LOCATION MANAGEMENT AND COST PLANNING FOR PERSONAL COMMUNICATION SYSTEMS

IFAC MCPL 2007 The 4th International Federation of Automatic Control Conference on Management and Control of Production and Logistics September 27-30, Sibiu - Romania

LOCATION MANAGEMENT AND COST PLANNING FOR PERSONAL COMMUNICATION SYSTEMS Doina Bein a,1 Vasu Jolly b Linda Morales c a

Department of Computer Science, University of Texas at Dallas,,Richardson, TX 75083, USA Department of Electrical Engineering, University of Nevada-Las Vegas, Las Vegas, NV 89154, USA c Department of Computer Science and Information Systems, Texas A& M University-Commerce, USA b

Abstract: Mobile networks have experienced a sharp expansion in the population of mobile clients/subscribers. Such growth incurs additional expending of the bandwidth resources for network cost management. For future PCS (Personal Communication Services) networks, it is desirable to devise mobile networks that make resourceful use of the limited radio bandwidth. Effective mobility and location management is a way to realize such efficiency. This paper surveys different location management strategies and cost planning for personal communication systems. The stress is on how to minimize both the location update and paging costs from the wireless and wired networks. Copyright © 2007 IFAC Keywords: Location management; Mobile networks; Personal Communication Services.

The increasing demands for diverse services dictate a high-quality framework of location management to accommodate mobile clients roving across different systems. Thus it is necessary to track down mobile clients within the time limit (the maximum setup time) before the receiving call connections can be determined. Thus a periodic update of the location in the PCS networks as mobile clients move out the location area (LA) (Fang et al., 2000) is required. Section 2 focuses on investigating the relevant research in implementing the location area. Section 3 is a review of cost of location management. Section 4 concludes the paper.

1. INTRODUCTION PCS networks facilitate unhindered dialogue between mobile clients at any time from any location using any form of services. A large area is covered by base stations that individually cover small portions. A set of base stations can be grouped together, under a Base Station Controller (BSC) authority, to optimize signalling (bandwidth allocation); the result is a location area (LA). Each LA is uniquely identified by a code, and mobile clients are responsible for detecting location area codes. A mobile node has associated a so-called Temporary Mobile Subscriber Identity (TMSI) that is a randomly allocated number that is given to the mobile, the moment it subscribes to the network. The number is significant only within a location area, and so it must be updated whenever the mobile moves to a new LA. When a mobile finds that the location area code is different from its last update, it performs a so-called location update, by sending to the network a location update request that contains its previous location and its TMSI. To prevent the identification of the subscriber and being tracked by eavesdroppers, the network can also change the TMSI of the mobile at any time.

2. LOCATION AREA MANAGEMENT The entire service area in the personal communication service network is illustrated in Figure 1. The network is divided into respective location areas (LAs) and each location area contains one or more cells (a cell is covered by a base station).

