Virtualized Multihop Access Networks for Disaster Recovery

Quang Tran Minh, Kien Nguyen, Shigeki Yamada

National Institute of Informatics, Tokyo, Japan

{quangtran, kienng, shigeki}@nii.ac.jp

Abstract—Disasters may destroy everything including

communication infrastructures isolating people in the disaster-

stricken areas. Recovery of these infrastructures is often

prolonged which is not suitable for disastrous fast-responses.

This paper proposes a wireless multihop access network

virtualization (WMANV) approach thereby users/victims are

provided Internet access transparently. Concretely, users are

provided Internet connection via multihop wireless access

networks as if they are connecting to conventional access points

(APs) using their commodity mobile devices. A tree-based

architecture was proposed to realize the concept of WMANV.

This approach allows participating mobile nodes (MNs) to

contribute on growing up access networks, thus provide the

Internet connection means to further disconnected MNs. The

feasibility and the scalability of the proposed approach have been

verified by real deployments and experimental evaluations.

Keywords- Wireless multihop access network virtualization,

WMANV, softAP, ad-hoc network, MANET.

I. INTRODUCTION

Natural disasters such as earthquake, hurricane, flood, cyclone, fire, etc., turmoil human activity, disconnect communication services [1]. Failure in communications and information exchange causes further heart-breaking crisis to human being [2]. Recent tragic disasters, such as the Great East-Japan Earthquake (Mar. 2011) or the Hurricane Katrina (Aug. 2005), show limitations of current communication technologies. More concretely, infrastructure-based networks, namely 3G, WiMAX, LTE, and even satellite, are vulnerable to disasters and take long recovery time when they disrupted.

In disasters, "safety" is the most important information for rescue and crisis mitigation. It is essentially demanded for people to be able to connect to the Internet to share their safety status as soon as possible. However, as mentioned above, the communication infrastructures have been completely damaged and recovery of these infrastructures is often complicated and prolonged. Therefore, strategic approaches to quickly setting up of resilient wireless access networks using on-site devices (laptops, smart phones,...) are essential for disaster recovery.

Wireless access networks such as mobile ad-hoc network (MANET) [3], wireless mesh network (WMN) [4], disruption/delay tolerant network – DTN [5] are self-configuring and self-healing networks of wirelessly connecting mobile nodes (MNs). If these networks are extended (via multihop communications) reaching still alive Internet gateways (IGWs), they can provide the Internet access to people in isolated/disaster areas. These networks are resilient for disaster recovery since they can be agilely configured using on-site battery-based mobile devices which are still working after disasters. The "resilience" here can be interpreted as the

ability of providing and maintaining an acceptable level of services in the face of various faults [6].

Current access network technologies mentioned above assume that special networking devices such as mesh routers (MRs) or ad-hoc routing compliant devices are always available to realize the multihop communications. These assumptions are unrealistic for disaster recovery since nobody knows where and when the disasters occur for such preparations. One of the suitable solutions is to have MNs downloading necessary multihop access network configuration software (NAS) on-demand from the Internet. However, it should be noted that before having the NAS running on MNs to configure a network no access network has been set up, thus no Internet access is available. This essential contradiction on multihop access network configuration has not been resolved in existing technologies. Moreover, according to our experiences on disasters, it is difficult for ordinary users, especially non-technical and elderly people, to manually configure such access networks. That is why it is difficult to find out effective access networks for disaster recovery in the real world.

This work proposes a new concept of wireless multihop access network virtualization (WMANV) in which users are provided a means to connect to the multihop access networks transparently as if they are connecting to conventional APs in infrastructure networks. More concretely, a tree-based architecture dedicated to virtualized multihop access networks is proposed. The access network (i.e. the tree) is gradually grown up, by the contributions of joined/connected MNs, until nodes in the disaster-stricken areas are reached. Under this approach, the aforementioned contradiction on network configuration is naturally resolved.

The rest of the paper is organized as follows. Section II reviews related work. The concept of WMANV as well as the realization methods for this concept will be presented in Section III. In Section IV, connectivity analysis and appropriate solutions to improve the connectivity/scalability of the proposed approach are thoroughly discussed. Practical experiments are presented in Sections V. Section VI concludes this work and draws out future work directions.

