Topology Adaptation to Services in Wireless Networks in Motion (NEMO) Johnson I Agbinya and Gina Paola Navarrete

School of Computing and Communications Faculty of Engineering and IT, University of Technology, Sydney Australia

AbstractThis paper proposes adapting dynamic network topology to match changing quality of service requirements in real-time wireless broadband networks. Based on modelling and drive tests, thresholds ensuring the quality of links for specified services are established. A method for matching network topologies according to link quality and capacity to IP services is presented. A service link quality matrix (SLQM) between mobile hosts according to the services supported is proposed and used. The matrix determines whether there is suitable and stable connectivity between two mobile hosts for specified service provisioning.

Dynamic Network Topology Prediction It is well known that offering of real-time IP services in fixed networks is very difficult and is often undertaken by combining the functions of many protocols such as real time protocol (RTP), real-time control protocol (RTCP), resource reservation protocol (RSVP) and many others including session initiation protocol (SIP) and MPLS. This makes the provisioning of the service highly complex and demanding of system resources. Offering real-time IP services in wireless networks in motion is even more complex and harder. The complexity is increased further because the network is moving as a whole unit and links can be made and broken routinely. Links in wireless network are highly dynamic and prone to rapid quality changes. Mobility exacerbates the problem further leading to more quality deterioration and instability of wireless links and hence understanding wireless channel characteristics and how they affect the provisioning of services in mobile networks has emerged as an important area of research. Wireless networks in motion (NEMO) are prone to rapid link degradations and hence reduce offered quality of service too often. Recently several approaches have been adopted in current literature for reducing link and topology instability. The methods include topology control [1] and topology prediction and convergence [2]. Topology control advocates posit that it is possible to maintain instantaneous network topology and to establish control for routing before it changes dramatically. Unfortunately, in a highly dynamic environment where hosts are highly mobile, the topology changes

very rapidly, node discovery and topology control updates become very frequent. To date most ad hoc network routing protocols including AODV [3], DSR [4] and OLSR [5] depend on route discovery either proactively or on demand. Route discovery unfortunately leads to large overhead traffic [6] and causes significant delay when routes are established. Consequently most of the ad hoc network protocols are not suitable for real-time IP communications [6] which require low delay and stable network environments. Recently a new approach was introduced in [2] to reduce the inherent delay in ad hoc networks that is associated with route and topology discovery. Instead of elaborate topology discovery, topology convergence based on prediction of the location of nodes using the mobility of neighbouring nodes was introduced [2]. In topology convergence (TC) the positions of neighbouring nodes are predicted and used to predict and update the instantaneous topology of the dynamic network. The objective in topology convergence is first to eliminate and or reduce as much as possible the overhead and delays associated with topology control and discovery. In TC, nodes do not need to propagate the location update information to their neighbours nor routing table information. Rather, each node updates its own routing table by estimating the location of the other nodes. This reduces the overhead traffic associated with ad hoc network protocols. The basic concept of Topology convergence is to update the routing tables of dynamic wireless networks while the topology is changing which differs from other routing protocols because all other protocols update their routing tables after the topology of the network has changed. The authors demonstrate in [2] that topology prediction method reduce delays in the network and out perform existing routing protocols such as DSR and AODV which depend on route discovery proactively or on-demand. This paper builds upon the concept of topology prediction [2]. When two nodes know their mutual locations and the signal strength measured from the link between them, strategic decisions can be taken about the quality of the link and its suitability for carrying packets requiring particular quality of service (QoS). Hence in situations of normal IP routing or when forward equivalence classes (FEC)

Third International Conference on Broadband Communications, Information Technology & Biomedical Applications

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DOI 10.1109/BROADCOM.2008.53

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are used in MPLS, nodes are able to quickly decide which path best matches an FEC or QoS. In what follows the words host, node and access point are used freely to mean the same thing. Base stations are also referred to as access points (AP).Quality of Wireless Links There are several approaches for analysing the reliability of wireless links between two mobile access points (hosts). One method depends on the coverage range of the access point and the second depends on the velocity between two hosts. The received signal power depends greatly on the distance between the two hosts and is modelled by the Friis equation. The coverage range approach transforms to the reliable method of measuring the strength between hosts. The objective of each host therefore includes measuring the received signal strengths from its neighbours. By measuring the signal strength and the noise power in a link, the signal-to-noise ratio (SNR) of the link directly provides a measure of the link capacity through Shannon’s popular equation .Hence this method is important for determining whether there are reliable links to support the required services with required link capacity C. It is known in practice that different services require different link capacities. This is formally established in network standards. For example a video call requires ‘stronger’ link qualities far above the simple requirements for voice calls. A ‘strong’ link has high power and low noise levels (hence large capacity).