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traffic, residential, business, shopping, parks, lakes etc. The authors in (Rocha et al., 1999), justifies that the mobile clients are most likely to move among certain areas, and most of them move from home to work and then back home. Partitioning in order to obtain an optimal total management cost for all mobile clients is done in (Rose, 1996, Akyildiz et al., 1996, Zheng et al., 2004). Under the static schemes, however, a mobile client positioned in proximity of the boundary of a location area may perform excessive location updates as it moves back and forth between two location areas. Several proposals introduce institute incremental improvements to the location area strategy. In (Okasaka et al., 1991, Escalle et al., 2002) overlapping LA systems were introduced to reduce the number of update operations that result from users moving near the LA boundaries (Bhattacharya and Das, 1999, Subrata and Zomaya, 2003). Additionally, sequential paging schemes were suggested to moderate the cost of paging generated by an incoming call. In this sequential paging strategy, the system sequentially pages sub parts of the current LA based on its location probability (Shirota et al., 1994, Rose and Yates, 1995, Mishra and Tonguz, 1997). Additionally, using a system of moving LAs can reduce the location update cost and the paging costs. This approach can be useful in the case of tracking fast moving users on freeways (Bejerano and Cidon, 2001). Different than static location area, the dynamic LA is based on the mobility behaviour and call patterns (call arrival rate) of individual mobile client. This scheme is tailored for the individual mobility patterns of each user. Dynamic location areas can be further classified into on movement-based LA (Akyildiz et al., 1996), time-based LA (Rose, 1996), and distanced-based LA (Wong and Leung, 2001). The concept of personalized LA (Xie et al., 1993, Lei and Rose, 1998, Lei et al., 2000, Ming-Hui et al., 2001) is proposed in (Xie et al., 1993), in which the respective size of the location area is defined on a per-user basis for reducing the signalling overhead of each individual user. Once the mobile client leaves a current LA, a new LA will be defined depending on the probabilities of crossing the boundaries of cells called transition probability. This new location area might have overlaps with the old one. The only downside of the personalized LA is that it groups the cells based on the transactional probabilities among them. If grouping is constrained by LA size, defined as a number of cells in the area the scheme might yield a nonoptimal solution, since the location update cost can be augmented under a larger LA, though the paging cost can be minimized, or fixed under this constrain. In (Tabbane, 1995, Pollini and Chih-Lin, 1997, Sen et al., 1999, Bhattacharya and Das, 1999), the mobile clients are allowed to miss out few update operations when they cross the boundaries of the respective location area. When a call comes in, the system uses the user profile information to estimate the probability for each LA that it is the current LA of the user. The system then pages the LAs in order of decreasing probability (Bejerano et al., 2003). An approach to group cells into location areas by

Fig. 1. Individual cells and 4 LAs in a region Location management administers two strategies: (a) location update and (b) paging to deliver calls and to maintain the calls in progress as mobile users move into a new area (Tabbane, 1997, Brown and Mohan, 1997, Bhattacharya and Das, 1999). Upon the arrival of a call, the system searches for the mobile client among a set of base stations (BS) over the current locality of the mobile (process called paging). When an incoming call arrives for the mobile client, the system performs paging by sending polling messages to all the cells in the mobile client’s last reported LA. Two simple location management strategies are: (a) always-update approach and (b) never-update approach (Subrata and Zomaya, 2003). In the first approach each mobile client performs a location update whenever it enters a new cell. This causes a large overhead for location update. However, no search operation would be necessary for incoming calls. In the latter approach of never-update, location update is never performed. When a call comes in, a search function is conducted to find the projected user. In this approach no resources are used for location update. However, the only overhead is for the search operation. Always-update location tracking strategy works well for a relatively small number of mobile users. In a particular PCS network, Universal Mobile Telecommunication System (UMTS), the population of mobile clients increases considerably and many new services like multimedia over telephony are provided. To accommodate the increased number of users and meet the quality of service requirements, the cell size is reduced. That allows also for power savings for transmission and greater frequency reuse (Wong and Leung, 2001). However, smaller cells unfavourably cause more frequent cell crossing by mobile clients. The latter circumstance in turn leads to higher location management cost. Most existing cellular systems use a combination of the always-update approach and the never-update approach. Various LA-based strategies have been proposed to reduce the signalling cost for location management. These strategies can be categorized into (1) static and (2) dynamic assignment of the location area (Rocha et al., 1999, Tabanne, 1997, Demestichas and Georgantas, 2000,). In static location area, the entire system is segregated into a number of LAs, which are fixed. (Rocha et al., 1999) propose a simulator built to show the division of a city area model. This Manhattan model allows tracking the hundreds and thousands of mobile clients. The idea is to divide the location areas on the basis of regions of interest such 684

