Abstract—The study of group communication in MANET can be

challenging due to its highly dynamic topology, limited wireless bandwidth and constraint of mobile node’s capability. Generally speaking, a tree-based scheme for group communication can avoid forwarding unnecessary duplicate data. However, to maintain a strict structure is not an easy task and the data delivery can be highly unreliable in the dynamic environment of MANET. Approaches like flooding or gossip can be more reliable through redundant routing paths, but are wasting a lot of bandwidth especially when the group size is large. In this paper, a hierarchical protocol using cross-layer optimization (HCLP) is proposed for group communication in MANET. HCLP constructs a hybrid two-layered overlay structure, combines both gossip-based and tree-based schemes for data dissemination, and adjusts its overlay topology using cross-layer information. Simulation results demonstrate HCLP’s high reliability and low bandwidth consumption.

Index Terms—MANET, Group Communication, Hierarchical Architecture, Heterogeneity, Cross-layer Protocol

I. INTRODUCTION

OBILE ad hoc network is a temporary and multi-hop network which allows portable devices to communicate

with each other without the aid of a centered infrastructure [1]. The ultimate goal of using ad hoc network is for information sharing or collaborative computing among nodes with common interest, like audio/video conferencing, disaster recovery and online games. And that motivates our research on group communication in MANET. However, designing a group communication protocol for MANET is challenging and difficult

Manuscript received Jan 9th, 2007. This work is supported by the National

Natural Science Foundation of China under Grant No.60403031 and No. 90604015, and funded by France Telecom R&D.

Yifen WEI is with Next Generation Internet Research Center, Institute of Computing Technology, Chinese Academy of Sciences, and Graduate University of Chinese Academy of Sciences, Beijing, 100080, P.R.China (Phone: 86-10-62600710; Email: wyf@ict.ac.cn).

Gaogang XIE is with Next Generation Internet Research Center, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100080, P.R.China, and ARLES, INRIA-Rocquencourt, Domaine de Voluceau, 78153 Le Chesnay, France (Email: xie@ict.ac.cn).

Zhongcheng LI is with Next Generation Internet Research Center, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100080, P.R.China (Email: zcli@ict.ac.cn).

due to the dynamic topology, limited bandwidth, constraint of node capability, and frequent disconnections in MANET.

Previous group communication protocols in MANET can be generally classified into several categories. The tree-based schemes can avoid forwarding unnecessary duplicate data and achieve high data delivery efficiency, and are thus widely exploited [2]-[4]. However, to maintain a strict structure is not an easy task and tends to be vulnerable to arbitrary node failures in the dynamic environment of MANET. By providing redundant routing paths between nodes, mesh-based schemes are proposed [5]-[6], which can tolerate random failures and improve reliability in a certain extent. However, the enhanced robustness is obtained at the expense of wasting bandwidth resources, and is quite limited. Approaches like flooding or gossip [7] can be much more reliable due to their inherent redundancy, but suffer from unbearable bandwidth overhead especially when the group size is large, and thus lack of scalability. Therefore, high performance group communication protocols are desirable, which can both guarantee data delivery ratio and avoid generating too much traffic.

In this paper, a hierarchical protocol using cross-layer optimization (HCLP) is proposed for group communication in MANET. HCLP constructs a hybrid two-layered overlay structure by taking into account both heterogeneity of MANET nodes [8] and physical distance information. For data dissemination, it combines both gossip-based and tree-based schemes to improve reliability and reduce traffic overhead. Also, it adjusts its overlay topology by checking its local routing table periodically to keep an optimized overlay structure. Simulation results demonstrate its high reliability and low bandwidth consumption.

The rest of the paper is organized as follows. Related work about group communication is presented in Section 2. In Section 3, HCLP operation is described in detail. Simulation results are shown and analyzed in Section 4. Finally in Section 5 we conclude the paper.

