lncs 4325 - zone-based replication scheme for mobile ad ...keshi.ubiwna.org/paper/zone-based...

J. Cao et al. (Eds.): MSN 2006, LNCS 4325, pp. 698 – 710, 2006. © Springer-Verlag Berlin Heidelberg 2006

Zone-Based Replication Scheme for Mobile Ad Hoc Networks Using Cross-Layer Design

Ke Shi, Rong Chen, and Hai Jin

Services Computing Technology and System Lab School of Computer Science & Technology

Huazhong University of Science & Technology, Wuhan 430074, China {keshi, crong, hjin}@mail.hust.edu.cn

Abstract. Accessing remote data is a challenging task in mobile ad hoc networks (MANETs). A common technique used to improve the performance of data access is replication, which improves the performance of data access in distributed systems at the cost of increased storage space and communication overhead. Due to strict resource constraint, node mobility and impairments of wireless transmission, applying replication schemes developed for distributed systems to MANETs directly leads to poor performance. In this paper, we develop a zone-based replication scheme for MANETs. In this scheme, every node proactively maintains replica distributing information within its replicating zone, which leads to the access from requesting node to the requested data item (including its replicas) distributed in its replicating zone can be satisfied directly. If requested data item is outside the replicating zone, reactive lookup process is invoked to find the node hosting the requested data item and the route to this node at the same time. Opportunistic data replicating is performed spontaneously with data transferring, and corresponding replica is allocated to nodes located in the replicating zone of the requesting node. Using cross-layer design, we illustrate how the hybrid adaptive routing technique, zone routing protocol, assists data lookup and replication to achieve high performance of data access. Simulation results have shown that our design is successful in a dynamic MANET.

Keywords: Ad hoc network, Zone, Zone Routing Protocol, Data Lookup, Data Replication, Cross-Layer Design.

1 Introduction

A MANET consists of many mobile nodes connected by wireless links[1].In such a network, each node operates not only as an end-system, but also as a router to forward packets. Two nodes can communicate with each other directly if they are within each other’s wireless transmission range or via intermediate nodes if they are far away.

Although routing is a very important issue in MANETs, other issues such as data access are also very important since the ultimate goal of using MANETs is to provide information access to mobile nodes. Accessing desired remote data in MANETs is much more difficult than in fixed networks. Due to strict resource constraint, node

Zone-Based Replication Scheme for Mobile Ad Hoc Networks 699

mobility and impairments of wireless transmission, disconnections may occur frequently. This means that the creator of data is often unreachable when the data is needed. Even when the creator of data is reachable, multi-hop wireless connections cause long request delay.

Data replication has been widely used to improve data accessibility in distributed systems. By replicating data at mobile nodes, data accessibility can be improved because there are multiple replicas in the network and the probability of finding one copy of the data is high. Further, data replication can also reduce the request delay, since mobile nodes can get the data from some nearby replicas.

However, applying replication schemes developed for distributed systems to MANETs directly leads to poor performance since the underlying network connections are not reliable and stable anymore and the availability of nodes is not identically independent distributed anymore. The performance of data access heavily depends on the underlying routing service.

To achieve high performance in data access, we have developed a zone-based replication (ZBR) scheme for MANETs, integrated with a data lookup service, and assisted by a hybrid adaptive routing protocol, zone routing protocol (ZRP)[2]. In this scheme, every node proactively maintains replica distributing information within its replicating zone, which leads to the access from requesting node to the requested data item (including its replicas) distributed in its replicating zone can be satisfied directly. If requested data item is outside the replicating zone, reactive lookup process is invoked to find the node hosting the requested data item and the route to this node at the same time. Opportunistic data replicating is performed spontaneously with successive data transferring, and corresponding replica is allocated to nodes located in the replicating zone of the requesting node.

The rest of this paper is organized as follows: Section 2 presents background and related work. The system model and basic notion is introduced in Section 3. Proposed zone based replication scheme using cross-layer design is discussed in detail in Sections 4. Section 5 evaluates the schemes using simulations with different setups. We conclude with Section 6 and outline the future work.

