Mobile Clients - Location Management Strategies

8/8/2019 Mobile Clients - Location Management Strategies

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Mobile clients LocationManagement strategies.


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Introduction

Increasingly becoming part of our lives A geographic region is divided up into interconnected cells

At the center of each cell is a base station to which all the telephone in the

cell transmit

All the base stations are connected to single device called an MTSO

(Mobile Telephone Switching Office) or MSC (Mobile Switching Center)

Mobile clients may move within their current cells or move into other cells

System needs to record the real-time location of a user while the user is

moving since other mobile clients may generate queries on the location of

the client

may want to communicate with the client

To efficiently manage the locations of mobile clients, location databases aredefined

When the mobility of the client is high, the validity of data elements may

change rapidly with time, the data elements for the locations of mobile

clients are real-time data.

On the other hand, the queries submitted from mobile clients are always

associated with timing constraints on their completion time.


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Location database model associated

with mobile network

a geographic region is divided into

number of connected cells

At the centre of each cell is a base

station or base supporting station

(BSS). The mobile clients within a cell

communicate through BSS through

wireless channels.

Each BSS maintains a location

database.

The location databases ofneighboring base stations are

organized into a hierarchical

structure.


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Architecture for Location Databases

There are two most common used architectures:

Firstly, two-tier schemes-in which the current location of user is saved at two

network locations

and secondly, a hierarchical distributed database where the whole space is

hierarchically decomposed into sub-regions.


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Two-tier Schemes

Every user is associated with a Home Location Register (HLR).

HLR primarily contains a location (zone) predefined for the user.

Whenever a need arises to search the current location of user, its HLR is

queried.

Whenever user moves to another area, its HLR is contacted and updated tomaintain the new location.

An addition to this scheme is a Visitor Location Register (VLR) associated with

each user.

VLR stores the current location of users which are not in their home location.

If a mobile userx is at jlocation, then on searching for its current location, first

the VLR ofjwill be queried and then if not found the HLR ofxwill be contacted.

Whenever, a mobile user moves from ito j, its entry on VLR ofiis deleted and

entry in VLR ofj is updated along with updating of location in its HLR.


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Hierarchical Schemes

maintain a tree-like structure

Each location database at the leaf nodes maintains the location information of

users of a single zone.

The information that is stored for a user is either a pointer to an entry in a

database at a sub tree (in case of internal nodes) or the actual location (in caseof leaf nodes).

The databases are connected to each other through intelligent signalling

network like a common channel signalling (CCS) network.

The type of location information maintained in the location database affects the

relative cost of search and update of the location information of users.

It also affects the distribution of loads among links and nodes. When a user moves from zone i to zone j, then updating is needed along path i

to LCA[i,j] and LCA[i,j] to j. (Least common ancestor)

In a hierarchical database network, HLR is not used with any user. The user is

located by querying database in hierarchy.

In worst case, entry for user is found in the root node.


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Principles of Location Update in

Hierarchical structure

It is proportional to the distance between the starting and the destination cells of

the mobile client.

The mobility patterns of all the mobile clients should be considered before

constructing the location database tree.

Leaf is the Least common ancestorof location databases DBiand DBjand thusdenoted as LCA(DBi, DBj).

Height ofLCA(DBi, DBj)to the leaf nodes of the tree is denoted as lca (DBi,

DBj).


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Location Update Generation -

Terminology

Let the leaf location database

responsible for the cell ibe LDB (i).

Definition 1: The distance between cells

iand j, termed as dis (i, j), is defined as

the height of the least common ancestor

of the responsible leaf the locationdatabases, that is

dis(i,j) = lca(LDB(i),LDB(j)).

Ifi = jthen dis(i, j) = 0.

Let cc(x) be the cell in which mobile clientx is now residing.

Definition 2: The distance between

mobile clients xand y, termed dis(x, y), isdefined as the distance of the two cells in

whichxand yis now residing, namely

dis(x, y) = dis(cc(x), cc(y)).


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Location Update Generation -

Terminology

While calculating the optimal value for distance threshold, we consider the

following related costs in location update and lookup procedure.

CL: the cost of following a link in the tree of the location databases, i.e., sending

a message to the parent or the child node of location database;

CU: the cost of database update; CQ : a database query cost

If the location update is to be generated whenever a client x moves from old

cell, oc(x), to current cell, cc(x), the database entries for x in both from old

cell up to LCA(cc(x), oc(x)) and from LCA(cc(x), oc(x)) down to cc(x) have

to be updated.