II. RELATED WORK Location-Guided Tree [2] is a stateless small group multicast

scheme, which utilizes geometric locations of destination nodes as heuristics to compute trees, and is accompanied by a hybrid location update mechanism to disseminate location information

A Hierarchical Cross-Layer Protocol for Group Communication in MANET

Yifen WEI, Gaogang XIE and Zhongcheng LI

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Proceedings of the 2007 IEEE International Conference on Telecommunications and Malaysia International Conference on Communications, 14-17 May 2007, Penang, Malaysia

1-4244-1094-0/07/$25.00 ©2007 IEEE. 62

among a group of nodes. Data delivery on top of the physically matched overlay minimizes communication overhead whereas is considerably vulnerable due to node failures. Adaptable Overlay Multicast [3] uses an expanding ring search method to build a shared-tree and maintains path by periodical detecting. It is robust and cost-efficient in a certain extent but path maintenance is not a trivial task and can easily overwhelm the network with unnecessary duplicate traffic, especially without the aid of lower layer information. WB [4] exploits structured P2P solutions Pastry [9] for group membership management and Scribe [10] for constructing multicast trees. However, its performance is only evaluated in STATIC environment and retains unknown when nodes are moving.

CAMP (Core Assisted Mesh Protocol) [5] uses a shared mesh structure to support multicast routing in MANET. This structure ensures the mesh includes the reverse shortest path from all receivers to the source. CAMP consists of the maintenance of multicast meshes and loop-free packet forwarding over such meshes. ODMRP [6] uses forwarding group concept and a sender-advertised approach to build the mesh. ODMRP can operate both as a unicast and a multicast protocol and thus doesn’t require a separate unicast routing protocol running in the background. However, as previous mentioned, mesh-based protocols can only provide limited robustness, and also the maintenance of mesh structure is difficult.

Route Driven Gossip [7] is a reliable gossip based protocol which utilizes on-demand routing protocol DSR [11] for membership management. It provides an analytical evaluation about its reliability using mathematical method. However, redundancy inevitably produces a large amount of traffic and consequently undermines its scalability.

III. HIERARCHICAL CROSS-LAYER PROTOCOL In this section, we will introduce a hierarchical cross-layer

protocol (HCLP), which targets at implementing a reliable, cost-effective and scalable group communication protocol in MANET. We‘ll describe HCLP in the following subsections in detail: 1) overlay construction; 2) data dissemination; 3) overlay topology maintenance. Prior to detailed protocol presentation, we’d like to make some general assumptions and introduce basic data structures.

A. Assumptions and data structures For simplicity and without loss of generality, the following

assumptions are made for the issue of group communication in MANET: 1) Each node may have information to distribute to all other nodes in the group. Each node in the group maintains a local database, and the data item is identified by a tuple <source id, version number, data content>; 2) Node capabilities are assumed to be Pareto distributed, namely a majority of nodes

have a small capability, while the powerful nodes are in the minority; 3) At the beginning, each node should know the existence of at least one node in the group or flood request messages into network to get its existence, which is called a contact; 4) Nodes are easily disconnected and may reconnect later.

Next we would like to introduce some basic data structures and message definitions used later. 1) Notations related to node property

id: A unique identifier that each node has; SN/LN: Super node (SN) or leaf node (LN), which is the role

each node plays. It is determined by the SN/LN election policy; cap: Capability of a node, i.e. measurement of CPU process

ability and memory storage, which is predefined and never changes;

SL: Super node list in the system that each node keeps; SDTable: A table of distances to current super nodes, which

consists of a set of <id, distance> and is updated accordingly. Distances are extracted from routing tables; 2) Global defined parameters

minCap: Minimum capability for a node to be able to take the responsibility of SN;

maxDis: Maximum distance from LN to its connected SN; It has an impact on the SN/LN election policy and exceeding this will invoke topology maintenance operation.

avgCap: As each SN is connecting to several LNs, SN should be powerful enough to take charge of its connecting LNs. avgCap is the minimum average capability that an SN should at least allocate for each of its connecting LN. If accepting another LN makes the average capability each of its LN obtains smaller than avgCap, then SN should refuse the subscription. 3) Message definitions