2 Background and Related Work

Data replication is a traditional technique in distributed systems. Hara[3] proposed a data replication scheme in MANETs, which optimized the location of data replicas within a network periodically to achieve certain data accessibility. However, the assumption that access frequencies to data items from each node are known and are fixed limits the applicability of the schemes in practical systems. Periodical replicas reallocation also leads to heavy communication overhead.

Similarly to Hara’s work, Wang[4] considered the problem of replica allocation. It takes into consideration topological information, and data replication occurs only when necessary according to certain topology detection schemes. These schemes depend on the mobility model and assume that the locations and velocities of all mobile nodes are known. Yin and Cao[5] proposed data replication schemes that address both the query delay and the data accessibility. As both metrics are important for mobile nodes, their schemes need to balance the tradeoffs between data

700 K. Shi, R. Chen, and H. Jin

accessibility and request delay under different system settings and requirements. Their work adopted the same system model with Hara’s work.

What is fully unseen from these works is the consideration of the underlying MANET routing services coupled with data access tightly. They do not address the issues that how to find an optimal path from the node requesting data to the node hosting the data or its replica either.

The existing routing protocols can be classified either as proactive or reactive. Purely proactive schemes continuously use a large portion of the network capacity to keep the routing information current, such as DSDV[6] and OLSR[7]. The widely used DSR[8] and AODV[9] are reactive protocols, in which global search procedure leads to significant control traffic and long delay. ZRP[2] provides efficient and fast discovery of routes by integrating these two radically different routing schemes.

Cross-layer design introduces stack wide layer interdependencies to optimize overall network performance. MobileMan project[10] introduces inside the layered architecture the possibility that protocols belonging to different layers can cooperate by sharing network-status information while still maintaining separation between the layers in protocol design. This project focuses only on providing a general architecture and does not look at the special problems such as data access.

Chen etc.[11] proposed a cross-layer framework to solve the data accessibility problem in MANETs. It utilizes advanced data advertising, lookup and replication services, as well as a novel predictive location-based QoS routing protocol in an integrated fashion to achieve high data access success rate. The performance of this scheme depends on the predictive accuracy of nodes’ location and movement, which is the difficult task in practical environment.

Gruber etc.[12] develop a Mobile Peer-to-Peer Protocol (MPP) stack to support peer-to-peer file sharing in MANETs. It spans from the network layer to the application layer, and tries to reuse existing protocols as far as possible. The underlying routing protocol is DSR.

3 System Model and Basic Notion

Fig. 1 shows part of a MANET. Each mobile node in the network is assigned a unique identifier. Data is handled as a data item which is a collection of data. Each data item located in the network is also assigned a unique data identifier. The original copy of each data item is held by a particular mobile node. Each mobile node has certain storage space for creating replicas excluding the space for the original data item that the node holds. For example, node S has n original copies of data items {d1, d2 . . . dn}.

In this MANET, a data request is forwarded hop-by-hop until it reaches the node hosting the original copies of data items and then this node sends the requested data back. To improve the successful data access ratio and reduce the request delay, the length of this multi-hop path between the data provider and the requester should be as short as possible, and the time spending on find such an optimal path should be as short as possible too. Although data replication and


Fig. 1. A MANET

routing protocols can be used to achieve this goal separately, there is a limitation on how much they can achieve. In the following, we propose cross-layer zone-based replication scheme.

The basic notion is that data replication service in the application layer and zone routing protocol in the network layer can cooperate by sharing network-status information. Zone is the core concept in this scheme. A zone (of radius r) is defined for each node and includes the nodes whose minimum distance in hops from the node in question is at most r hops. Each node is assumed to maintain some kinds of information only to those nodes that are within its zone. In network layer, this zone is called routing zone, and routing information is maintained. In application layer, this zone is called replicating zone, and the information about replicas distribution and storage space are maintained. All these information are shared by the two layers. A node learns its zone through some sort of a proactive scheme.

Data lookup is incorporated with route discovery. Opportunistic replica distributing is performed with data transferring simultaneously when there is no available replica in the replicating zone of data requestor.

