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									                          DYNAMIC GROUP MOBILITY MODEL
                             FOR HYBRID NETWORKS


                                       Author: Diouba Sacko,
                                       Prof. Huang Benxiong,
                                       Prof. Wang Furong, and I.
                                       Khider. Huazhong
                                       University of Science and
                                       Technology, Friendship
                                       apartment, room 411,
                                       Wuhan-430074,      Hubei,
                                       P.R. China.
                                        sacko_dioba@hotmail.com


                                               ABSTRACT
                 This paper presents a dynamic group mobility (DGM) model for hybrid
                 networks. In this model, the ad hoc network is placed in the cellular system.
                 In ad hoc network, mobile nodes (MNs) can dynamically re-configure
                 themselves triggering group partition and mergence. Therefore, MNs
                 sometimes merge and move together and sometimes split and move
                 individually. In cellular system, when group MNs roam from one local area
                 to another, the group leader ensures the location update for the whole group.
                 Since it is too expensive for each MN within the group to communicate all
                 the time with the base station (BS), we designate the group leader to ensure
                 the location update and the administrative tasks for the whole group. This
                 allows to reduce the power consumption, and to limit the wireless
                 bandwidth used.

                 Keywords: Mobility, Hybrid networks, Group leader,          Group partition,
                 Group merging, Simulation.


1   INTRODUCTION                                           workstations. On the other hand, the existing group
                                                           mobility models assume that nodes in the same group
          The mobility models proposed so far in the       stay in a homogeneous network throughout the whole
literature assume some kind of permanent group             simulation process. In DGM model presented in this
affiliation. Also they require that each node belongs      paper, movement MNs in the scope of the group
to a single group. In reality in many real life            happens in ad hoc network while group movement
applications, a much more complex mobility                 from one local area to another happens in cellular
behavior is observed. Some nodes move in groups;           system. In cellular system, when group MNs roam
while others move individually and independently.          from one local area to another, the group leader
Moreover, the group affiliation is not permanent. The      ensures the location update and the administrative
MNs can dynamically re-configure themselves                tasks for the whole group. This allows the reducing
triggering group partition and mergence. A good            of the power consumption, as well as the limitation of
realistic mobility model must capture all these            the wireless bandwidth used. The paper is organized
mobility dynamics in order to yield realistic              as follows. Section 2 presents the structure of DGM
performance evaluation results [2]. In this paper, in      model. The model is an integration of ad hoc network
section 3, we present a group of three individuals of      and cellular system. Section 3 presents intra-group
which one Worker, one Seller, and one Businessman;         movement i.e. movement MNs in the scope of the
belonging to a single home. Depending on time of the       group. In Section 4, we present inter-group
day, individuals move either from home to                  movement i.e. when group MNs roam from one local
workstations or from workstations to home. On the          area to another. Section 5 analyses the power
way to the workstations or back from the                   consumption during inter-group communication i.e.
workstations, they move sometimes together and             communication between MNs and the base station.
sometimes separately. Alternatively, they merge and        Section 6 analyses the performance of the model in
split at some reference points placed on the way of        ad hoc network through simulation results.


                    Ubiquitous Computing and Communication Journal                                             1
Conclusions and references appear in sections 7 and     Figure 2 illustrates the weekday’s trip chain of
8; respectively.                                        individuals. In this example, 4 switch stations are
                                                        placed in the trip chain. At the switch stations either
2   STRUCTURE OF DGM MODEL                              the group partitions into individuals or individuals
                                                        merge into group. Such group dynamics happen
         Figure 1 illustrates the structure of DGM      under the control of configured partition and merge
model. The model realizes an integration of ad hoc      probabilities. Each group member is defined with a
and cellular networks i.e. ad hoc network for intra-    member stability threshold value. At the switch
group movement and cellular system for inter-group      stations, each individual in the group will check
movement. It eliminates the need for each MN within     whether its stability value is beyond its group
the group to communicate with the base station. The     stability threshold value. If it is true, this individual
group leader does this job for whole the MNs within     will choose a different path. A group partition
the group. Group MNs is indicated by the yellow         happens. When several individuals arrive at the same
circles. The group moves from local area LA1 to local   station and select the same path for the next
area LA2; separated by the line “LA border”. Group      movement, naturally, they will merge into one group
movement from LA1 to LA2 is indicated by the            [2].
dashed arrow [8].
                                                                                 Home