INIT/RESPONSE: Whenever a node joins the system, it sends an INIT message to its contact node, who responds with a RESPONSE message containing SL;

SUBSCRIBE/CANCEL: A node tries to subscribe to SN to become its LN by SUBSCRIBE message, and quits from it by CANCEL message;

ACCEPT/REFUSE: super node’s approval or denial message responding to SUBSCRIBE;

FLOOD/UNFLOOD: Declaring to become an SN or no longer to be an SN;

REQUEST/REPLY: A reconnected node asks for latest data from adjacent nodes by REQUEST, and REPLY is the response message. These two messages both have the form of <id,version>…<id,version>;

UPDATE: Data information is encapsulated in UPDATE message.

B. Overlay construction HCLP constructs a two-layered overlay structure by electing

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super nodes and leaf nodes when they join the system. The design of constructing overlay topology is motivated by the following two considerations. 1) Packets transmission will actually traverse a shorter physical path if overlay topology is more adjacent to underlying network, and thus incur less communication traffic and are less likely to get lost. That is the reason why we try to get overlay topology to be matched with physical network; 2) It is supposed that super nodes should take a more significant responsibility as they usually take charge of several leaf nodes. Thus node heterogeneity is the other consideration in the SN/LN election policy.

The SN/LN election policy is defined by procedure MakeLocalDecision. It takes as input cap and SDTable and outputs decision result of becoming SN or LN. We denote in SDTable the shortest distance as closest and number of distances shorter than maxDis as count, and define TF as the probability of becoming SN. Then TF is calculated as follows:

min

min & & max

min && max

0

1

* *

cap Cap

cap Cap closest Dis

cap Cap closest Dis

TF

p CF q DF

<

≥ >

≥ ≤

=

+

(1)

Here p and q are parameters to respectively measure the importance of CF and DF, which are expressed as follows:

( ) /CF cap minCap cap= − (2) (0,1)1/exp( ) ( )tDF count t ∈= − (3)

Thus a node which is too incapable to take the responsibility of an SN, should definitely become an LN in order not to be exhausted. If the node is of sufficient capability but too faraway from all super nodes, then it goes to the role of SN, otherwise physical distance from LN to SN will become too large, making overlay topology mismatched with underlying network. In the third case that the node has sufficient capability and short enough distance to super nodes, satisfying both requirements of becoming SN or LN, TF is calculated as combination of effect of node capability CF and effect of physical distances DF. Finally, we make a comparison between TF and threshold value W. If TF is greater than W, then become SN else LN.

The detailed operation for overlay construction is presented in Fig. 1. At the beginning, the joining node tries to retrieve current super node list SL from contact node through INIT/RESPONSE interaction and fill in local SDTable. Then the node decides to become SN/LN through MakeLocalDecision procedure. If the decision result is SN, then it floods to each super node in the system declaring itself to become SN, otherwise it attempts to subscribe to the nearest super nodes in succession.

With regard to SN, its action is described as follows. When SN receives a SUBSCRIBE message, it decides whether to accept the subscribing node or refuse it according to its capability and current out degree OD. If the expression

/( 1)cap OD avgCap+ > (4) is satisfied and thus this SN won’t be exhausted even after accepting the new subscribing node, it responds with ACCEPT message otherwise with REFUSE message. In case that SN receives a FLOOD message, it appends the source id to local SL, and then forwards on to each LN, making newly elected SN to be known by all nodes in the system.