An example of a zone (for node A) of radius two hops is shown in Fig. 1. For the purpose of illustration, we depict zones as circles around the node. However, one should keep in mind that the zone is not a description of physical distance, but rather nodal connectivity (hops). Note that in this example, nodes A–J are within the routing zone of the central node A. Node K-V is outside A’s routing zone. Peripheral nodes are nodes whose minimum distance to the node is exactly equal to the zone radius. The remaining nodes are categorized as interior nodes. Thus, in Fig. 1, nodes G, I and C are interior nodes while B, D, E, F and J are peripheral nodes.

4 Cross-Layer Zone-Based Replication Scheme

In this section, we describe cross-layer zone-based replication scheme in detail. Data replication, lookup and ZRP work together to facilitate data access for various applications at the end-systems.


4.1 Zone Information Maintenance

In network layer, a node maintains routing information to those nodes that are within its routing zone through some sort of a proactive scheme, which is called intra-zone routing protocol (IARP) in ZRP. In this paper, we use OSLR [7]. However, any other proactive scheme would do. While the performance of the ZRP depends on the choice of IARP implementation, previous research[13] suggests that the tradeoffs are not strongly affected by the particular choice of the proactive scheme used.

In application layer, a node needs to maintain the information about the replica distribution and the nodes’ capabilities within its replicating zone (its routing zone in network layer) to support data lookup and replica allocation. Using cross-layer design, it incorporates with routing zone maintenance. Every node has three tables, routing table, data lookup table and capability table.

Data lookup table describes the distribution of the data items (original copies or replicas) within the node’s zone with a list of entries: <data_id,o_flag, valid_period, description>. The valid_period field indicating the freshness of the data is used to maintain consistency. We will discuss the detail in section 4.4. The o_flag field indicates whether the data item is original copy or not.

Mobile nodes may have very different capabilities ranging from small PDAs to laptops. Considering heterogeneity of the nodes, capability table provides useful information of nodes’ resource within the zone supporting replica allocating decision. In this paper, only free storage space is considered since we assume single node’s processing capability does not have significant effect on the performance of data access. Other parameters such as remaining power and processor utilization can be easily inserted into this table to support more comprehensive decision.

OLSR utilize periodical “hello” messages to sense neighbor and update routing table. To maintain the rest zone information, each node appends data lookup entries and capability entry to the “hello” message. Upon receiving the “hello” message, the data lookup table maintenance procedure renews the information associated with the existing data items, and augments the table if new data items become available, and capability table maintenance procedure renews the free storage space parameter associated with the nodes in this zone. Because the updates are only propagated locally, the amount of update traffic required to maintain a zone does not depend on the total number of network nodes (which can be quite large).

Since a node may contain a larger number of data items, the size of “hello” message may become very large. Periodical propagating full information may lead to unnecessary overhead. To reduce the size of the “hello” messages, we develop a method to include only the difference of contents from the previous “hello” message. The complete “hello” messages are propagated in longer time intervals. Between complete “hello” messages, smaller differential “hello” messages are sent out in shorter time intervals.

4.2 Data Lookup

In our scheme, data lookup is integrated with route discovery. In ZRP, IARP maintains routes for the nodes that are within the coverage of the routing zone. The inter-zone routing protocol (IERP) is responsible for reactively discovering routes to


destinations located beyond a node’s routing zone. In application layer, intra-zone data lookup based on IARP finds the data items located in the nodes that are within the coverage of the replicating; and inter-zone data lookup based on IARP is responsible for reactively discovering the data items located in the nodes beyond a node’s replicating zone.

When a node wants to access a special data item, intra-zone data lookup takes place locally at this node. The process of intra-zone data lookup is as follows:

(1) Check the data availability through local data lookup table. If data item is available in the local zone, go to step 2; otherwise, inter-zone data lookup process is invoked.

(2) Check the path to the hosting node through local routing table. (3) Send the request to the hosting node to retrieve the data. (4) Hosting node transfer the data items to the requested node.

Fig. 2. An example of data lookup

Since the lookup table has descriptions of all available data located in the nodes within the replicating zone, the node can get this kind of data items with a very low request delay. As shown in Fig. 2, if A want to access data items c2, A can find its hosting node D and corresponding route A-G-D through intra-zone data lookup process since D is within A’s zone.

