A RESOURCE DISCOVERY STRATEGY FOR MOBILE

PEER-TO-PEER NETWORKS

Hao Wu, Chao Cheng and Zhangdui Zhong

State Key Laboratory of Rail Trafﬁc Control and Safety, Beijing Jiaotong University, 100044 Beijing, China

Keywords:

Mobile P2P, Resource discovery strategy, M-Tapestry.

Abstract:

Resource discovery is one of the key issues in mobile P2P studies. Nonetheless, in existing schemes there

are still some deﬁciencies, such as the lake of ﬂexibility, proportionality and adaptability. In this paper, we

present a resource discovery model Mobile-Tapestry (M-Tapestry) for mobile P2P networks based on the P2P

Tapestry strategy. The philosophy of this model is to make the network architecture layered , and only a

small number of super nodes are chosen instead of all nodes to access the Tapestry system. This measure

may reduce the cost of ordinary nodes and solve the reliability problems caused, when the routing table is

updated frequently. Additionally, we partition the nodes according to their geographical location, this may

avoid the problem that the distance between the nodes having adjacent IDs is actually large due to the Hash

operation. Finally, our simulation results and analysis shows that the M-Tapestry strategy has an improved

lookup efﬁciency for mobile P2P networks compared to the Tapestry strategy.

1 INTRODUCTION

With the rapid development of mobile Internet ap-

plications, researchers started to pay attention to us-

ing P2P technologies in the mobile environment. Re-

source discovery strategy is one of the key issues for

mobile P2P (MP2P) applications (Ponmozhi and Ra-

jesh, 2009; Voitenko, 2009; Tianhao and Nikolaidis,

2004). However, due to the difference between the

mobile and Internet transmission environment, band-

width limitations, node mobility, and multi access in-

terference pose unique challenges to deploying the

existing P2P technologies in MP2P networks. There-

fore they must be improved in MP2P applications.

In the current researches, (Andersen et al., 2004)

built a Mobile eDonkey network for 3G networks

based on extending the Internet eDonkey system.

Similarly, (Hossfeld et al., 2005; Bakos et al., 2003;

Cramer and Fuhrmann, 2005) proposed a type of

eDonkey solution which may be used for mobile op-

erational networks with some improvements. Its ba-

sic idea is to make use of the resources in one mobile

network operator as far as possible, hence it could li-

minit the network trafﬁc mainly occurred in the local

network.

Distributed Hash Table (DHT) is another type of

distributed resource discovery strategy, CAN (Rat-

nasamy et al., 2001), Chord (Stoica et al., 2003), Pas-

try (Rowstron and Druschel, 2001), Tapestry (Zhao

et al., 2001) are typical structured P2P system. Some

researchers took into account these strategies used in

MP2P networks, for examples, in (Peng et al., 2004)

the authors proposed an improved CAN lookup pro-

tocol M-CAN which introduced the concept of su-

per node. (Musolesi et al., 2005) studied the scheme

that using Chord Ring structure to organize nodes and

route between nodes in wireless sensor networks, and

also gave the experiments of this scheme. (Pucha

et al., 2004) proposed Ekta which integrates a DHT

with a multi-hop routing protocol based on geo-

graphic location, Ekta divides a mobile P2P network

into many subareas with the same range, each one is

responsible for a series of hash key values. (He et al.,

2005) proposed a P2P video streaming sharing strat-

egy in the the mobile network environment by taking

the access point (AP) as a resource index.

In this paper, considering that Tapestry is an ideal

resource discovery strategy for its low space complex-

ity and lookup complexity compared to other strate-

gies, we propose a Tapestry-based, efﬁcient, ﬂexible,

high-dynamic resource discovery strategy “Mobile-

Tapestry” (M-Tapestry) and discuss the performance.

The rest of this paper is organized as follows. In Sec-

tion 2, we present the M-Tapestry system model and

propose a resource discovery protocol for mobile P2P

networks; In Section 3, we give the lookup efﬁciency

Wu H., Cheng C. and Zhong Z. (2010).

A RESOURCE DISCOVERY STRATEGY FOR MOBILE PEER-TO-PEER NETWORKS.

In Proceedings of the International Conference on Wireless Information Networks and Systems, pages 42-46

DOI: 10.5220/0002987200420046

 SciTePress

performance simulation and analysis of proposed M-

Tapestry strategy ; Section 4 concludes the paper.

2 SYSTEM MODEL

The resource discovery strategy, M-Tapestry, present

in this paper for mobile P2P networks is based on

the Tapestry, a existing discovery model for P2P net-

works. Tapestry (Zhao et al., 2001) is a Plaxton-

based distributed query algorithm system, resources

and nodes are both identiﬁed with the GUIDs (Glob-

ally Unique Identiﬁer), which are unrelated with the

location and contents and are determined randomly.