II. RELATED WORK

Existing mobile communication technologies, namely 3G, WiMAX, LTE, or even satellite [7] are powerful in terms of transmission range and coverage. However, their power supply and antenna systems are vulnerable to tsunamis or earthquakes. Resilient wireless access networks such as mobile ad-hoc network (MANET) [3], wireless mesh network (WMN) [4], disruption/delay tolerant network – DTN [5] are feasible solutions for disastrous fast-responses.

978-1-4673-5828-6/13/$31.00 ©2013 IEEE

One of the most important features in MANET and WMN is multihop communications thereby two far apart MNs can communicate with each other via hop-by-hop packet forwarding. In MANET, participating nodes can be mobile while WMN focuses more on backhaul networks of MRs. DTN is an advanced version of MANET supporting the so-called "in-network storage" capability to cope with severe disruptions and long delay communications. However, DTN is not matured enough to be applied in real world applications compared to its counterparts, namely MANET and WMN. Since access networks can be quickly configured on-demand without existence of any network infrastructure, these technologies are promising for disaster recovery.

One of the most important requirements for disaster recovery access networks is the connectivity, meaning that how to provide the Internet access to isolated victims. It is reasonable to assume that somewhere outside the disaster-stricken areas some IGWs are still alive. The difficulty is how to build the "bridge" from the isolated victims to one of the IGWs. According to our experiences on disasters, approaches proposed in existing technologies cannot properly work as analyzed below:

There are two main streams on wireless access network researches in the last decade. The first direction focuses on wireless mesh backhaul network technologies. These studies were dedicated to develop robust MRs in which transmission power, collision avoidance, throughput improvement are considered [8]. However, this approach cannot be applied in the context of disaster recovery since it requires pre-deployment of MRs which cannot be satisfied in real disaster recovery. The second trend is to propose a more flexible mesh architecture, namely "client mesh network" or MANET [3] which is a mesh network created by client devices. In this trend, effective ad-hoc multihop routing protocols considering the nodes' mobility such as AODV, OLSR, etc., [9] and network auto-configuration mechanisms are the main research issues. As an ideal assumption, the network configuration and routing utilities/software are installed on MNs in advance for automatically configuring of MANETs when MNs are placed close with each other. However, this assumption is unrealistic in disaster recovery when only commodity mobile devices (laptop PCs, tablet PCs, smart phones, ...) are available.

In order to overcome the aforementioned difficulties, more strategic approaches should be considered. Commonly, people in the disasters are non-technical users. They cannot manually set up such complicated ad-hoc multihop networks. In this work, a wireless multihop access network virtualization (WMANV) approach is proposed so that the networks are automatically configured transparently to the original users. In this model, users can connect to the multihop access networks as if they are connecting to conventional APs. Of course, the network auto-configuration mentioned above must be conducted based upon the support of network configuration software (NAS). This software can be downloaded once users successfully connect to the Internet following the tree-based scheme. As a result, the access network (i.e. the tree) is gradually grown up by the joining MNs until nodes in the disaster-stricken areas are reached. We believe that the concepts of wireless multihop access network virtualization and tree-based architecture are firstly proposed which will open a new research direction in disaster recovery access

networks. The details of the proposed approaches are presented in the following sections.

III. TREE-BASED VIRTUALIZED MULTIHOP ACCESS

NETWORKS

This section proposes a novel approach to access network virtualization based on the tree-based architecture. Here, commodity mobile devices (without any special pre-installation) are opportunistically utilized to configure resilient access networks for disaster recovery.

A. Tree-based Architecture

As mentioned, the network configuration contradiction can be interpreted as: "which must be available first among the NAS and the Internet connection". More concretely, to setup a network the NAS is needed. Mean while, to have the NAS installed in MNs, it must be downloaded from the Internet, thus the Internet connection must be available before hand.