If the requested data item is not available in the replicating zone, inter-zone data lookup process is invoked to find the requested data item and corresponding path. In our scheme, it is implemented by extending AODV. The process of inter-zone lookup is as follows:

(1) The data requestor propagates a data request to all its peripheral nodes. (2) Upon receiving the data request, the peripheral nodes execute the intra-zone

data lookup: they check whether the data item is located in the nodes within their zone. If so, go to step 3. If not, the peripheral node forwards the request to its peripheral nodes, which in turn execute the same procedure.

(3) A data reply (including route reply) is sent back to the data requestor indicating the route to the node hosting the requested data items (original copies or replicas).

(4) The route between the data requestor and hosting node is established through route accumulation. AODV utilizes short-term storage at each relaying node to temporarily store a route in the form of next-hop routes back to the data requestor.


Comparing with DSR, route accumulation would occur during the route reply phase rather than the route query phase, resulting in less IERP traffic.

(5) Hosting node transfer the data items to the requested node along the established route. Opportunistic replication is triggered at the same time. The core idea of opportunistic replication is to replicate the data items beyond the zone of data requestor into the nodes within its zone with the normal data access.

An example of this inter-zone data lookup procedure is demonstrated in Fig. 2. If A wants to access d2, A first checks whether d2 is within its zone through intra-zone data lookup. Since A find no node within its zone hosts d2, A propagates a query to its peripheral nodes; that is, A sends a query to nodes B, D, E, F, H and J. Now, in turn, after verifying that d2 is not in the nodes within its routing zone, each one of these nodes forwards the query by propagating the query to its peripheral nodes. In particular, H sends the query to N, which recognizes d2 as being in S within its zone and responds to the query, indicating the forwarding path: A–C–H–L-N-Q-S.

A nice feature of this distributed data lookup and route discovery process is that a single data query can return multiple route replies. The quality of these returned routes can be evaluated based on hop count (or any other path metric accumulated during the propagation of the query). The best route can be selected based on the relative quality of the route.

The inter-zone data lookup process based on IERP is distinguished from standard flooding-based query/response protocols by exploiting the structure of the routing/replicating zone. The zones increase the probability that a node can respond positively to a query. This is beneficial for traffic that is destined for geographically close nodes. More importantly, knowledge of the zone topology allows a node to efficiently continue the propagation of a query in the more likely case that destination can be found. At the same time, since the zones heavily overlap, the query will be forwarded to many network nodes, multiple times. To reduce the corresponding traffic, a query control scheme proposed by Haas [13] is adopted in our scheme.

4.3 Opportunistic Replication

Comparing with fixed networks, there exist many resource limitations in MANETs, for example, intermitted transmission, low bandwidth, poor connectivity, and unstable topology. At the same time, most nodes in MANETs also suffers from poor resources, for example, limited memory or storage space, short battery life, and unpredicted sleep or shutdown. Therefore, replication can not cause much additional network overload, which is determined by the characteristics of MANETs.

Our solution is opportunistic replication: data replication only performs with the occurrence of normal data accessing and transferring, which only consumes the energy and storage space of the nodes. Opportunistic replication is triggered by inter-zone data lookup as discussed in section 4.2. The data item that is not in the nodes within the zone of the requesting node is replicated into the node with enough free storage space within this zone when this data item is transferred from the hosting node to the requesting node. The following rules decide which node within the zone host the replica.


(1) The replica is first allocated to the peripheral nodes along the data accessing route.

(2) If the peripheral nodes along the data accessing route do not have enough free storage space, the replica is allocated to the interior nodes along the data accessing route.

(3) If the interior nodes along the data accessing route do not have enough free storage space, replica replacement procedure is invoked to evict the data replicas from the peripheral nodes when new data arrive. Replica replacement policy is the widely used LRU, which removes the least-recently-used data replicas.

In the intra-zone data lookup example shown in Fig.2, the replica of data item d2 is first allocated to H. if H does not have enough free storage space, it is allocated to C. if C does not have enough free storage space, H replace old replicas with the replica of data item d2.