                                                                              Station 1



                                                          Sale                  Work            Business


                                                                             Specific Switch
                                                                             Station (Meal)


          Figure 1: Structure of DGM model                                    Station 2
3 INTRA-GROUP MOVEMENT

          Intra-group movement happens in ad hoc                 Sale           Work              Entert.
network when MNs move in the scope of the group.
Ad hoc network is the infrastructureless mobile
network which has no fixed gateways (routers). All                              Station 3
nodes are capable of movement and can be
connected dynamically in an arbitrary manner.
Nodes of these networks function as routers which
discover and maintain routes to other nodes in the
network. Example applications of ad hoc networks
are emergency search-and rescue operations,
meetings or conventions in which folks wish to                                     Figure 2:
quickly share information, and data acquisition                                   Group motion
operations in inhospitable terrain [1]. This section
provides the movement of three individuals of which                               Individual motion
one Worker, one Seller, and one Businessman.

3.1 Trip Chain                                          3.2 Activities Sequence
           The trip chain is a sequence of actions to              In switch station 1, the group from home
be executed; execution of an action requires person     partitions and everyone moves toward his
to change location (for example, shopping requires      workstation. In specific switch station, at the pause
going to shops, lunch requires going to restaurants,    time from 12:00 to 13:00, the individuals meet in
etc…). After finishing current activity, the next       their common favorite restaurant to take lunch
activity is chosen and new movement is initiated [6].   together and to exchange the earlier informations




                    Ubiquitous Computing and Communication Journal                                             2
from their respective workstations. After lunch,
individuals move together toward the reference point
switch station 2. Here, the group partitions and                                   Home
everyone moves toward his own predefined
destination. At the end of daily’s activities,                         28, 6%              71, 4%
individuals merge into group at the reference point
switch station 3 and together return back at home as
                                                             Entert.
centroid .                                                                          Sale
3.2.1 Aggregated Activities Sequence
         Person’s behavior can vary in different days
in the week. In such a case aggregation of activities
is used. Figure 3 illustrates aggregated activities                                 Meal
sequence of individuals. Probability of switching to
particular activity between states, which is 100%, is
omitted. The switching probabilistic values from the                                                28, 6%
current location to the next indicate the probabilistic                          71, 4%
frequency to visit the next location.
Figure 3: Aggregated activities sequence of person 1,                               Sale
person 2, and person 3:
                                                                                    Person 2

                         Home
                                                                                           Home
               28, 6%         71, 4%
                                                               85, 7%
                                                                        14, 3%                 85, 7%
     Entert.
                          Work
                                                              Entert.                  Business

                          Meal
                                                                          14, 3%                        28,6%
                                       28, 6%                                              Meal

                               71, 4%                                               71, 4%

                          Work                                                  Person 3

                                                          We observe that the probabilistic frequency for
                                                          person 3 to switch from home to business is higher
                        Person 1
                                                          than 71, 4% (85, 7%). This because we assume that
                                                          he can go from home to business even the weekend.
                                                          Similarly, the probabilistic frequency to return back
                                                          at home just after entertainment is higher than 71,
                                                          4% because he can go from home to entertainment
                                                          and return back at home just after entertainment the
                                                          weekend.
                                                          3.2.2 Aggregated Activity matrices
                                                                     For aggregated activity matrices, the next
                                                          activity is chosen from a set of alternatives with a
                                                          certain probability.
                                                          3.2.2.1 Activity Transition Matrix
                                                                   Activity transition matrix stores transitions
                                                          between activities for each person depending on time
                                                          of the day. At different time of day unlike changes
                                                          between activities are possible. For example, after
                                                          work, at 12:00 a person is likely to go to lunch, but at
                                                          17:00 he is more likely to go home [6]. According to