To illustrate in a clearer manner how overlay topology is constructed, let’s take Fig. 2 as an example. As denoted in Fig. 2(a), currently there exist super nodes S1~S4 and leaf nodes

Figure 1 Overlay construction

(a) Before nodes join (b) After noes join Figure 2 How nodes join

Table 1 Node capability and SDTable parameters

Procedure Join_Group 1. Send INIT to the contact; 2. Wait for RESPONSE, then SL RESPONSE.SL;

if timeout, goto Step 1 after a random time; 3. SDTable extract from routing table the physical distance of

each node in SL; 4. type MakeLocalDecision(cap, SDTable); 5. if(type = SN) { //become SN

send FLOOD to each node in SL; set itself to be SN; return;

} 6. else { //try to become LN

while(There exists unchecked nodes in SDTable) { send SUBSCRIBE to the nearest node; if(received ACCEPT)

set itself to be LN; return;

} //Failed to become LN

Goto Step 1 after a random time; } End Procedure Join_Group

S1

S2

S4

S3

L1

L3

L2 L8

L4

L7

L6L5

S1

S2

S4

S3

L1

L3

L2 L8

L4

L7

L6L5

M1

M2

M3

(a) System parameters minCap avgCap maxDis

10 7 2

（b）Super node cap S1 S2 S3 S4

28 13 20 15

(c) Joining nodes’cap and SDTable SDTable Joining

Nodes cap S1 S2 S3 S4

M1 8 1 2 3 2

M2 13 3 4 1 2

M3 18 3 4 3 5

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L1~L8 in the system. Super nodes connect to each other while leaf nodes connect to only one super node, which are always the cases whenever a node joins the system using above described mechanism. M1, M2, M3 are nodes willing to join the system. Necessary parameters are set accordingly as in table 1. With a capability smaller than minCap, M1 picks up the nearest super node S1 to subscribe and is fortunately accepted by S1 with formula (4) satisfied. M2, which has a higher capability than minCap and a shortest distance to super nodes smaller than maxDis, decides to become a leaf node according to MakeLocalDecision. Then M2 sends a SUBSCRIBE message to the nearest super node S3 but is refused as S3 is already saturated. So M2 continues to try a second nearest super node S4 and is successfully accepted. With regard to M3, which has a larger capability than minCap but a greater distance than maxDis from all super nodes, it floods to the system declaring itself to become SN. The final formalized overlay topology is depicted in Fig. 2(b).

As can be seen in Fig. 2, the following characteristics are observed in the overlay topology: 1) A majority of nodes are LNs and much fewer are SNs; 2) Each SN is connecting to several LNs; 3) Each SN is physically close to its LNs while faraway from other SNs. 4) Ideally, each node is supposed to be aware of all SNs in the system (Actually it may not be completely true because FLOOD message may get lost).

C. Data dissemination Reliability and communication overhead are two main factors

to evaluate the performance of group communication protocol. For one single packet transmission, its delivery rate is determined by the length of routing path and success rate at each hop [7]. Similarly, communication overhead is largely depending on the length of routing path and packet size.

In order to improve reliability and reduce communication overhead, the following polices are exploited in HCLP. Among physically faraway super nodes, gossip mechanism is utilized and the redundant routing paths greatly enhance data delivery rate. To further improve reliability, gossip targets are always chosen from nearer super nodes in its routing table and packets are spreading step by step until they reach all destinations. Between close super nodes and leaf nodes, unicast forwarding from SN to LN is deployed, which can be both reliable and cost-effective due to short physical distances. When nodes reconnect to network after disconnecting for a period of time and missing certain packets, REQUEST messages are sent to pull latest data.

The detailed operations are as follows. Whenever an LN generates traffic for delivering, data is encapsulated in an UPDATE message and transmitted to its connected SN. Whenever an SN originates an UPDATE message or receives it for the first time, it forwards the message to all its connecting

leaf nodes excluding the originator. Then it selects a specific number of nearer nodes from SDTable as targets and propagates the message to them. The target number is roughly chosen logarithmically with the size of SNs in the system according to generic gossip theory [15]. In this way, packets are spreading all over the group until almost every member receives it. For a reconnected leaf node, a REQUEST message is sent to its connected SN, and for a reconnected super node, it is destined to adjacent SNs. Then SNs send back latest data with a REPLY message.