Following these rules, no extra data transferring is needed to allocate data replicas. Due to the characteristics of MANETs, replica migration is restrictedly limited to reduce the network bandwidth and node energy consumption. When the node hosting the replica of a special data item is down or leaves the zone, we do not try to restore the replica until next access to this data item occurs. Every replica is created on demand. If there are more than one replica of a special data item existing in a zone, the redundant replicas can be removed and relieved storage space can host the replicas of other data items. However, this removing progress can only be triggered by the event that there is no enough storage space at any nodes in this zone to host the replica of new data items that does not exist at any nodes in this zone.

Since all the nodes are mobile, the nodes may join or leave a zone dynamically. IARP will sense the change in the network layer, and then trigger zone information maintenance process in the application layer to update corresponding zone information. If there are duplicated replicas after new nodes join, the duplicated replicas will be deleted later as mention above. We don’t try to predict which node will leave and move the replicas that leaving node hosts to other nodes in the zone because mobility predication is difficult in the practical environment and replica movement may result in communication overhead.

4.4 Consistency

There is a consistency issue in our replicating scheme. Due to network bandwidth, power constraints and node mobility in MANETs, it is too expensive to maintain strong consistency among replicas. In our scheme, a weak consistency model called δ-consistency model [14] is adopted, which is a time-based consistency model. The intuition is based on the fact that replicas are consistent even if their versions are different but has not passed a predetermined time δ (the valid period) since they have been updated last. There are applications such as weather maps, etc., where updates arrive periodically and application only needs to know a consistent value in a certain period.

Every data replica is assigned a valid period δd, and a data requesting node considers a replica up-to-date if δd>0. When opportunistic replication occurs, the owner decide the validation period δd of the data replicas based on updating interval and current data access time if the data requesting node gets the data from the owner.


If the data requesting node gets the data from other nodes hosting the replica, the value of δd of the new replica equals to the old one. Each node hosting the replica decreases its δd value in the same ratio.

The replicas with δd=0 can be removed from the hosting node to save storage space. The removing process is triggered later when there is no enough free storage space for new replicas. It is because the invalidated replicas may be still useful and indicate the users’ interests for special data items.

5 Performance Evaluation

We use the OPNET network simulator, an event driven simulation package, to evaluate the performance of our scheme over MANETs. Cross-layer zone-based replication scheme is evaluated over a range of zone radius, ranging from purely reactive flooding-based method (r=1) to purely proactive table-driven method (r=∞). Performance is gauged by measuring successful data access ratio, request delay and the control traffic generated by this scheme. We also compare the performance of our ZBR scheme with MPP.

Our simulated network consists of 200 mobile nodes, whose initial positions are chosen from a uniform random distribution over an area of 2500m by 2500m. We utilize 802.11b with a maximum data rate of 11Mbit/s as MAC. The Two-Ray-Ground propagation model has a maximum radio range of 250m.

The nodes move according to random walk mobility model. A node moves from its current location to a new location by randomly choosing a direction and speed from pre-defined ranges, [0,vmaxm/s] and [0,360o], respectively. Each movement occurs in a constant time interval, 10 [s], at the end of which a new direction and speed are calculated. If a node reaches a simulation boundary, it bounces off the simulation border with an angle equal to the incidence angle. Two vmax values, 2m/s and 20m/s, are studied in the simulation. We do not adopt widely used random waypoint mobility model because it has been proved to fail to provide “steady state” in that the average node speed consistently decreases over time [15]. This could lead to unreliable results.

There are 200 data items in the simulated network. Each node can host 10 data items. For each data item, the fraction of nodes hosting this data item is defined as replication rate. The mean replication rate is 20%. Two values of the size of data item, 2KByte and 2MByte, are studied in the simulation. Each node generates a single stream of data requests. The request generating time follows exponential distribution with mean value Trequest, 1 request/s. After a request is sent out, the node does not generate a new request until the request is served. The access pattern is based on uniform distribution. For MPP, the replication rate is also set to 20%, and the replicas are uniformly distributed in the nodes within the network.

The zone radius changes from 1 to 8 hops. The “hello” messages used to maintaining zone information are transmitted at random intervals of mean Thello. Thello is inversely proportional to the node speed, so networks with different mobility experience the same acceptable accuracy level of zone information.


Simulations were run on 50 randomly distributed node layouts, each for duration of 125s. No data was collected for the first 5s of the simulations while the initial intra-zone information maintaining process stabilized.