3

4

5

2 IGW1

Phase 1

Isolated(b)

3

4 2 IGW1

Isolated

Phase 1Phase 2

5

(c)

3

4

5

2 IGW

1

Isolated

Backbone

Network (a)

3

4 2 IGW1

New commers

Phase 1Phase 2

5

67

Phase 3

(d)

3

4 2 IGW1

5 6

7

(e)

Figure 1. A tree-based structured access network

In the conventional MANET, it assumes that the NAS is available in advance so that the MANET can be configured whenever MNs are close with each other. However, this approach cannot properly work in the disaster recovery since such special software is not always available in commodity mobile devices. As a result, the group of isolated users (in the disaster areas) cannot access the internet as shown in the upper part of Fig.1 (Fig. 1a). Here, an IGW is still alive connecting to the Internet backbone but it cannot be reached by a far apart group of isolated MNs. At the same time node 1 is entering the disaster area (e.g. the node is carried by a volunteer). This node can "bridge" the gap between the isolated group and the IGW. However, no NAS is installed on node 1 neither on each node in the isolated group to configure a multihop access network bridging the isolated group and the IGW.

We propose a new concept of "wireless multihop access network virtualization" (WMANV). In WMANV, users can

connect to access networks transparently as if they are connecting to conventional APs. This virtualized multihop access network can be realized by applying a tree-based architecture where the network configuration is conducted in the reverse way of the conventional approach. The lower part of Fig.1 (Fig. 1b to Fig. 1e) depicts this architecture. As shown in Fig. 1b, the network is configured starting from the IGW. At phase 1, node 1 connects to the IGW as a common wireless station (STA). Once node 1 connects to the IGW, a trigger is fired on the IGW forcing node 1 to download and install the NAS from the Internet. This software transforms node 1 to a software-defined AP (SD_AP). This SD_AP provides a connection means for any nearby mobile node. At phase 2 (Fig. 1c), node 2 connects to node 1 as if connecting to a common AP, it is forced to download the NAS by a trigger on node 1. This procedure is iterated at node 2 providing the Internet access to its surrounding nodes, namely nodes 3, 4, 5 at phase 3 (Fig. 1d). At this phase, the isolated group is fully "bridged" to the IGW so that all the isolated nodes can connect to the Internet. Fig. 1e shows that the newly configured multihop access network can accept any newcomer (e.g. nodes 6, 7).

B. Implementing Tree-based Virtualized Multihop Access

Networks

To realize the tree-based virtualized multihop access networks as shown in the Fig. 1e, every node must be capable of connecting to different networks simultaneously. Concretely, on one hand, an MN works as a common wireless STA to connect to the nearby AP (either the actual AP or the SD_AP). On the other hand, it must serve as an AP (SD_AP) for further nodes. Commonly, to fulfill this requirement, multiple network interface cards (NICs) are needed. However, this condition is impossible for commodity devices. Installing additional NICs into MNs on-demand is also unrealistic.

Figure 2. From the wireless virtualization to access network virtualization

In order to solve the aforementioned dilemma, an idea of transforming from the wireless virtualization (WV) [10] to the WMANV is proposed. The WV abstracts a single physical NIC into multiple virtual NICs thereby a single MN can connect to different networks simultaneously as shown in Fig. 2 (on the left). In this work, this technique is applied for WMANV as shown in the right part of Fig. 2 where a single NIC on a laptop (PC0) is virtualized into 2 virtual NICs. One of the virtual interfaces connects to the AP in its common infrastructure mode and the other one serves as a SD_AP providing connection means to the surrounding MNs such as PC1. The work in [11] is closely related to this work where a node can work both in common STA and AP modes at different virtual NICs. However, in [11] WV was mainly utilized on energy saving (actual APs are replaced with SD_APs at off-peak

times) and on soft handover realizations. No discussion on on-site installation of NAS and network configuration was given. Therefore, that work is completely different to the approaches proposed in this paper.

Turning back to the Fig. 1e in the previous section, a single NIC in each MN is virtualized into 2 virtual NICs: one works as a common station mode and the other works in an access point mode. This implementation realizes the proposed tree-based WMANV scheme. It should be noted that the WV functionalities and the software-defined access point (SD_AP) functionalities are encapsulated in the NAS which is stored in a specific web server for MNs to download when they connect to an AP. Microsoft wireless hosted network [12] is one of the examples of NAS. The captive portal technique [13] can be applied to trigger this download process whenever an MN connects to an AP.

C. Routing in Tree-based Virtualized Multihop Access

Networks

One of the advantages in the proposed tree-based WMANV is that routing protocol becomes simple. Uplink packets (packets from MNs to IGW) are straightly forwarded from the corresponding SD_AP to the next hop, namely its connecting AP. The tree-based architecture assures that each node has one and only one connecting AP. For the downlink packets, since each intermediate MN is a SD_AP with an efficient address management mechanism to manage the list of nodes that are connecting to it, it can recognize which nodes the packets should be forwarded to.