                     Ubiquitous Computing and Communication Journal                                             3
the activities sequence in figure 2, the model utilizes
a probability matrix to determine the location of a          Location                    Duration (H)
particular individual in the next time. Therefore, the             10-12 3:00-3:30 5-8 0:30-1:00
probability matrices indicate the probability for an             H 1        0        0     0
individual to switch from the current location to the       P1 = S    0     1        0     0
next depending on time of the day.                              W 0         0        1     0
The probability matrices used are:                              M 0         0        0     1
                                                                                             Time (H)
     Current location            Next location

            H S W M
         H 0 1 0     0                                      Location                   Duration (H)
    P1 = S 1/3 0 2/3 0                                             10-12 3:00-3:30 5-8 0:30-1:00
        W 0 1/2 0 1/2                                            H 1         0      0     0
         M 0 1 0     0                                      P2 = S 0         1      0     0
                                   Time (H)                     Sa 0         0      1     0
                                                                M 0          0      0     1
                                                                                           Time (H)
  Current location
                          Next location
              H S Sa M
        H     0   1 0 0                                    Location                     Duration (H)
   P2 = S     1/3 0 2/3 0                                        10-12 3-3:30 4-6 0:30-1:00 1-2
       Sa     0 1/2 0 1/2                                      H 1       0     0     0        0
       M      0   1 0   0                                 P3 = S    0    1     0     0        0
                         Time(H)                               B    0    0     1     0        0
                                                               M 0       0     0      1       0
                                                               E    0    0     0     0        1
Current location                                                                           Time (H)
                          Next location
            H     S B M E                                 Legend: P1, P2, P3 = Probability matrices for
      H      0    1 0 0 0                                 persons 1, 2, and 3; respectively.
  P3= S     1/3   0 1/3 0 1/3                             H, S, W, M, B, Sa, E = Home, Switch station, Work,
     B       0    0 0 1 0                                 Meal, Business, Sale, and Entertainment; respectively.
     M       0    1 0 0 0
     E       0    1 0 0 0                                 From probability matrices, we observe that
                                                          individuals spend the same amount of time at home
                               Time (H)                   (10-12H), at switch stations (3-3:30), and at
                                                          restaurant (0:30-1:00). Indeed, individuals usually
Legend:                                                   merge simultaneously at these reference locations
P1, P2, P3 = Probability matrices for persons 1, 2, and   and split simultaneously from those.
3; respectively.                                          3.2.3     Algorithm of activities’ sequence
H, S, W, M, B, Sa, E = Home, Switch station, Work,                  The activity or a certain mobility behavior
Meal, Business, Sale, and Entertainment;                  that a person will demonstrate is determined by his
respectively.                                             current intention; for instance a person who is
3.2.2.2 Activity Duration Matrix                          hungry would intend to move toward the restaurant.
      Activity duration matrix stores the                 The act of being hungry is his current mental state.
information about duration of person’s activities at      That is, intention is again governed by mental states.
certain time period. At various time periods, the         The mental state of a person is a function of various
same activity can last for different amount of time.      factors. For example, how often a person gets hungry
For example, a lunch in a restaurant at 12:00 can         is regulated by habits and characteristics such as age,
take 30 minutes, but after 19:00 it might take 3          health, appetite, the time since last eating and the
hours [6]. According to the activities sequence in        amount of food taken at that time [9].
figure 2, the model utilizes a probability matrix to      The intention algorithm illustrated below determines
determine the amount of time spends by a                  what mobility act a person will take part in:
particular individual at visited location.                Intention Algorithm according to the figure 2:
The probability matrices used are:
                                                            if (person==worker) then