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Fig. 6. The successful data access ratio against mobility, the size of data item is 2KB

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Fig. 8. The control traffic against mobility, the size of data item is 2KB


Fig. 3 shows successful data access ratio as a function of zone hops. Our ZBR scheme outperforms MPP scheme with appropriate r value, 2-5 in our simulation. When r increases further, the performance of our scheme degrades. Successful data access ratio of our scheme is lower than that of MPP scheme. The reason is that the number of data replicas distributed in the network decreases when r increases. Furthermore, the overhead caused by zone maintenance becomes very large, and the information updates may not arrive in each node in time, which leads to inaccurate zone information. The intra-zone lookup process based on these stale information in the routing table and data lookup table may fail to find the requested data .

We also find the performance improvement with appropriate r values is more significant when the size of data item is large. It is because our scheme allocates the replicas around the data requesting nodes dynamically. Comparing with the random allocation in MPP, it makes the requesting node can find its requested data in closer node, which lead to shorter transferring route. In MANETs, shorter path has much longer lifetime than longer path. The probability that path breaks during data transferring decreases significantly. When the size of data item is small, data transferring time is short, this improvement can be observed but not very obvious. When the size of data item is large, data transferring need more time, this improvement is more obvious.

Another important performance metric is request delay. In our simulation, request delay is measured as time span from the request generating in the requesting node to the route establishing between the hosting node and the requesting node. This definition excludes data transferring time. Although transferring data items with larger size may occupy more network bandwidth and increases the request delay, it is not a significant factor. Fig. 4 shows the request delay as a function of zone hops when the size of data item is 2KB.

Our scheme achieves lower request delay than MPP scheme with appropriate r value. The request delay decreases with the increasing of r when r<6. When r further increases, the request delay begins to increase. Since inter-zone data lookup happens less frequently when r becomes larger, it looks like data requesting node can get most data items through intra-zone data lookup and the request delay should be lower. However, as we mentioned before, the overhead of maintaining a large zone is very large, which leads to inaccurate zone information and makes intra-zone data lookup process fail. Before the requesting node finds its requested data, it may experience several failed intra-zone data lookup process, and then the request delay increases significantly.

The overhead is gauged as control traffic caused by our scheme. Transferring requested data items from the hosting nodes to the requesting node is not counted as control traffic, which eliminates the effect of the size of the data item on the overhead. Fig. 5 shows the control traffic as a function of zone hops when the size of data item is 2KB. Our scheme achieves lower control traffic than MPP scheme with appropriate r value. Opportunistic replication does not cause extra replica migrating traffic, and δ-consistency model does not need extra traffic to maintain the consistency among the replicas either. As we discussed above, when r is larger, zone information maintenance causes too much control traffic and make the control traffic of our scheme is higher than MPP scheme.


As shown in Fig. 3, 4, and 5, when r = 1, the performance metrics for ZBR and MPP are very similar because both the underlying routing mechanisms are reactive. The data requests are flooded among the nodes within the network. When mobility increases, we notice that the performance difference becomes a little larger. Under this high mobility circumstance, our scheme performs better than MPP because AODV performs better than DSR. The simulation results shown in Fig.6, 7, and 8 demonstrate this trend.

Fig. 6, 7, and 8 illustrate the effects of mobility on the successful data access ratio, request delay, and control traffic respectively. We see that the optimal zone radius at which better performance can be achieved decreases as mobility increases. Increased mobility causes the network topology to change more rapidly, resulting in an increased of zone information update traffic. Therefore, successful data access ratio decreases, and request delay increases.

6 Conclusion and Future Work

In this paper, we focus on the cross-layer design between two major layers of the mobile end-system, the routing layer and the application layer. They work together to facilitate data access for various applications at the end-systems.

Specially, a cross-layer zone-based replication scheme for MANETs is developed, which provides flexible and efficient data access service with low overhead by integrating data replication, lookup and underlying ZRP routing protocol. Our simulations show that the overall performance of data access is improved. Through simulation we also find for any particular network configuration and performance demand, each node has an optimal zone radius. Our future work is to determine the best choice for the zone radius based on local information directly available.

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