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Consider for example that the nodes are a mix of 3G mobile base stations (node Bs). The information exchanged between the handset and the base station when a call is being handed over between neighbouring base stations includes reports on the measured signal strengths in the network. This information can be used for other purposes (in addition to handoff) to meet quality of service requirements. This paper proposes combining the information on the location of mobile hosts with the measured signal strengths in the links as seen by the mobile host to decide in real-time which link should be used for sending the packet towards its destination. We posit that a node need not know the whole route to the destination but knowledge of just one good link in the direction of the destination is enough at each node to decide a path segment to use. This decision is made by each node downstream until the packet arrives at its destination. The real benefit of this method is optimisation of the path quality and matching of path quality to service quality in real-time and matching of the dynamic network topology to changing QoS.

Generally the function of measuring signal strengths of neighbouring base stations is performed by mobile communication handsets. All mobile phone handsets contain transceivers and thus can be modified to ad hoc network nodes if they are made to listen to each other. Adding node localisation algorithms to handsets increases their capabilities further. In today’s terms they are unfortunately never used in that form in ad hoc network modes for creating wide area networks. In the emerging fourth generation (4G) networks a key desirable feature of mobile terminals (hence called hosts) is to facilitate the establishment of mobile broadband wide area networks when required using mobile hosts.Topology change and hence path change is particularly profitable in high node density network environment where nodes interfere with each other and several paths downstream can be created to the destination. Hence in the following sections, we assume that there is significant number of network nodes close to the transmitting node and within its coverage range.

Adaptation of Topology Services In pursuit of topology adaptation we use several third-generation (3G) handsets to measure the signal strengths from neighbouring base stations. In 3G the information regarding the control of the quality of the signal is exchanged between handsets and the fixed network while the phone is moving around. Handsets from different vendors however work differently and exchange different messages with the network. Therefore the paper also studies handsets from different vendors (Nokia and Samsung). Assume a vehicular network where each vehicle carries a mobile router. Assume too that the positions of the routers are updated periodically with their nearest neighbours. Assume further that the vehicular network is used to offer broadband services to passengers. Hence continued connectivity and handover of sessions and terminals occur. We have described this network in details in [7-9]. The topology of vehicular networks is dynamic and there are enough signal indicators to help establish the most suitable topology to meet the quality of service requirements of a service. Each mobile host sees many links from many other neighbouring hosts within its coverage range and hence has a rich set of information not just for handover of calls but also to dynamically decide the paths that packets should take to their destinations. For the sake of the explanations, we assume the vehicular network is a mobile 3G network deployed in an urban setting on buses. Current 3G terminals measure the RSCP per link and also the signal-

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noise-ratio (Ec/No) per code, which are both clear indicators of the quality of the links. These parameters are hence suitable for deciding the best topology to meet the requirements of an FEC or QoS. In 3G the parameters Ec/No and RSCP are directly related to each other, as in equation (1):

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is the power of the cell in the ‘active set’ of the phone in watts. Thus the mobile hosts provide information about the conditions of the links with the other hosts around the area and each host keeps track of this information. We use this information to classify the links in order to adapt the dynamic network topology to services. It is also used to build topologies with different link qualities. Different topologies with different link qualities can therefore be constructed to provide communications for different services with different link requirements.

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The adaptation of the network topology is as follows. Each host captures information about the quality of the links with other hosts around it using a record of the values of Ec/No and RSCP. The information is used to generate two matrices, one for RSCP or power values and the other for Ec/No from which we obtain interference values. Equations (2) and (3) are examples when four hosts are monitoring the links between themselves. These two matrices need to be combined in order to determine the quality of the links for the mobile host to provision the network service (Voice calls, video call, etc) with the best topology segment. It is proposed here that the links

be prioritised according to quality depending on the service they can support.