                      Ubiquitous Computing and Communication Journal                                           4
   if (mental state==need work) then go to work            related attributes: (a) CPU load; (b) memory; (c)
   station, work                                           battery and (d) bandwidth.
   else if (mental state==hungry) then go to               *Time until now since last time being a leader.
   restaurant, eat                                         This factor contributes to load balance among
   else if (mental state==tired) then stop work, go        peers. The overall weight can be calculated as
home                                                       follows, with relative importance (e.g., w1, w11)
   else work                                               specially defined for different applications (e.g.,
                                                           by group initializer).
  else if (person== businessman) then                      Weight = Resource*w1 + Elapsed_time*w2 (1)
            if (mental state== need business) then go      w 1 + w2 = 1
            to town, do business                           Resource*w1 = CPU_ Load*w11 + memory*w12 +
            else if (mental state==hungry) then go to      battery*w13 + bandwidth*w14          (2)
            restaurant, eat                                w1 = w11 + w12 + w13 + w14
            else if (! entertainment) then go to a         Note that it can be easily extended to cover other
            playground, play                               metrics, and metrics need normalization since they
            else if (mental state==tired) then stop        are in different units and are not comparable. In case
            entertainment, go home                         of tie of overall weights, the leader is selected
            else do business                               randomly. Leader rotation is started if some node has
                                                           an overall weight higher than the current leader. This
  else if (person==seller) then                            may result from multiple reasons: the current leader’s
        if (mental state==need sell) then go to a          weight keeps falling with longer time of being leader
market, sell                                               or a member’s resources get richer (e.g., gets power
        else if (mental state==hungry) then go to          plugged-in). Change of leader requires the transfer
        restaurant, eat                                    between the old and new leaders, the information that
        else if (mental state==tired) then stop sell, go   is only kept in the leader (e.g., the leaders of other
home                                                       neighbor groups). And the new leader needs to
        else sell                                          inform the whole group the changes of leader, along
                                                           with the group information including group member
3.2.4 Group Leader Selection                               list. As stated, group management over MANET
        Several criteria have been proposed for leader     requires managing mobility-induced changes in
selection in ad hoc networks, including: (i) highest       group membership in a manner that is transparent to
degree, where nodes with the maximum number of             applications. Since a new node is detected by the
neighbors are selected as group leader. This               network layer an event-based mechanism can be
approach has low rate of group leader change, but          installed on the leader to invite the new comer to join
suffers from low input since the throughput is shared      the group, on the condition that the group is able to
among group members. (ii) extrema-id where the             accommodate more members. The leaving of a node
node with the smallest or greatest id is assigned as       can be similarly handled by the leader’s sending an
the group leader. The shortcoming of this approach is      event-invoked group-wide announcement of updated
its bias, against nodes with extrema ids; (iii) node       member list [7].
weight, which is an integrated metric for evaluating
the suitability of a node as a group leader. It can        4   INTER-GROUP MOVEMENT
depend on various factors such as the resource
richness and the neighbor count. Above criteria are                Inter-group movement happens in cellular
essentially based on group attributes. Therefore, it is    network when group MNs roam from one local area
natural to integrate them to evaluate a node’s             to another. The cellular network is an infrastructured
suitability for acting as a leader, by tuning different    network with wireless last hop from fixed and wired
weights on different metrics for different scenarios.      gateways (See figure 4). The gateways for these
In particular, in this paper, we consider the following    networks are known as base stations. A mobile
two metrics, which are locally available on each           terminal within these networks connects to, and
node for election of group leader:                         communicates with, the nearest base station that is
*Resource richness. Powerful nodes with richer             within its communication radius. As a mobile travels
resources are considered more suitable as group            out of range of one base station and enters into the
leaders. This is because group leader consumes             range of another, a handoff occurs from the old base
more resources such as battery and computing               station to the new so that the mobile is able to
than other group members. It also improves group           continue communication seamlessly throughout the
performance, because weak group leaders tend to            network. Typical applications of this type of network
be the bottleneck, e.g., group leader is responsible       include      cellular    systems,    which       allow
for forwarding inter-group communication. In               Telecommunication accesses over wide areas [1].
particular, we consider the following resource-




                     Ubiquitous Computing and Communication Journal                                             5
                                                            (4) The HLR performs the required procedures to
                                                            authenticate the MT and records the ID of the new
                                                            serving VLR of the MT. The HLR then sends a
                                                            registration acknowledgement message to the new
                                                            VLR.
                                                            (5) The HLR sends a registration cancellation
                                                            message to the old VLR.
                                                            (6) The old VLR removes the record of the MT and
                                                            returns a cancellation acknowledgement message to
                                                            the HLR [3].