Another important aspect should be considered is the link failure in the tree-based architecture. In the tree-shape network, any single link failure results in disconnection of all nodes in the sub-tree it serves. We propose a simple yet effective path rediscovery method to resolve this issue. Each node maintains 2 lookup tables, namely connecting and supporting tables described as follows:

Connecting_Tab(node_ID)

Supporting_Tab(SSID, hop_count, status)

The connecting table stores all the nodes (node_ID) that are connecting to the considered node which is serving as a SD_AP. For example, the node 2's connecting table contains nodes 3, 4, and 5 (Fig. 1e). The supporting table contains information about APs (represented by SSID) which can serve the node's connection. hop_count is the number of hops from the SSID to the final IGW (e.g. the actual AP). The status describes the status of the corresponding SSID. There are three status, namely connecting (i.e. the node is connecting to this SSID), active (i.e. this SSID is ready for the node to connect), and inactive (the SSID has disappeared). This table is sorted by the increment of hop_count and the node is connecting to the SSID in the first record (lowest hop_count). For example, in Fig. 1e, after scanning, node 5 finds 4 nodes (nodes 2, 6, 4, and 7) as its supporting APs (SD_APs). Currently, node 5 connects to node 2 and its supporting table is shown in Table I.

Having this data structure stored and updated in each node combining with the proposed tree-based approach, the path rediscovery becomes simple. For example, if the link between node 2 and node 1, namely Link2_1, is failed because node 1 moves out of the node 2's sensing range, and node 2 (i.e. AP2)

cannot find any alternative path then it must be inactivated. When inactivating, node 2 informs its connecting nodes (nodes 3, 4, 5) this status. Node 5 updates its supporting table by changing the status of the corresponding record (i.e. SSID = AP2) to "inactive". It then hands over to the next active supporting AP, namely node 6 (the current lowest hop_count AP) to maintain its Internet connection.

TABLE I. NODE 5'S SUPPORTING TABLE

IV. CONNECTIVITY ANALYSIS AND IMPROVEMENT

Connectivity can be expressed as the capability of far apart MNs connecting to the IGW where data transmission speed is acceptable (e.g. as the speed of the dial-up technology which is around 56Kbps). Obviously the connection must be established via multihop communications. Therefore, connectivity is affected directly by the multihop throughput degradation. This relationship is thoroughly analyzed and sound solutions that improve the throughput resulting in connectivity/coverage improvement are proposed.

A. Throughput Degradation and Spatial Reuse

For simplicity, static multihop access networks are considered where a single wireless channel is shared for transmissions. In the IEEE 802.11 half-duplex Distributed Co-ordination Function (DCF) protocol, only a half of the link available bandwidth is utilized for communications between any pair of nodes. Therefore, the throughput degrades almost a half per each hop in multi-hop communications. Let denote lb the minimum bandwidth required for an acceptable Internet connection using TCP/IP protocol, which is defined as 56Kbps in the legacy dial-up network; n the maximum bandwidth of the wireless medium; k the number of hops between two end nodes. The relationship between these parameters can be described in (1).

bkl

n

2 (1)

From (1), the maximum distance in terms of number of hops (i.e. k) between the furthest node and the IGW, can be inferred in (2).

)(log 2

bl

nk (2)

For example, if the IEEE 802.11g is utilized where the maximum bandwidth is 54Mbps (ideally), and lb = 56Kbps, then the maximum number of hops is 10 as calculated in (3).

914.9)1056

54(log 3

2 k (3)

In practice, the average transmission range between two IEEE 802.11g nodes in a single hop is around 100m revealing average network coverage as 1000m (10hops x 100m). This

coverage is still modest in real disaster recoveries where the still alive IGWs are commonly several kilometers far apart from disaster-stricken areas.

Obviously, in order to improve the number of acceptable hops, the multihop throughput degradation must be reduced. Channel utilization (i.e. spatial reuse) [14] is an applicable mechanism. Nodes that do not contend the medium with each other should transmit concurrently to optimize the channel utilization as shown in Fig. 3. Here, node N5 is out of the interference ranges of both N1 and N2, it can transmit to N6 concurrently with the transmission pair N1-N2. Similarly, pairs N2-N3 and N6-N7 can transmit simultaneously without any collision. It should be noted that N3 is in the interference range of N2. Meanwhile, N4 is the hidden node of the transmission pair N1-N2, its transmission to N5 may cause collision at N2.

