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UBICC, the Ubiquitous Computing and Communication Journal [ISSN 1992-8424], is an international scientific and educational organization dedicated to advancing the arts, sciences, and applications of information technology. With a world-wide membership, UBICC is a leading resource for computing professionals and students working in the various fields of Information Technology, and for interpreting the impact of information technology on society.
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. firstname.lastname@example.org 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 . 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 . dashed arrow . 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 . 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 . 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. 126.96.36.199 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 . 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 188.8.131.52 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 . According to the activities sequence in amount of food taken at that time . 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 . 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 . 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 . 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 . 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 . for standardization; and refining quality of service for wireless connections. Figure 8 lists the handoff management operations . 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 . 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 . 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 8 REFERENCES 1600  Amitava Mukherjee, Somprakash Bandyopadhyay, and Debashis Saha. Location 1400 Management and Routing in Mobile Wireless 1200 Networks. 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