 Figure 4: A cellular network (Infrastructured
network)

4.1 Location Registration
        In order to correctly deliver calls, the public
land mobile networks (PLMN) must keep track of the
location of each mobile terminal (MT). Location
information is stored in two types of database, VLR
(Visitor Location Register) and HLR (Home
Location Register). As the MTs move around the
network coverage area, the data stored in these
databases may no longer be accurate. To ensure that
calls can be delivered successfully, the databases are
periodically updated through the process called
location registration. Location registration is initiated
by an MT when it reports its current location to the
network. We call this reporting process location
update. Current systems adopt an approach such that
the MT performs a location update whenever it enters
a new LA. Recall that each LA consists of a number          Figure 5: Location Registration Procedures
of cells and, in general, all BTs belonging to the same
LA are connected to the same MSC (Mobile                    4.2 Paging
Switching Center).                                                  Typically, fixed hosts connected to the
When an MT enters an LA, if the new LA belongs to           Internet remain online for extended periods of time,
the same VLR as the old LA, the record at the VLR is        even though most of the time they do not
updated to record the ID of the new LA. Otherwise, if       communicate hence such hosts are excluded from
the new LA belongs to a different VLR, a number of          routing cache. When a correspondent node transmits
extra steps are required to i) register the MT at the       packets for a host, which is excluded from routing
new serving VLR, ii) Update the HLR to record the           cache, gateway router broadcast in their domain to
ID of the new serving VLR and iii) deregister the MT        find a host. This action incurs large overhead.
at the old serving VLR. Figure 5 shows the location         Therefore Cellular IP uses a paging technique [10].
registration procedure when an MT moves to a new            A Paging Area (PA) is identified by its Controlling
LA. The following is the ordered list of tasks that are     Foreign Agent (CFA) and Paging Foreign Agent
performed during location registration:                     (PFA) IP addresses. A Paging Area Identification
(1) The MT enters a new LA and transmits a                  (PAI) is constructed by appending its PFA IP address
location update message to the new base station.            to its CFA IP addresses. As a network prefix
(2) The base station forwards the location update           distinguishes a network, a PAI is used for identifying
message to the MSC which launches a registration            a PA in a particular Regional Area (RA). In this way,
query to its associated VLR.                                each PA is uniquely identified by using a small
(3) The VLR updates its record on the location of the       amount of bandwidth. PAI extension is shown in
MT. If the new LA belongs to a different VLR, the           figure 6.
new VLR determines the address of the HLR of the
MT from its Mobile Identification Number (MIN).
This is achieved by a table lookup procedure called
Global Title Translation. The new VLR then sends a
location registration message to the HLR. Otherwise,
location registration is complete.