D. Topology maintenance As nodes keep moving in mobile ad hoc network, distances

between super nodes and leaf nodes can become unbearably large, causing the overlay topology to no longer match with physical network. Thus, it is important for HCLP to adjust overlay topology according to network dynamics and in the meanwhile keep maintenance overhead as small as possible.

The overlay topology maintenance algorithm is described as follows. With a leaf node, it periodically checks its distance to its super node in its routing table. If the distance is smaller than maxDis, then adaptation is unnecessary. Or else, if there exists at least one node in SDTable that is within a smaller distance than maxDis, then it tries to subscribe to the nearest node one by one until it is accepted or all subscribing fails. In the third case that no SN is near enough or all subscribing fails, this node is promoted to a super node if its capability is large enough (i.e. larger than twice the minCap) or else just remains the same status. With regard to SN, only when no leaf node is connecting and its capability is smaller than twice the minCap, it considers whether to change its role according to MakeLocalDecision in order not to generate too much maintenance traffic. If the deciding result is LN, it tries to subscribe to the nearest super nodes one by one and upon success, it changes its role to LN and sends UNFLOOD to other super nodes declaring no longer to be SN. Otherwise it remains SN and nothing needs to be done.

IV. SIMULATION AND ANALYSIS In this section, the performance of HCLP is studied by

simulation and compared with gossip-based protocol. Particularly, we have studied performance metrics including reliability and communication overhead, which are illustrated as follows: 1) Reliability: packet delivery ratio, namely average ratio of data packets actually delivered to intended destinations as a function of data packets supposed to be delivered to intended destinations; 2) Communication overhead: bandwidth overhead occupied by data packets for delivery and control packets for topology maintenance;

The simulation experiment is carried out under different system settings, including group size, node density, moving

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speed, and radio propagation distance, which are described respectively in later subsections.

A. Simulation Model The simulation experiment is based on NS-2 [12] with CMU

wireless extension and DSDV [13] is used as underlying unicast routing protocol. We simulate a mobile ad hoc network with 60 to 110 nodes moving within a 1500m*1500m area, operating over 1000s simulation time. Moving pattern follows a Random Way Point model [14]. Initially nodes are placed randomly in the area. Each node selects a random destination and moves towards the destination with a speed randomly selected from [Vmin, Vmax]. After it reaches the destination, it pauses for a period of time and repeats this movement pattern. In our simulation Vmin is 1m/s and Vmax has a range from [2m/s, 18m/s]. The pause time is set to 30s. Simulation parameters are presented in table 2.

In the experiment, 10 nodes are randomly selected to consecutively originate data transmission with each packet having a length of 300 bytes. Each simulation is repeated three times to obtain average values. Both HCLP and gossip use the

Table 2 Simulation parameters Parameter Default value Range Area size 1500m*1500m -- Number of nodes 80 60-110 Group size 30 20-70 Vmin 1m/s -- Vmax 8m/s 2m/s-18m/s Pause time 30s -- Propagation distance 250m 250m-450m Simulation time 1000s --

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Data delivery rate(%)

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erhead(

KB)

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(a) impact on data delivery rate (b) impact on bandwidth overhead Figure 3 effect of group size

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Tot

al b

andwidt

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erhe

ad(K

B))

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(a) impact on data delivery rate (b) impact on bandwidth overhead

Figure 4 effect of node density

same network scenarios.

B. Effect of group size The first set of experiments aims at evaluating effect of group

size on the performance of HCLP. Group size ranges from 20 to 70 with a fixed number of system nodes 80. As seen in Fig. 3(a), both gossip and HCLP have a fairly high data delivery ratio, respectively from [81.1%, 87.6%] and [84.5%, 91.1%] and basically HCLP outperforms gossip a bit. In terms of communication overhead as in Fig. 3 (b), HCLP induces much lower overhead than gossip, with a range [328.4, 1030.08] KB comparing to [328.4, 1030.08] KB. As the number of nodes increases, both HCLP and gossip generate an increasing amount of traffic but HCLP advances much more slowly. This shows HCLP ‘s significant advantages over gossip especially when group size is large and thus demonstrates its scalability.