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After combining the matrices in equations (2) and (3), the resulting output is the quality of the link matrix. This new matrix given in equation (5) provides information about the service that can be provisioned with the links. For instance, video is highly demanding of link capacity as is data-transfer, while voice is less demanding. Three main services were considered: voice calls, video calls and data transfers. Each service has different QoS (link quality) requirements for the minimum values of RSCP and Ec/No. These are given as thresholds before the calls drop out. Let the link quality be defined as the pair of variables ( ,β α ) where in the 3G case the pair is (Ec/No, RSCP). For instance, in UMTS networks, the minimum values for (Ec/No, RSCP) = (-20 dB, -120 dB) and for video (-10dB, -95 dB). For data transfer these values vary according to the speed used: for 64Kbps and 128Kbps (Ec/No, RSCP) = (-13dB, -113 dB); and for 384Kbps is (-9.5dB, -93 dB). However, these values can vary between different equipment supplied by different vendors (e.g. Nokia, Alcatel, Samsung and Sony Ericsson) due to their differing sensitivities. The determination of the type of service that can be supported by each link is defined by the following mathematical relation in equation (4):

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Figure 1: Values of RSCP and Ec/Io collected by the Nokia handsets displayed using Actix.

RSCP and Ec/No thresholds are the minimum required values to support the different services (eg. voice, data, video and IPTV). After applying equation (4), the resulting service link quality matrix (SLQM) for four hosts monitoring the links between themselves is:

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is used to decide the service path between hosti and hostj resulting from the equation (4). Figure 2 shows the profile of measurements collected with a Samsung handset and analysed with NEMO Tools software. This software is similar to Actix software, but NEMO is also used to collect the measurements. From Figure 2, it can be observed that the handset reports the power values (RSCP) of the active set, the monitored and detected set. The

active set represents the base stations that are currently serving the phone. The detected set is the base stations that can potentially serve the phone in case the active connection is lost due to degradation of the link it is using. Here the base stations in the active set are physically connected to the base stations in the monitored set; they are all part of the topology. However, the topology may be modified dynamically by the network operator. Therefore the detected set is a strategic extra feature of this particular handset. These measurements can be used to identify missing links required for connections in the network; this is used to change the topology of the network. Unfortunately in today’s networks, this process is not undertaken during the measurement. This is because in 3G networks the handsets follow instructions from the network and cannot automatically make decisions about their network configurations. For future networks however, this paper proposes enabling handsets to use these measurements to find the instantaneous optimum path and topology of a network in real-time while the base stations are constantly moving. Today’s mobile handsets do not decide which base station they should connect to but may suggest to

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the network a good new set of links for the network to automatically update its topology. If this were possible, this would allow the topology of the mobile network to be built according to each handset’s

preferences and service requirement. Therefore the handsets or base stations can be used to adapt the dynamic topology.

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Figure 2: Samsung measurements of the RSCP values of the detected, monitored and Active set, displayed using Nemo Tools.

From Figure 2, the handsets on a network should really be regularly enhancing the capability of the network by adding intelligence to the network. This new intelligence is used to detect new links with better quality than what is being used in the current network topology. This creates a network that is self-adapting using its constituent mobile nodes, taking new decisions on best routes and system quality.

Drive Tests Drive test is usually done, in order to check if a pre-created network topology (links) is correct. It is used to distinguish good links from bad ones and to then build sub-optimum network topology that will remain after the tests. This static topology is optimal for most fixed wireless networks but is highly unsuitable when there is network mobility because the deteriorating mobile network environment also fails to meet required quality of service. Hence, it is essential to adapt the network topology to the changing quality of service requirements. Figure 2 illustrates this. In order to find the best topology, apart from the phone measurements, an extra signal strength scanner can also be used. A network in which the base stations were moving around was used for this study of topology adaptation. The measurements were based on a UMTS network and were collected to find the SLQM

and then adapt the network topology. For that purpose the mobile handsets, the nodes Bs and the relative movements between them are considered as moving base stations for study purposes. For the measurements, a mobile Samsung handset was used. Samsung handsets, apart from measuring the quality of the links with the node Bs, which are part of the topology of the UMTS network (active and monitored sets), they are also capable of detecting other nodes Bs that are not part of the network topology being used. This feature of the Samsung handsets is used to find the dynamic topology of the network every time that the handset or (base station) detects a good link with another base station.