                     Ubiquitous Computing and Communication Journal                                             6
             Figure 6: PAI extension                     network. Handoff management includes two
                                                         conditions: intracell handoff and intercell handoff.
PAIs are distributed by Agent Advertisements with a      Intracell handoff occurs when the user moves within
PAI extension. Therefore, MNs detect their PA by         a service area (or cell) and experiences signal
receiving Agent Advertisements.                          strength deterioration below a certain threshold that
a) When a CFA receives packets from the Home             results in the transfer of the user’s calls to new radio
Agent (HA) sent to an idle MN, it sends Paging           channels of appropriate strength at the same BS.
Requests to all PFAs in its RA.                          Intercell handoff occurs when the user moves into an
b) All PFAs will not relay Paging Requests to all        adjacent cell and all of the terminal’s connections
MNs in their PAs. Before relaying Paging Requests        must be transferred to a new BS. While performing
to their MNs, PFAs search their visitor lists to find    handoff, the terminal may connect to multiple BS’s
out the MN in idle mode. Only the PFA which has          simultaneously and use some form of signaling
the MN’s home address in its visitor lists will send     diversity to combine the multiple signals. This is
Paging Requests to its PA.                               called soft handoff. On the other hand, if the terminal
c) When a MN finds its home address in the Paging        stays connected to only one BS at a time, clearing the
Request, the MN sends the Paging Reply to its PFA.       connection with the former BS immediately before or
The MN changes its mode to active and starts its         after establishing a connection with the target BS,
active timer.                                            then the process is referred to as hard handoff.
d) When the PFA receives the paging reply, it sends      Handoff management research concerns issues such
a Regional Registration Request to its CFA.              as efficient and expedient packet processing;
e) The CFA sends back a regional registration reply      minimizing the signaling load on the network,
to the PFA.                                              optimizing the route for each connection; efficient
f) The PFA sends a paging reply to its CFA.              bandwidth reassignment; evaluating existing methods
Paging procedure is shown in figure 7 [11].              for standardization; and refining quality of service for
                                                         wireless connections. Figure 8 lists the handoff
                                                         management                  operations               [4].




           Figure 7: Call flow of paging
                                                                Figure 8: Handoff management operations
4.3 Handoff Management
        Handoff management plays an important role       5   POWER CONSUMPTION ANALYSIS
in the integration of heterogeneous wireless networks.
Horizontal handoff (intra-system handoff) occurs                   Let E be the average power consumption of
when a mobile terminal is moving out of the              an MN communicating with the base station and e be
coverage area of a base station into the coverage area   the average power consumption between MNs in
of another BS within the same system. Vertical           group. It has been shown that the power that an MN
handoff (inter-system handoff) is defined as handoff     uses to transmit a message is on proportion to the
between BSs that are using different wireless network    square of the distance to the destination. From figure
technologies. It usually occurs in wireless overlay      1, it is obvious that the communication distance in
networks where the coverage areas of different tiers     the scope of the group is much shorter than to the
of networks are overlapping to each other [5].           base station. This implies that E >> e. In traditional
Handoff (or Handover) management enables the             location update scheme, when a group of (n) MNs
network to maintain a user’s connection as the MT        crosses one location area to another, every MN sends
continues to move and change its access point to the     a location update message to the base station.




                    Ubiquitous Computing and Communication Journal                                              7
Therefore, the total energy consumption is nE. While
                                                                     3000
in DGM scheme, every time that the group crosses
the border LA, only the group leader is charged to
                                                                     2500
report location update. Therefore, the whole system
uses only E for each crossing. Even we add the cost
for member joining, quitting, leader selection, leader               2000

rotation, the power consumptions are still saved for




                                                         Packet ID
the whole system [8].                                                1500



6   SIMULATION                                                       1000



6.1 Simulation Description                                            500
        It has been shown that mobility patterns can
affect the performance of ad hoc network routing                        0
                                                                            0            5                10                15              20          25
protocol significantly. In this section we will                                                                 Time (s)
evaluate the performance of DSDV routing protocol
under the DGM model. For our simulation purpose,                                         Figure 9: Packet ID vs. time
the performance metrics collected include the flow of
data packets and the drop packets. Our evaluations
are based on the simulation using Network Simulator                  3000
environment (NS-2); we extract the useful data from
trace file. The graphs are generated using Matlab.                   2500
Simulation environment consists of 3 wireless nodes
forming an ad hoc network, moving over a 500 X
                                                                     2000
500 flat space, DSDV routing protocol for 30
seconds of simulation time; the Time To Live (TTL)
                                                         Packet ID




                                                                     1500
is 32 seconds. The traffic consists of tcp type with 3
connections; packet size is 1060 bytes.
                                                                     1000