Tapestry model has the advantages of low complexity

and balanced load, consequently it is more suitable

to be applied in the mobile P2P networks. On the

other hand, the disadvantage is that the node mainte-

nance overheads for neighbor mapping table is very

heavy, because nodes join and leave the network fre-

quently in the mobile P2P environment, moreover it

will lead to system instability. Therefore, this paper

designs a M-Tapestry model for mobile P2P networks

combined with the ideas of (Peng et al., 2004) and

(Pucha et al., 2004). M-Tapestry model ﬁrst partitions

some subareas according to node geographical loca-

tion, and introduces the concept of super node, which

may take charge of the routing information mainte-

nance. Whereas the shared resource information is

maintained by the ordinary nodes, moreover it can

reduce the communication overheads, and improve

bandwidth efﬁciency and the lookup speed.

2.1 M-Tapestry Basic Idea

M-Tapestry is layered with two types of nodes: super

nodes and ordinary nodes (Peng et al., 2004). The su-

per nodes constitute the higher layer of the network,

those nodes with high performance are chosen to be

super nodes, such as with a high computing capacity

and stability, good reliability, etc. In mobile P2P envi-

ronment, sink nodes and part of the Internet terminals

can be looked as super nodes, because they are very

important to the entire network. The rest of nodes are

treated as ordinary nodes, which constitute the lower

layer of the network. The super nodes are managed

through Tapestry routing protocol, and the ordinary

nodes are directly registered to the super nodes. M-

Tapestry gives full consideration to the network phys-

ical architecture. Those ordinary nodes controlled by

the super nodes can be divided into groups by geo-

graphical characteristics (Pucha et al., 2004), which

can ensure ordinary nodes have less hops to the su-

per node, and avoid the problem that the adjacent ID

nodes is actually located a far distance due to the hash

operation.

Super Node ID=1 Super Node ID=2

Super Node ID=3

Peer ID=11

Peer

ID=21

Peer

ID=31

Peer

ID=41

Peer

ID=12

Peer

ID=22

Peer

ID=32

Peer

ID=13

Peer ID=23

Peer

ID=33

M-Tapestry System Architecture

Figure 1: The system architecture of M-Tapestry.

The architecture of M-Tapestry model is shown in

Figure 1. Supposed that super nodes are distributed 1

bit for Super Node ID, according to the geographical

characteristic, each super node takes charge of man-

aging the registered resources of nodes in a subarea

range. Resource IDs can be obtained through the hash

digest. The routing between super nodes is completed

by means of Tapestry model.

M-Tapestry model involves the following terms:

• Super Node ID: Super node identiﬁer;

• Peer ID: Ordinary identiﬁer. Peer ID = Peer

ID(preﬁx)+ Super Node ID, and Peer ID (preﬁx)

can be randomly obtained;

• Object ID: Shared resource identiﬁer.;

• Message ID: Message identiﬁer;

• Root ID: Root identiﬁer, for each shared re-

source object, M-Tapestry allocates a relevant

node, which called the root of the resource, root

(objectID) = the Peer ID closest to the object ID;

• Server ID: Server identiﬁer. Server ID has been

introduced to allow for routing more easily in M-

Tapestry system.

2.2 M-Tapestry Routing Mechanism

In M-Tapestry system, routing between super nodes

is accomplished according to Tapestry routing mech-

anism, each super node maintains a table of node reg-

istered resources within a certain subarea range and

a mapping table for its neighbor super nodes in ac-

cordance with the routing hierarchy. Meanwhile each

super node also maintains a back pointer list, which

points to those nodes who look itself as a neighbor.

During routing period, the super node looks up the

level of neighbor mapping table in turn, and routes

the data as far as possible by matching a larger preﬁx,

until it arrives the destination super node.

A RESOURCE DISCOVERY STRATEGY FOR MOBILE PEER-TO-PEER NETWORKS

When the Server Node S plans to release a shared

resource O, it ﬁrst sends a “registered” message to

its Super Node S

, which includes the information of

node Server ID and Object ID (GUID is O

). S

re-

ports that there is a resource O saved in S through

sending a message to the Super Node S

periodically,

is the registered super node of resource O’s root

node O

. S

forwards it and informs the root node O

that Node S contains the resource O, each super node

in this release route stores the resource O’s location

information pointer < O

, S >, where the location in-

formation is only a pointer pointing to S, rather than a

copy of the object O.