N1 N2 N3 N4 N5 N6 N7 N8 N9

Figure 3. Pairs N1-N2 and N5-N6 can transmit simultaneously

The aforementioned spatial reuse mechanism limits the throughput degradation until 4

th hop. From 5

th hop the

throughput is kept almost stable as that of the 4th hop.

Theoretically, the network can be extended unlimitedly keeping the overall throughput as high as that of the 4 hops chain. It is worth to note that when the receiving node is deployed far apart (even in the transmission range) from the sending node, the signal strength degrades revealing lower transmission rate due to the auto-rate algorithm in IEEE 802.11 [15]. This also affects the overall throughput. However, this effect is not significant compared to the exponential throughput reduction under multihop communications as discussed above. This point will be confirmed in the evaluation section.

B. Gateway Selection

The spatial reuse mechanism can be utilized only in the ideal placements of nodes by which the distance between adjacent nodes is about the transmission range. In practice, this situation is unusual. In contrast, nodes may be very close to each other (e.g. laptops in the same office) revealing unnecessary multihop connections between any end-to-end pair even though they can connect directly. Therefore, it is essential to propose an adaptive gateway selection (AGS) mechanism by which an MN can select the "right" gateway/AP so that it can connect to the final IGW via a minimum number of hops. Figure 4 illustrates this mechanism.

Figure 4. Appropriate selection of Gateways

Assuming that 5 nodes are in the transmission range of each other and N5 is the gateway for the outside part. In the left, each node selects the nearest node, based on the radio signal strength indicator (RSSI) for example, as its direct gateway (connecting AP). Here, 4 hops are created to provide a connection from N1 to N5. In the right, every node connects

SSID Hop_count Status

AP2 2 Connecting

AP6 2 Active

AP4 3 Active

AP7 3 Active

N1

N2

N3

N4

N5 N1

N2

N3

N4

N5

directly to N5. The throughput from N1 to N5 of the cases in the left and the right, namely Tleft and Tright, can be presented in equations (4) and (5), respectively. Here, m is the maximum available bandwidth of the wireless link, and k is the total number of nodes except the final gateway (e.g. N5). Obviously, Tright is larger than Tleft in all the cases when k is larger than 1.

422

mmT

kleft

(4)

4

m

k

mTright

(5)

An emerging issue is how a node can directly select the appropriate (the furthest) gateway. RSSI can be used as the RSSI from the furthest node (N5) is the lowest one detected by the considered node (N1). However, since all the nodes are close to each other, they may affect their RSSIs revealing some errors.

As mention in section III.C, the information of connecting AP and its corresponding hop_count in a node's supporting table (Table I) can be effectively used for other nodes on their appropriate gateway selections. For example, after connecting to N5, N4 describes N5 as its connecting AP whose hop_count is 0 (N5 is the final gateway). When N3 want to join the network, it scans and finds two candidates, namely N4 and N5 (the RSSIs detected from N4 and N5 may be comparable). Based on the aforementioned information extracted from the supporting tables of N4, and N5, node N3 is aware that it should connect to N5 rather than to N4 since N4 is just a bridge for the final connection to N5. This simple yet effective mechanism significantly reduces the number of hops between the MN and the IGW thus improves the throughput of the whole network.

V. EVALUATIONS

This section evaluates the feasibility and the scalability of the proposed tree-based WMANV approach. For intuitively verifying the feasibility of the proposed scheme, a tree-based access network was set up. Several websites including those providing multimedia services such as video streams have been visited. One cannot recognize any disruption or delay even for video streams viewed on the furthest PC which is 7 hops from the actual AP (IGW).

For further analyzing the connectivity in terms of number of hops accepted by the proposed network, a part of the previous network (a sub tree) was kept as shown in Fig. 5. Here, the multihop throughput degradation considering the effect of spatial reuse and AGS mechanisms discussed in the previous section is verified.