C. Effect of node density In order to evaluate the impact of node density on protocol

performance, number of nodes varies from 60 to 110 distributed over the network while group size is fixed at 30. As seen in Fig. 4(a), HCLP has a data delivery rate from 79.3% to 92.2% while gossip has a tiny higher range from 82.3% to 93.3%. In Fig. 4(b), both HCLP and gossip incur smooth traffic overhead, ranging from 381.168KB to 436.67KB and from 792.23KB to 969.07KB respectively.

Basically, the distinction in terms of packet delivery ratio is unremarkable as node density increases. However, when the number of nodes in the system is small, it seems that gossip excels HCLP quite a bit. This is because HCLA largely relies on physical distances for optimization. With a sparsely distributed

(a) impact on data delivery rate (b) impact on total bandwidth overhead Figure 5 effect of moving speed

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0

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2 4 6 8 10 12 14 16 18Movi ng r at e( M/ S)

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l b

andw

idt

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)

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network, average physical hops between nodes become considerably large that unicast transmission between super nodes and leaf nodes suffers from a great packet loss rate, undermining protocol performance. Nevertheless, with regard to bandwidth overhead, HCLP is less than half of gossip, outperforming gossip a great deal.

D. Effect of node moving speed Network partition occurs frequently and packet loss rate

increases due to no route when nodes are moving with a high speed. The following set of experiments evaluates the impact of varying moving speeds on protocol performance. As seen in Fig. 5(a), both HCLP and gossip have a fluctuating data delivery rate. HCLP ranges from 81.4% to 91.0% with a majority above 85% while gossip ranges from 77.3% to 90.1% with a majority below 85%. With regard to bandwidth cost, gossip scales from [670.15, 848.395]KB, twice as much as HCLP from [366.06, 470.22]KB.

It is the randomly generating scenario that causes simulating results to be fluctuating a bit. The data delivery ratio gap between HCLP and gossip is slight. However with respect to communication overhead, HCLP is superior to gossip significantly. So totally we can say HCLP provides high adaptability to the dynamic situation in MANET.

E. Effect of radio propagation distance Generally speaking, with propagation distance increasing,

packets will traverse a smaller number of hops and that improves reliability and consumes less communication overhead. Fig. 6 shows this trend in terms of data delivery ratio and bandwidth cost with propagation distance varying from 250m to 450m. In Fig. 6(a), data delivery rate of HCLP ranges from 91.0% to 95.1% while gossip ranges from 82.3% to 97.8%. Communication overhead decreases from 455.96KB to 383.57KB for HCLP and from 826.96KB to 648.96KB for gossip.

It is worth mentioning that with propagation distance increasing, packet delivery ratio of gossip surpasses HCLP a bit. This is mainly because with a large propagation range but a fixed area size, average distances between mobile nodes in terms of physical hops become so small that the hierarchical characteristics in HCLP is not so obvious and thus becomes less competitive. However in order for MANET to be applicable, radio propagation distance should not be too large.

V. CONCLUSION In this paper, we designed and evaluated a hierarchical

cross-layer protocol for group communication in MANET. It took into account heterogeneity of mobile nodes as well as physical distances to elect super nodes and leaf nodes, constructing a two-layered overlay topology. We used gossip

mechanism for data dissemination among super nodes to improve reliability and unicast between physically close super nodes and leaf nodes. We also designed a topology maintenance mechanism to keep overlay topology adjacent to physical network. In the simulation experiment, the performance is studied and compared with gossip-based protocol under different settings of group size, node density, node moving speed and signal propagation distance. Simulation results demonstrate that HCLP is a reliable, cost-effective and scalable protocol for group communication.

Periodic path maintenance mechanism sometimes may not timely reflect the changing of underlying network. So in the future, we plan to deploy event driven mechanism, namely obtaining information from MAC layer to react to the changing network and further improve its performance.

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