In our experiments, drive tests were undertaken around major routes and suburbs in Sydney. The measuring vehicles contain 3G receivers connected to signal strength measuring and visualisation software Actix. Figure 1 shows also measurements of the radio frequency signals collected with a Nokia handset and analysed with Actix. Actix software may be used to analyse the communication and aids network optimisation. The exchanged measurements between the network and the phone can be displayed after the data from the phone has been collected. From Figure 1, it is observed that the handset is capable of reporting the power outputs of base stations within its

305

neighbourhood through the so-called radio service control power (RSCP) of the ‘active set’ and ‘monitored set’. The ‘active set’ and the ‘monitored set’ are links that the phone uses to connect to the network. The ‘active set’ is the link the phone is actually using to communicate with the network and the ‘monitored set’ represents links that can be used

if the ‘active set’ links are broken, meaning that the fixed network already knows the topology of the network, but does not adapt it. It will eventually select a new active set if the existing one is inadequate but does not match it to the service rate and quality.

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Figure 4: Measurements of RSCP and Ec/No from handsets, displayed with Nemo Tools.

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Other tests were conducted with a Samsung handset and analysed with the NEMO Tools software. NEMO displays the map of the area using MapInfo v5 and shows the location of the moving car (carrying a Samsung handset) and also of the active base stations serving the mobile. Figure 3 shows the NEMO workspace displayed by the MapInfo as used to conduct the measurements. The figure illustrates the fixed location of the node Bs or access point (base station); the route driven (red line on the map) while collecting the measurements with the Samsung handset and the areas where the measurements were taken (circles in the figure). The small blue circles inside the areas show the positions of the handset. Each area was considered as a different base station moving all at the same time. In addition, information provided by a GPS system of the position and the distance to the serving base station is also provided at the bottom of the figure. This information is used to study the topology of the network according to the distance between the base stations, its velocity and the coverage range expected by the base stations. However, post-processing of considerable data is required in order to find the quality of the link. Example of the values of RSCP and Ec are guveb in Figure 4. Figure 4 shows the active, monitored and detected set of RSCP and Ec/No measured by the handset.

Results from the Tests The minimum threshold values of RSCP and Ec/No used in the test to find the (SLQM) are shown in Table 1. Coloured lines represent the links that support particular types of services in the topology. The constant line represents high speed (HS) data, double line video, broken line data and the line with the small docs represents the links for voice in the topology. The thresholds are approximations close to values used in UMTS technology. Note that a link that can support HS (High Speed) data can also support other services (video, data and voice) because of the quality of the link; while a link that can just support voice cannot support other services. Therefore, a constant line (HS data) in the topology is part of a video, data and voice link requirement. A double line (Video) can also support data and voice. For instance, in the network topology a double line topology that supports video form part of the broken line topology as well as the topology represented with small dotted lines (data and voice). In Table 1, the measurements were taken three times every five seconds in order to observe the differences between the topology while the car was moving over short distances. This is used to demonstrate how rapidly and dramatically the

topology changes while vehicle was moving. Four areas were selected for the measurements. Each area was considered as an individual AP moving around. Four moving APs were considered and the topology resulting from the measurements is displayed. Table 1 has five columns; the first column is the value of RSCP of the node Bs collected by the phone, the second column are the values of Ec/No collected by the phone. The third column represents the identification number of the antenna serving the phone. The fourth column is the results of the equation (4) by applying the thresholds values. The fifth column shows when there is a new link in order to detect the changes in the network topology. This column is used from the second set of measurements where new links can be detected.