Figure 5. A chain of connected PCs in WMANV

A network evaluation tool, namely the Iperf [16], was utilized where an Iperf server was installed on the PC0 and an Iperf client was installed on each PCi (i = 1...7). Each client (PCi) sent packets, using TCP, to the server (PC0) as fast as possible. The evaluation parameters are presented in Table II. Every experiment was conducted in 100s and the average

throughput (the average of a 100s-section experiment) reported by Iperf were recorded. For each client, five continuous experiments were conducted and the average of the reported values (i.e. the average values of the 5 different 100s-section experiments) was calculated. It should be noted that at a given time only one client sent TPC packets to the server (PC0) while intermediate PCs merely served as forwarders.

TABLE II. EXPERIMENT PARAMETERS

Parameter Value TCP window size 64KB

Buffer length (in Iperf) 8KB: Iperf works by writing an

array of 8KB continuously

Maximum Transmission

Unit (MTU)

1500 Bytes

Evaluating duration 100s

Wireless link IEEE 802.11g/54Mbps

Firstly, Fig. 6 shows the throughput of transmissions in a single hop with regards to the change of RSSI. The sender was kept at a fixed location and the receiver moved further apart. At each location, RSSI and throughput of the received packets were measured. As shown, the higher the RSSI is, the better the throughput is. This is mainly because of the auto-rate algorithm provided by IEEE 802.11 [15] to adapt to the change of RSSI. However, the throughput is stable within a relevant RSSI range, namely larger than -65dBm. This result provides a hint for setting the nodes' locations in further experiments.

Figure 6. Throughput between 2 nodes w.r.t RSSI

For further experiments, two scenarios were created: (a) all the nodes were located close to each other (i.e. in the transmission range of each other), and (b) adjacent nodes were far apart so that the interference between nodes was minimum while keeping RSSI at around -65dBm to assure a good connection. To keep RSSI at around -65dBm, the distance between two nodes was about 70m to 90m. Figure 7 shows the throughput of multihop communications in the two aforementioned scenarios. When nodes were close to each other, the throughput degrades almost a half per each hop, revealing dramatic throughput degradation. Here, when the number of hops was 7 the throughput became as low as 0.3Mbps. This significant throughput degradation hinders the scalability of the system. In contrast, when nodes were far apart from each other, the spatial reuse mechanism could be utilized. As a result, after 4 hops the throughput became stable at around 1.8Mbps which is definitely good enough for any web-based application. This result confirms the scalability of the system if the nodes are "right" located. Concretely, the coverage of the

...

PC0 APPC1PC2PC7Internet

proposed network can be extended unlimitedly since the multihop throughput becomes stable after 4 hops.

Figure 7. Throughput comparison w.r.t different deployments of nodes

Figure 8. Effectiveness of the proposed gateway selection mechanism

As discussed in Section IV.B, the proposed AGS mechanism helps to increase the throughput of every connection giving a network with the same number of MNs. Let k be the number of nodes around a given IGW. Figure 8 shows a numerical analysis for the effectiveness of the proposed AGS method in terms of throughput of transmissions from the furthest node (among the k nodes) to the IGW. Obviously, the proposed approach becomes prominent when the number of nodes reaches 2. One of the interesting points is that the furthest node in the group of k nodes may latter serve as a gateway (SD_AP) for other group of nodes. Therefore, its transmission performance to the IGW is very important in improving the scalability of the whole access network. As shown, when the number of nodes reaches 8, the throughput of the conventional hop-by-hop approach degrades to around 150Kbps which is too slow for a node to serve as a gateway. In contrast, in the proposed AGS approach, throughput is kept as large as about 2Mbps which is relevant for a node serving as a gateway for other networks.

VI. CONCLUSION AND FUTURE WORK

This paper proposed a novel approach to wireless multihop access network virtualization (WMANV). In this approach users are provided the Internet access via multihop access networks transparently as if they are connecting to conventional APs in infrastructure networks. While connecting to a virtualized multihop access network, participating MNs contribute to the growth of such a network by playing as intermediate nodes in the tree-based architecture.

A reasonable realization scheme for the proposed WMANV approach considering strict requirements in harsh environments of disasters was thoroughly discussed. More concretely, only commodity mobile devices with a single off-the-shelf IEEE 802.11 family NIC are required for configuring the proposed virtualized multihop access networks. The proposed tree-based

architecture does not only simplify the network configuration (e.g. routing and path rediscovery) but also provides a natural way for setting up access networks from scratch. This approach completely resolved the so-called network configuration contradiction remained in the existing MANET technologies.

