models process up to 30 million packets per second (pps).

Lookup

• The table is learnt manually or through routing protocols, such as BGP or OSPF.

TCAM

• CAM: Content Addressable Memory. • CAM reads the data, and returns a list of

addresses where the data is stored, if it finds any.

• CAM searches the entire memory in one operation.

• TCAM: three states, 0, 1, or don’t care

TCAM

• A Priority TCAM IP-Routing Lookup Scheme, Po-Chou Lin and Chung-Ju Chang, Senior Member, IEEE

Switches

• After figuring out the next hop, need to send the packet to the next hop.

• The switches works in time slots. A large packet is divided into fixed length cells, cells are reassembled at the output.

N by N crossbar

• Usually, the switch is a crossbar. • An input can send at most one cell per time

slot, and an output can receive at most one cell per time slot.

• Consider unicast packets.

Output contention

• Consider an N by N switch. What if two input ports both have a cell to send to the same output port at the same time?

Buffers

• So, buffers have to be added to the switch. • You may have buffer at the input port, or at

the output port.• Which one is better?

Input Buffer Switch

• Modern switches are input-buffered. • Cells arrive at the input port, if cannot be sent

out, will be temporarily stored at the input buffer.

• How would you organize the buffer? FIFO?

Head-of-Line Blocking

• If simply using FIFO, you will have Head-of-line blocking.

• Consider the case when at input port 0, you have 23334. If some other input port gets grant to send to output 2, while no one is sending to output port 3, input port 0 is forced to go idle – no good.

• Throughput bounded 58%.• Any suggestions?

VOQ

• Organize the cells into Virtual Output Queues (VOQ).

• At each input port, you have N queues, one for each output.

• Coming back to the example, at input port 0, you have 3 non-empty queues:– 2– 333– 4

Problem?

• Now, every input port can potentially have cells to every output ports – How to schedule the transmission of cells?

Bipartite Matching

• Draw a bipartite graph, let the left side vertices be the inputs, let the output side vertices be the outputs.

• A left side vertex is adjacent to a right side vertex if this input port has a cell to send to the output port.

• Now, recall the constraint that an input port can send at most one cell, and the output port can receive at most one cell.

• Therefore, any schedule is a matching.

Maximum Matching

• Maximum Matching in bipartite graphs can be found in O(n2) time.

• But the schedule must be computed really really fast, in the order of 10ns.

Maximal Matching

• How about a really simple algorithm – just pick edges in any arbitrary order until no edges can be picked?

• How bad can this be, compared to the maximum matching?

Maximal Matching

• So, can we just run a maximal matching algorithm?

The algorithm being used

• The materials in following slides are from “The iSLIP Scheduling Algorithm for Input-Queued Switches” by Nick McKeown published in IEEE/ACM Transactions on Networking.

iSLIP Algorithm

The iSLIP Algorithm

• Achieves 100% throughput for some simple type of traffic.

node lookup in p2p networks

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