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ServiceID

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-95 -10 VIDEO 2-113 -13 DATA 3-120 -20 VOICE 4

NA 5Table 1: Thresholds values for RSCP and Ec/No

Table 2 shows the values of the RSCP and Ec/No measured by the handset for the positions of AP1, AP2, AP3 and AP4. These values are the strengths of the signals received by the AP1 (handset), AP2, AP3 and AP4 (for this example mobile handsets were used as APs). The handsets measure the signals from the node Bs, which are identified in the table as access point ID (AP ID). In the table, the column with heading “Service” shows the matching service. The far right-hand column (Node Status) determines whether there is a new link detected in the new measurements in order to update the network topology with it. Three topologies resulting from the three sets of measurement taken every five seconds are displayed in Figures 5 to 7. The connectivity of the APs is as shown in the Figures except that we have prioritised them using the relevant colours for the offered SNR. The connections between AP1, 2, 3 and 4 are displayed each time with the topology resulting from the measurements. The following matrices show equivalent values selected for Ec/No and RSCP in line with equations (2) and (3). The resulting SLQM values are also shown. Since a node does not provide a link to itself, we represent that situation as not applicable (NA).

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When the matrix when both the values of and are zero, there is not link between the APs. When an SLQM value is equal to five, the AP cannot find a suitable link for any service. The values 4, 3, 2 and 1 in the SLQM show that the link of that quality can support service type 4, 3, 2 and 1. The most common link values in UMTS

recorded are between -70 to -85dB for RSCP and between -4 to -6 for .

SLQM/Ec No RSCP

/Ec NoFigure 5 shows the resulting topology from the previous matrices as well as from the first set of measurements by the handsets. The brown links support voice, the blue links can support data and orange lines are high speed data links. Figure 6 shows the topology resulting from the second set of measurements (five seconds later). The connection between AP1, 2, 3 and 4 are this time displayed just graphically as a topology graph. Figure 7 shows the topology resulting from a third set of measurements, 10 seconds later. The connection between AP1, 2, 3 and 4 are also displayed just graphically in the topology graph. As can be seen the topology in Figure 5 has more links than the topology in Figure 7. The topology is different every time, a clear indication that the topology changes rapidly with the quality of the link. As can be seen some of the links disappear and others are added to the topology so it is a very complex dynamic network topology and a link quality monitoring and matching algorithm is necessary for forwarding packets of different quality of services efficiently.

AP1 AP2

RSCP Ec/No AP ID Service Node Status RSCP Ec/No AP ID Service Node Status-91 -7 399 HS DATA -91 -4 386 HS DATA-93 -8 247 HS DATA -97 -18 387 VOICE

-101 -16 256 VOICE -107 -20 397 VOICE-103 -19 409 VOICE -98 -22 395 NA-107 -23 386 NA -96 -23 252 NA

-104 -23 409 NA-100 -24 410 NA

Results of measurements 5 seconds later Results of measurements 5 seconds later-92 -4 247 HS DATA EXISTING LINK -94 -11 386 DATA EXISTING LINK

-101 -15 409 VOICE EXISTING LINK -95 -11 395 DATA EXISTING LINK-94 -20 256 VOICE EXISTING LINK -104 -21 387 NA EXISTING LINK-95 -24 399 NA EXISTING LINK -94 -10 409 VIDEO EXISTING LINK-96 -23 387 NA NEW LINK -103 -20 410 VOICE EXISTING LINK

-105 -21 383 NA NEW LINK-106 -23 397 NA EXISTING LINK

Results of measurements 10 seconds later Results of measurements 10 seconds later-85 -4 399 HS DATA EXISTING LINK -89 -7 386 HS DATA EXISTING LINK-92 -10 247 VIDEO EXISTING LINK -94 -15 395 VOICE EXISTING LINK

-102 -21 409 NA EXISTING LINK -92 -13 368 DATA NEW LINK-103 -22 248 NA NEW LINK -96 -14 397 VOICE EXISTING LINK-104 -23 256 NA EXISTING LINK -99 -17 252 VOICE NEW LINK

-104 -21 384 NA NEW LINK

Conclusions This paper has demonstrated that a wireless network topology can be adapted based on the measurements of the received signal strength (RSCP and Ec/No) between the APs and to match the links to QoS more efficiently. It is also possible to build the topology to match the service that each link can support, meaning that each service

provided by the network may need to use a different serving topology for efficient QoS support. However more research is required to study how fast and how dramatically the topology can change as a function of speed and terrain. Including the structures of the roads where the mobile network hosts are, the coverage range, velocity between APs and the terrain should be considered when

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studying the network topology of a moving broadband wireless network.