When the Client Node C needs to request a re-

source, it ﬁrst sends a “resource request” message to

its Super Node S

, which includes the information of

node Peer ID and the requested resource Object ID.

sends a “lookup” message to the Super Node S

which is the registered node of root node, if a super

node in the lookup route has the requested resource

location information, it will directly turn to the Super

Node S

which is the registered super node of Server

Node, and then the Client Node requests a copy of re-

source from the Server Node through the Super Node

; Otherwise, the message ﬁnally reaches the Root

Node through the Super Node S

, it can get the loca-

tion information pointer of resource O, then the Client

Node C may connects to the Server Node S and down-

load the resource.

As shown in Figure 2, it illustrates a description

of the actual routing process. Each super node is as-

signed a Super Node ID number, and maintains a re-

source table of registered nodes, in which the node ID

number and the registered resource information are

included. When the node with Peer ID = 0000 re-

quests a resource with Object ID = 0111, it ﬁrst sends

a RootToObject request message to its registered su-

per node with Super Node ID = 00, which includes

Object ID and Peer ID information. Receiving this

message, super node analyzes the information of Ob-

ject ID and gets to know its registered super node is

with Super Node ID = 11, because these information

are contained in the message RootToObject. The mes-

sage is forwarded by Tapestry routing in the network

between super nodes, which is easy to arrive the super

node with Super Node ID = 11. Super node with Su-

per Node ID = 11 looks up its own resources table of

registered nodes, and transmits message to the node

with Peer ID = 0111, node with Peer ID = 0111 re-

turns the Server ID information corresponding to Ob-

ject ID = 0111 through its own stored information,

that is to respond Server ID = 1101. The super node

with Super Node ID = 11 returns “Server ID = 1101”

to the super node with Super Node ID = 00, then super

node with Super Node ID = 00 forwards this message

to the client node with Peer ID = 0000. Receiving this

message, the client node with Peer ID = 0000 sends

a request to the server node with Peer ID = 1101 for

resource information, the server node with Peer ID =

1101 returns the copy of Object ID = 0111. Thus, this

resource discovery process is completed.

In this example, only one Server ID has been re-

turned, whereas in practical process, when the mes-

sage forwarded to the node with Super Node ID =

11, it is possible that the Server ID information of the

Object ID is found, then it returns the Server ID di-

rectly without ﬁnding the ultimate Root ID to get the

Server ID. In addition, the Super Node ID is only as-

signed for 2 bits, hence it has found the destination

super node in one hop during the message forwarded

between nodes, the actual situation may exist multi-

hops.

(7) Request

resource directly

(3) RouteToNode

(Object ID=0111,

Node ID=0111,Exact)

(4) Response

Server ID=1101,

Object ID=0111

(2) RouteToNode

(Object ID=0111,

Node ID=11,Exact)

(5) Response Server

ID=1101, Object

ID=0111

(1) RouteToObject

(Peer ID=0000,

Object ID=0111)

(6) Response

Server ID=1101,

Object ID=0111

Super Node ID=00

)

Super Node ID=01

)

Super Node ID=10

Super Node ID=11

)

Peer ID=0000, Object ID=0011

Peer ID=0100, Object ID=1010

Peer ID=1000, Object ID=1111

Peer ID=1100, Object ID=0101

Peer ID=0001, Object ID=0010

Peer ID=0101, Object ID=1000

Peer ID=1001, Object ID=1101

Peer ID=0010, Object ID=0011

Peer ID=0110, Object ID=1010

Peer ID=1010, Object ID=0101

Peer ID=1110, Object ID=1101

Peer ID=0011, Object ID=1111

Peer ID=1011, Object ID=0010

Peer ID=1111, Object ID=1100

Object ID=0111, Server ID=1101

... … … ...

Peer ID=1101, Object ID=0111

Peer ID=0111, Object ID=1000

(7)

(4)

Figure 2: The M-Tapestry routing schematic diagram.

2.3 Node Joining and Leaving

In M-Tapestry model, nodes often join in or leave the

network, including ordinary node joining in or leaving

a subarea managed by a super node; the exit of super

node, and the splitting of super node.

It is very easy for ordinary node to carry out a

joining process. First, the ordinary node broadcasts a

“joining” message within the entire network, then all

super nodes which have received the message return

a “response” message, and the ordinary node chooses

the nearest super node to register according to the

time-delay of received response message. Hence, the

WINSYS 2010 - International Conference on Wireless Information Networks and Systems

joining process is accomplished. The leaving process

of ordinary node is classiﬁed as two situations: active

leaving or proactive leaving. When the super node re-

ceives an “exit” message from an ordinary node (ac-

tive), or monitores the failure of the ordinary node

(proactive), the super node will delete the relative in-

formation of the ordinary node.