Real deployments and experimental results reveal the preliminary feasibility and scalability of the proposed approach. Further improvements of throughput with regards to the increment of the number of hops and the number of concurrent connecting users are interesting research directions. Moreover, further real-field experiments must be conducted to confirm the effectiveness of the proposed solutions. We believe that this approach will open a new research direction in disaster recovery access networks.

REFERENCES

[1] M. Portmann, and A. A. Pirzada, “Wireless Mesh Networks for Public Safety and Crisis Management Applications,” IEEE Internet Computing, Vol 12. No.1, pp.18-25, 2008.

[2] R. A. Lawson, “Tsunami Detection Systems for International Requirements,” OCEANS07, pp.1-7, Vancouver, Canada, Sep. 2007.

[3] J. C. Kim, D. Y. Kim, S. M. Jung, M. H. Lee, K. S. Kim, C. K. Lee, J. Y. Nah, S. H. Lee, J. H. Kim, W. J. Choi, S. K. Yoo, “Implementation and Performance Evaluation of Mobile Ad hoc Network for Emergency Telemedicine System in Disaster Areas,” 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 1663-1666, Minneapolis, Minnesota, USA, Sep., 2009.

[4] M. Portmann, and A. A. Pirzada, “Wireless Mesh Networks for Public Safety and Crisis Management Applications,” IEEE Internet Computing, Vol 12. No.1, pp.18-25, 2008.

[5] M. Y. S. Uddin, H. Ahmadi, T. Abdelzaher, and R. Kravets, “A Low-energy, Multi-copy Inter-contact Routing Protocol for Disaster Response Networks,” IEEE Sensor, Mesh and Ad Hoc Communications and Networks, pp. 1-9, Italy, Jun. 2009.

[6] J. P. G. Sterbenz, D. Hutchison, E. K. Cetinkaya, A. Jabbar, J. P. Rohrer, M. Scholler, and P. Smith, “Resilience and survivability in communication networks: Strategies, principles, and survey of disciplines, Computer Networks,” Vol. 5, pp.1245-1265, 2010.

[7] N. Uchida, K. Takahata, Y. Shibata, N. Shiratori "Never Die Network Extended with Cognitive Wireless Network for Disaster Information System". CISIS 2011, pp.24-31, Seoul, Korea, Jun. 2011.

[8] E. M. Mohamed, D. Kinoshita, K. Mitsunaga, Y. Higa and H. Furukawa, "An Efficient Wireless Backhaul Utilizing MIMO Transmission and IPT Forwarding," International Journal of Computer Networks, IJCN, vol. 2, No. 1, pp.34-46, Mar. 2010.

[9] H. Bakht, "Survey of Routing Protocols for Mobile Ad-hoc Network", International Journal of Information and Communication Technology Research, pp. 258 - 270, Vol. 1, No. 6, 2011.

[10] R. Chandra, P. Bahl, “MultiNet: Connecting to Multiple IEEE 802.11 Network Using a Single Wireless Card ,” IEEE INFOCOM, pp. 882-893, Hong Kong, Mar. 2004.

[11] Y. Al-Hazmi, H. D. Meer "Virtualization of 802.11 Interfaces for Wireless Mesh Networks," 8th Int'l Conf. on Wireless On-Demand Network Systems and Services, pp. 44-51, Italy, Jan., 2011.

[12] Wireless hosted network "http://msdn.microsoft.com/en-us/library/windows/desktop/dd815243%28v=vs.85%29.aspx," access Mar. 2013.

[13] Captive portal "http://en.wikipedia.org/wiki/Captive_portal," accessed Mar. 2013.

[14] Z. Fu, P. Zerfos, H. Luo, S.Lu, Li Zhang, M. Gerla "The Impact of Multihop Wireless Channel on TCP Throughput and Loss," INFOCOM03, pp. 1744-1753, San Francisco, Mar., 2003.

[15] V. Bahl, R. Chandra, P. P. C. Lee, V. Misra, J. Padhye, D. Rubenstein, Y. Yu "Opportunistic Use of Client Repeaters to Improve Performance of WLANs," CoNEXT08, Dec., 2008.

[16] Iperf, " http://iperf.fr/," accessed Mar. 2013.