AP3 AP4

RSCP Ec/No AP ID Service Node Status RSCP Ec/No AP ID Service Node Status-91 -7 399 HS DATA -91 -4 386 HS DATA-93 -8 247 HS DATA -97 -18 387 VOICE

-101 -16 256 VOICE -107 -20 397 VOICE-103 -19 409 VOICE -98 -22 395 NA-107 -23 386 NA -96 -23 252 NA

-104 -23 409 NA-100 -24 410 NA

Results of measurements 5 seconds later Results of measurements 5 seconds later-92 -4 247 HS DATA EXISTING LINK -94 -11 386 DATA EXISTING LINK

-101 -15 409 VOICE EXISTING LINK -95 -11 395 DATA EXISTING LINK-94 -20 256 VOICE EXISTING LINK -104 -21 387 NA EXISTING LINK-95 -24 399 NA EXISTING LINK -94 -10 409 VIDEO EXISTING LINK-96 -23 387 NA NEW LINK -103 -20 410 VOICE EXISTING LINK

-105 -21 383 NA NEW LINK-106 -23 397 NA EXISTING LINK

Results of measurements 10 seconds later Results of measurements 10 seconds later-85 -4 399 HS DATA EXISTING LINK -89 -7 386 HS DATA EXISTING LINK-92 -10 247 VIDEO EXISTING LINK -94 -15 395 VOICE EXISTING LINK

-102 -21 409 NA EXISTING LINK -92 -13 368 DATA NEW LINK-103 -22 248 NA NEW LINK -96 -14 397 VOICE EXISTING LINK-104 -23 256 NA EXISTING LINK -99 -17 252 VOICE NEW LINK

-104 -21 384 NA NEW LINK

Table 2: Measurements of RSCP and Ec/No collected with the Samsung handset.

Figure 5: Resulting Network Topology from the first set of measurements from Table 13. References[1] L. Li, J.Y. Halpern., P. Bahl, Y-M. Wang, R. Wattenhofer, “A cone-based distributed topology-control algorithm for wireless multi-hop networks”, IEEE/ACM Transactions on Networking, Feb 2005 [2] M. Al-Hattab, J. I. Agbinya, “Topology Prediction and Convergence for Networks on Mobile Vehicles”, in Proc. Intern Conf. on Computer & Communication Engineering, Kuala Lumpur, Malaysia, May 13-15, 2008, pp. 266 - 269

[3] C. Perkins, E. Belding-Royer, and S. Das, "Ad-hoc on-demand distance vector routing," in Proc. of 2nd IEEE Workshop on Mobile Computing Systems & Applications, 1999, pp. 90 - 100. [4] D. Johnson and D. Maltz, "Dynamic source routing in ad-hoc wireless networks," in MobileComputing, vol. 5, T. Imielinski and H. Korth, Eds.: Kluwer Academic Publishers, 1996, pp. 153 -181. [5] P. Jacquet, P. Muhlethaler, T. Clausen, A. Laouiti, A. Qayyum, and L. Viennot, "Optimized Link

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Century: IEEE International, 2001, pp. 62 – 68 [6] R. RoyChoudhuri, S. Bandyopadhyay, and K. Paul, "Topology Discovery in ad hoc Wireless Networks Using Mobile Agents," in Proc. of Second International Workshop, MATA, vol. 1931/2000, E. Horlait, Ed. Paris: Springer Berlin / Heidelberg, 2000, pp. 531-542. [7] Agbinya, JI., Design Considerations of MoHotS and Wireless Chain Networks”, in Wireless Personal

Communications © Springer 2006, Vol. 40, pp. 91 -106 [8] Agbinya, J.I, Gina P. Navarrete, Mohammad Momani and Mohmood Akache, “Limits of Interference in MoHotS and Wireless Chain Networks”, in Proc. DSPCS'05 & WITSP'05, Noosa Heads (Sunshine Coast, Australia), 19 – 21 December 2005. [9] Agbinya, J.I., Design Concepts: Wireless Moving Networks, Proceedings ICACT'2004, Korea, February 8-11, 2004, pp. 703 – 708.

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Figure 6: Resulting Network Topology (5 seconds later).

Figure 7: Resulting Network Topology from the second set of measurements (10 seconds later).

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