When the number of ordinary nodes managed by

the super node beyond the threshold M, it will lead to

the splitting of super node. During the splitting pro-

cess, the super node divides those nodes maintained

by itself into two groups, one group is still managed

by the Original Super Node (OSN), and another group

is managed by the New Super Node (NSN). OSN

will select an ordinary node as the NSN according to

the reliability and stability of the connection between

nodes.

Either super node’s failure or leaving actively are

resulted in the super node exiting from the network,

and it can be looked as a leaving super node (LSN).

Ordinary nodes may detect the failure of super node

by the “heartbeat” mechanism, and then ordinary

nodes change to register the primary neighbor super

node, the registration process is same as the joining

process of ordinary node. When the leaving super

node actively leaves the network, it will transfer those

nodes managed by itself to the primary neighbor su-

per node, and informs other neighbor super nodes to

update their neighbor mapping table by means of the

back pointer.

3 SIMULATION AND ANALYSIS

We use P2PSim software platform in Linux environ-

ment to simulate the performance of the M-Tapestry

model compared to the Tapestry model. The conﬁg-

ure of the parameters is: random network topology;

In M-Tapestry model, number of super nodes is 24,

number of ordinary nodes is 1000; Each super node

can manage up to 100 ordinary nodes, the super nodes

and those ordinary nodes are partitioned according to

geographical location. Node query interval: lookup-

mean = 60000ms; the average survival time of super

node: lifemean1 = 3600000ms; the average time of

death of super-node: deathmean1 = 3600000ms; the

average survival time of ordinary node: lifemean2

= 3600ms; the average time of death ordinary node:

deathmean1 = 3600ms, time Simulation duration is

200000ms; started statistical time is100000 ms; In

Tapestry model, there are total 1024 nodes, which

other parameters are same as the above.

We are primarily concerned with the lookup

efﬁciency performance for M-Tapestry. The lookup

mean time statistical distribution region of M-

Tapestry and Tapestry is shown in Table 1. Pro-

cessed the simulation results, we can get the lookup

mean time probability distribution of M-Tapestry and

Tapestry, as shown in Figure 3.

Table 1: Lookup time statistical data in M-Tapestry and

Tapestry.

Period (ms) M-Tapestry(times) Tapestry(times)

0-100 786 56

100-200 84 264

200-300 46 283

300-400 34 236

> 400 10 121

0 100 200 300 400 500

0.0

0.2

0.4

0.6

0.8

1.0

Probability Distribution

Lookup Time

M-Tapestry

Tapestry

Figure 3: Lookup mean time probability distribution.

Observed from Table 1 and Figure 3 we can con-

clude that the resource discovery efﬁciency of the M-

Tapestry model is better than Tapestry model, for ex-

ample, in M-Tapestry, about 81.87% values of lookup

time are between 0-100ms, but in Tapestry it is ob-

viously lower than this percent, only 4.79% between

this period. It is because the nodes in M-Tapestry

model are partitioned at ﬁrst according to geographi-

cal location to ensure that the nodes in neighbor map-

ping table are also adjacent in actual distance. And

the architecture of M-Tapestry model is layered , the

distance between ordinary node and its registered su-

per node is short, so when using a direct point to point

communication, the propagation delay is very low. As

we known, Tapestry routing mechanism are used be-

tween super nodes, the lookup complexity is O(logn),

in which the value of n in M-Tapestry system is obvi-

ously much smaller than that in Tapestry. Therefore,

the lookup efﬁciency of M-Tapestry model is much

better than that of Tapestry.

A RESOURCE DISCOVERY STRATEGY FOR MOBILE PEER-TO-PEER NETWORKS

4 CONCLUSIONS

This paper addressed various resource discovery

strategies designed for mobile P2P networks. Com-

pared to traditional ﬁxed P2P networks, the new chal-

lenges of MP2P require improved resource discov-

ery strategies. Therefore we improved the Tapestry

model and proposed the novel M-Tapestry model for

mobile P2P networks, which is both more efﬁcient

and more ﬂexible. We adopted a layered architecture

in M-Tapestry, and instead of allowing all nodes to

access the Tapestry system, only a small number of

super nodes were chosen for this purpose. Thus our

solution reduces the cost of ordinary nodes and solves

the reliability problems caused by frequent of routing

table updates; On the other hand, we partitioned the

nodes according to their geographical location, which

assists us in avoiding the problem that the distance be-

tween ID-adjacent-nodesmay be high due to the Hash

operation. We analyzed the lookup efﬁciency of the

M-Tapestry model, and veriﬁed that it is more suitable

for employment in mobile P2P networks.