3. COST MANAGEMENT

considering movement behaviour of individual mobile client is proposed in (Lee and Chen, 2003). LAs are fixed for each mobile client but could be different for different clients. In (Bar and Kessler, 1993, Subrata and Zomaya, 2003), a subset of cells in the network is elected as the reporting cells. Each mobile client performs location update, only when it enters one of these reporting cells. When a call arrives, the search is restricted to the respective reporting cell to which the client last reported and the neighbouring bounded non-reporting cells. Figure 2 illustrates an example, upon arrival of call at cell” CALL”, the search is limited to (a) the reporting cell that the user last reported in, i.e. cells named “RC” and (b) the non-reporting cells named “NC”. The authors in (Bar and Kessler, 1993) mentions finding an optimal set of reporting cells based on cost performance is an NP-complete problem. In (Abutaleb and Li, 1997), a heuristic method to find near optimal solutions is described.

The problem of minimizing the total cost of location update and paging can be formulated as an optimization problem and is NP-complete. The total location management cost in a respective location area “K” is C ( K ) = C p λc N + Cuφu where N denotes the number of cells in the LA, λc is the call arrival rate for the mobile client, φu is the location update rate of the mobile client for the location area “K” and is equal to 1/ t’ where t is the mean residence time. Cp and Cu are the per-cell paging cost and the unit location update cost, respectively (Abutaleb and Li, 1997). The first component of the right side of the above equation corresponds to the paging cost and the addend is the location update cost. A personalized LA is formed such that the total location management cost is minimized. In (Zheng et al., 2004), an iterative greedy heuristic algorithm that yields a sub-optimal solution is proposed. The minimum computed cost Cmin starts with C min = C p λc + Cu λ mv where “mv” is the possible location of the current mobile client. Cmin is further decreased until the threshold cp λc ( |TLA| +1) is reached (which is the paging cost of grouping when one more cell is added to the temporary LA). If the condition is met, there is no need in further check because Cmin will be less than the total cost incurred by adding any single cell. The movement-based dynamic location update scheme is explained in (Li et al., 1999). An analytical model is applied to formulate the costs of location update and paging in the movement-based location update scheme. In the movement-based location update policy, location update is executed whenever the mobile client completes “d” movements between cells. The value d is called the location update movement threshold. When an incoming call arrives, the system pages a location area including all cells within a distance “d’ from last registered location of the called mobile user. Under the movement-based location update scheme, the location update is performed after the dth cell boundary crossing since the last location registration. Assume that the cost for performing a location update is U (U > 0), which account for the wireless bandwidth utilization and the computational requirements in order to process the location update. Note that the probability density function of the cell residence time has Laplace-Stieltjes transform fm(s), mean 1/ λ m. The call arrival to each mobile user is a Poisson process with rate λ c . Note that a mobile user has smaller mean cell residence time than the mean call arrival time interval to the mobile user if θ < 1, and vice versa. That is, the smaller the CMR, the higher the mobility that a mobile user has. For calculating the paging cost, assume that the cost for polling a cell is P (P > 0). All the cells in the paging area are paged when an incoming call arrives. In (Bejerano et al., 2003), for each mobile user, the system keeps a record of the current LA where it resides. Each time a user crosses an LA boundary, it

Fig. 2. Regions showing reporting cells In the movement-based location update policy, location update is executed whenever the mobile client completes “d” movements between cells. The value d is called the location update movement threshold. When an incoming call arrives, the system pages a location area including all cells within a distance d from last registered location of the called mobile user. In the time-based location update scheme, location update is executed every “t” units of time. The size of the location area is estimated according to the mobility of the mobile user in the scheme. In the distance-based location update policy, location update is executed whenever the distance between the current cell that the mobile user locates and the last cell in which the update is performed is “d”. So the location area is an area with which the central cell is the last cell where the last update occurs surrounding by “d” rings of cells (Li et al., 1999). In (Hwang et al., 2000, Zheng and Regentova, 2004) a hybrid approach is proposed wherein both distance and direction metrics are taken into account yielding the improvement of the signalling cost. Performance comparison of the hybrid location update (HLU) with the distance-based location update (DSLU) and direction-based location update (DRLU) shows the superiority of the former. When the mobility patterns become more and more directional, the HLU approaches the DRLU. It tends to approach the DRLU for more random patterns. Additionally the total signalling cost increases as the call to mobility decreases. Next we address strategies to calculate the total location management cost for a mobile client.