6.2 Simulation Results
         Figures 9, 10, and 11 show sending packets                   500

from node 1 to node 2, from node 0 to node 2, and
from node 2 to node 1; respectively. The router                         0
                                                                            4       6        8       10           12        14        16         18    20
message for these figures is RTR (Router Trace).                                                               Time (s)
According to figures 9, 10, and 11, when t < 4                                          Figure 10: Packet ID vs. time
Seconds, nodes move together hence there is no
sending packets. For 4 < t < 22, we note on the
figures sending packets from one node to another.                    3000

Sending packets increases almost linearly with the
time. For t > 22 Seconds; nodes are merging hence                    2500

sending packets ceases. Figure 12 shows the drop
packets from node 1 to node 2. For t < 6.1, nodes are                2000

close each other thus we don’t observe drop packets.
                                                         Packet ID




For 6.1 < t < 7.2, the amount of drop packets                        1500

increases linearly with the time. That is, when the
                                                                     1000
distance between nodes increases, the probability of
drop packets increases, too. For t > 7.2 nodes are
                                                                      500
merging, no drop packets. Figure 13 shows the drop
packets from node 2 to node 1. Similarly as figure 12,
                                                                        0
there is no drop packets when nodes are close each                          2   4        6       8    10          12       14    16        18     20   22
                                                                                                               Time (s)
other. Otherwise, the amount of drop packets
increases linearly with the time. The router message                                     Figure 11: Packet ID vs. time
for figures 12 and 13 is mac.




                    Ubiquitous Computing and Communication Journal                                                                                      8
                                                                                                             reducing of the location update signaling in the
                         560
                                                                                                             database side significantly as well as the consumption
                                                                       RET pkt
                         540                                                                                 of wireless bandwidth for location update message.
                                                                                                             Analysis presented in section 5, shows that the DGM
                         520                                                                                 scheme greatly saves energy for MNs during inter-
                                                                                                             group communication. In section 6, we have
          Drop Packet




                         500
                                                                                                             evaluated the performance of DSDV routing protocol
                         480
                                                                                                             under ad hoc network. Simulation results are highly
                                                                                                             dependent on the movement behaviors of mobile
                         460                                                                                 node, the routing protocols under investigation and
                                                                                                             simulation environment. We implemented mobility
                         440                                                                                 model in NS-2 environment and converted the useful
                                                                                                             trace file to graphs using Matlab. Obtained results
                         420
                               6       6.2       6.4      6.6        6.8           7        7.2        7.4   agree with expected results based on the theoretical
                                                        Simulation Time (s)
                                                                                                             analysis.
                                       Figure12: Drop Packet vs. time
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                        1000                                                                                 Number: 2003041889,          2003 ARTECH HOUSE,
    Drop packet




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                               4   5         6   7      8       9     10
                                                       Simulation Time (s)
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                                                                                                             Management in Next Generation Wireless Systems*,
                                   Figure 13: Drop Packet vs. time                                           Broadband and Wireless Networking Laboratory,
                                                                                                             School of Electrical and Computer Engineering,
ACKNOWLEDGEMENT                                                                                              Georgia Institute of Technology, Atlanta, GA 30332.
This work was supported by national natural science                                                          Proceedings of the IEEE, vol.87, No.8, pp.1347-84
foundation of China under grant No.60572047.                                                                 (August 1999).
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7                  CONCLUSIONS                                                                               S. M. Ho, Huseyin Uzunalioglu, and Wenye
                                                                                                             Wang. Mobility Management in Next-Generation
              The mobility models proposed so far in                                                         Wireless Systems, Proceedings of the IEEE,
the literature assume some kind of permanent group                                                           vol.87,       No.8,         pp.1347-84,      0018-
affiliation. In this paper, we presented in section 3 the                                                    9219/99$10.00 1999 IEEE (August 1999).
movement of three individuals in the scope of the                                                            [5] I. F. Akyildiz, J. Xie, and S. Mohanty. A Survey
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presented in section 2, realizes an integration of ad                                                        verteilte systeme (IPVS), Abteilung Verteilte
hoc and cellular networks. Indeed, in DGM model,                                                             Systeme. Universitat Stuttgart Fakultat Informatik.
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