ACKNOWLEDGEMENTS

The authors thank Prof. Lajos Hanzo for many

helpful suggestions. This paper is supported by the

Joint State Program of the National Natural Science

Foundation of China (NSFC) and the National Rail-

way Ministry of China under project grant number

60830001.This paper is also supported by the State

Key Laboratory of Rail Trafﬁc Control and Safety un-

der key project grant number RCS2008ZZ007.

REFERENCES

Andersen, F., deMeer, H., and Dedinski, I. (2004). An archi-

tecture concept for mobile p2p ﬁle sharing services. In

Proc. of the Workshop at Information 2004 Algorithms

and Protocols for Efﬁcient Peer-to-Peer Applications,

pages 229–233.

Bakos, B., Csucs, G., Farkas, L., and Nurminen, J. (2003).

Peer-to-peer protocol evaluation in topologies resem-

bling wireless networks. an experiment with gnutella

query engine. In Proc. of the 11th IEEE Interna-

tional Conference on Networks (ICON2003), pages

673–680.

Cramer, C. and Fuhrmann, T. (2005). Isprp: A message-

efﬁcient protocol for initializing structured p2p net-

works. In Proc. of the 24th IEEE Int’l Conf. on Perfor-

mance, Computing, and Communications, pages 365–

370.

He, Y., Lee, I., Gu, X., and Guan, L. (2005). Centralized

peer-to-peer video streaming over hybrid wireless net-

work. In Proc. of IEEE International Conference on

Multimedia and Expo(ICME 2005), pages 550–553.

Hossfeld, T., Tutschku, K., and Andersen, F. (2005). Map-

ping of ﬁle-sharing onto mobile environments: Feasi-

bility and performance of edonkey with gprs. In Proc.

of the IEEE Conf. Wireless Communications and Net-

working, volume 4, pages 2453–2458.

Musolesi, M., Hailes, S., and Mascolo, C. (2005). Adap-

tive routing for intermittently connected mobile ad

hoc networks. In Proc. of the Sixth IEEE International

Symposium on World of Wireless Mobile and Multime-

dia Networks (WOWMOM 05), pages 183–189, Wash-

ington, DC, USA. IEEE Computer Society.

Peng, G., Li, S., Jin, H., and Ma, T. (2004). M-can: a lookup

protocol for mobile peer-to-peer environment. Inter-

national Symposium on Parallel Architectures, Algo-

rithms, and Networks, pages 544–549.

Ponmozhi, K. and Rajesh, R. (2009). Applying p2p in

manets for resource sharing. In Proc. of 2009 Interna-

tional Conference on Control, Automation, Communi-

cation and Energy Conservation, pages 1–5.

Pucha, H., Das, S. M., and Hu, Y. C. (2004). Ekta: An

efﬁcient dht substrate for distributed applications in

mobile ad hoc networks. In Proc.of the 6th IEEE

Workshop on Mobile Computing Systems and Appli-

cations (WMCSA 2004), English Lake District, pages

163–173.

Ratnasamy, S., Francis, P., Handley, M., Karp, R., and

Shenker, S. (2001). A scalable content addressable

network. In Proc. of ACM SIGCOMM 2001, pages

161–172.

Rowstron, A. and Druschel, P. (2001). Pastry: a large-scale,

persistent peer-to-peer storage utility. In Proc. of the

8th Workshop on Hot Topics in Operating Systems.

Stoica, I., Morris, R., Liben-Nowell, D., Karger, D.,

Kaashoek, M., Dabek, F., and Balakrishnan, H.

(2003). Chord: A scalable peer-to-peer lookup pro-

tocol for internet applications. IEEE/ACM Trans. on

Networking, 11(1):17–32.

Tianhao, Q. and Nikolaidis, I. (2004). On the performance

and policies of mobile peer-to-peer network protocols.

In Proc. of Second Annual Conference on Communi-

cation Networks and Services Research, pages 208–

217.

Voitenko, I. (2009). On the implementation problems of

mobile peer-to-peer networks. In Proc. of 29th IEEE

International Conference on Distributed Computing

Systems Workshops, ICDCS Workshops ’09, pages

455–458.

Zhao, B. Y., Kubiatowicz, J. D., and Joseph, A. D. (2001).

Tapestry: An infrastructure for fault-tolerant wide-

area location and. Technical report, University of Cal-

ifornia at Berkeley, Berkeley, CA, USA.

WINSYS 2010 - International Conference on Wireless Information Networks and Systems