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locate the mobile client. Thus, the average total cost per unit time, can be expressed as

updates the system with its new location. When an incoming call arrives, the system simultaneously pages the user in all the cells of its current LA. After receiving the user reply, the system establishes a connection between the call originator and the called user. Thus, the location management scheme produces two types of signalling costs, where the costs are considered from both the wireless and wired network perspective. An update cost that reflects the cost of all the update operations performed by the users during one time unit, and a paging cost that results from all the paging operations during a time unit. Consider an LA, L = {S1 , S 2 ,...S k } . Let f be the user incoming call rate and Cp be the cost of paging a single cell. The paging cost of a single LA, L, with |S| cells, is the product of the incoming call rate multiplied by the cost of paging all the LA cells. Similarly, for the update cost a user induces an update operation whenever it moves from a cell “i” in one LA to a cell “j” in an another LA. The amount of traffic per time unit between the two cells is fij , so the update cost caused by traffic between the cells i and j is Cu·fij where Cu is the cost of a single update operation. The total cost of update operations in the system is equal to the amount of traffic between the LAs times Cu. The overall signaling cost determines the efficiency of a given LA planning. An optimal LA planning, LOPT, is a graph partition with the minimal signaling cost among all the feasible LA plans, i.e. Cost ( LOPT ) = min L {Update Cost ( L) + Page cos t ( L)}

k −1

C = λ m C u [1 − 2q ∑ Π i + 1(1 − q)Π k ] + i =0

k

+ p t λ c C p ∑ Π i (2i + 1) i =0

The numerical results show that scheme has good performance when the cost of paging one LA is comparable with that of one location update. Moreover, the DBLU scheme does not require complicated computations in both the mobile client and network. This merit makes the DBLU scheme feasible in location management. 4. CONCLUSION The need for mobile usage is being driven by shared networking, increased business-to-business communications, expanding e-commerce, etc.. The prospects of future applications on cellular networks are countless. Constraints related to the call handling capacities of network elements and costs related to the paging and registration activities should be considered. Utilizing the available network information in a realistic manner further optimizes the location management costs. In this work we addressed the importance to minimize both the update and paging costs in location area planning from the wireless and wired networks perspective. The scope of both the mobility model and dynamic location update is quite large, and several possibilities and alternatives still need to be considered. An analytical model is studied to formulate the costs of location update and paging per call arrival for dynamic mobility management scheme, movement-based location update scheme and direction based location.

3.1 Direction-based Location Update In (Hwang et al., 2000), a direction-based location update scheme for the PCS networks has been explained. This scheme employs a line-paging strategy. A moving direction identification mechanism using only simple computations detects the change of moving direction and updates the mobile’s location. To locate a mobile client, paging can be carried out along its moving direction, and hence the paging cost is reduced. Moreover, the mobile client’s moving direction can be determined by simple numerical calculations. In the DBLU scheme, a mobile client performs a location update when its moving direction changes. For example, mobile client1 makes movements and its moving direction changes. After passing each directionchanging point, mobile client1 performs location update and informs the network of its new moving direction. Thus, the network can always keep track of mobile client1’s moving direction. When a call is originated to a particular mobile client, the system only pages the LA’s on the line of the mobile client’s moving direction. Let Cu and Cp denote the cost of one location update and one LA paging respectively. Assuming each call generated for the mobile client is a termination call with probability pt. At each LA crossing, a mobile client changes its moving direction with probability 1-2q. Besides, for a termination call to a mobile client at the system state Si, the DBLU scheme needs to page 2i+1 LA’s to

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