So, the total location update cost for x will be: Cost_update = 2dis(oc(x), cc(x))x CL + (2dis(oc(x), cc(x))+ )xCU [2]

eqn.(1)

Each element of the cover forms a cluster.

The objective for finding a covering of the set of n cells is to get the minimal

value of num-crossing.


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Location Management

Location management involves two operations, look-up and update.

Whenever a userneeds to be located, a lookup or search operation is used.

Whenever a mobile userchanges its location, the update operation is used.

Approach to store location information range between two extremes:

at one extreme, up-to-date information of location of a user is stored in everynetwork location which reduces the look-up cost as only the local database

used to be referred.

However the update cost becomes high as on every move of user, the

updating requires to be reflected in all the network locations.

At the other extreme, no useful information is stored at any network location.

Thus to locate a mobile user, search is needed to be done at all networksites. However, in such a case, the cost is reduced as change in location of

mobile user does not require any updating.


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Placement of Databases

Flat

The flat search queries all nodes from root to the leaf.

Expanding

The expanding search queries first its home, then homes parent & then

all its children & so on.

Hybrid

The hybrid search first performs expanding search and if the location is

not found then flat search is done.


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Dynamic Hierarchical Database

Architecture

The dynamic hierarchical database architecture periodically computes &

stores the location configuration for the mobiles with the help of Directory

Registers.

This Architecture proposed [5] introduces Directory Registers with the existing

two- tier scheme.

Partition

For each user, on the basis of locality of movement to avoid maintaining location

entries at all levels and thus reducing the search cost.

The information whether the user is in current partition is maintained by a Leaf.

To find the exact location of the user as it enables to decide which sub tree in

hierarchy is to be searched with flat searching. The update cost is increased however it also reduces the overall search cost as

compared to the flat search.


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Caching

Whenever a call is made, it is assumed that the information of the user will be

again used in further calls being made from the same region.

Information about the user is cached at the VLR of the callee so that the

information could be used in further calls.

So next time to locate the user, first the cache is being queried which stores theinformation

and if the location is not found at the cache, the HLR of the user is queried.

Two major types of caching:

Eager caching

the cache is updated every time user moves

Lazy caching.

The cache is updated only when there is a cache miss and move

operation.

Performance study for lazy cache is presented in [2].

Caching is appropriate when the users call-to-mobility ratio is high.


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Forwarding Pointers

It is quite expensive to update all the database records that containing users

information when the number of moves made by the user is quite large than the

number of his incoming calls.

Forwarding pointer is used that points to the current location of user.


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Forwarding Pointers in Two-tier

Architectures

To avoid the cost of updating HLR and VLR both, forwarding pointers are set

from the VLR is used.

From user xs previous location to its new location.

Whenever, the user will be called, its HLR will be queried first to find out the first

VLR at which the user was registered

A chain of forwarding pointers is followed.

The length of this chain of forwarding pointers is allowed to grow up to a length

of k.

In case of pointer loops back to its same location, then pointer compression

takes place.

This approach is employed on per-user basis and so the cost of call operations

affects the particular user.


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A cost-based approach for distance

threshold

The total cost in locating new location of a mobile client is compared with

the total cost in locating a mobile client in old location

Optimal distance threshold value is letting the cost for location update equalto the saving in cost.


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Call Mobility Ratio- Terminology

The ratio of the number of calls for locating a mobile client over the number of

cell boundary crossing defined as call to mobility ratio (CMR)[3].

CMR is an important factor affecting the costs for locating a mobile client and

location update.

If there are not many location calls to a mobile client per cell boundary crossing,

i.e., CMR is small, then the generation of a location update from a mobile client

will not result in much saving in the cost for locating the mobile client.

So in this case the location update must not be preferred.

And if the CMR is large, the generation of a location update can reduce the

location cost significantly.


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Costs in location update and lookup

procedure.

CL: the cost of following a link in the tree of the location databases,

i.e., sending a message to the parent or the child node of location

database;

CF: the cost of Forwarding a pointer.

the cost of sending a message to an arbitrary cell for the case where the

system knows at which cell it is now residing;

CU: the cost of database update;

CP : the cost for polling for a specific client in a cell;

CQ : a database query cost.


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Conclusion

While locating the mobile clients it is important to consider the architecture of

mobile network which in turn affects the performance of the system and the cost

associated with the system.

Different mobile clients have different patterns of mobility.

Patterns may change gradually with time making it essential to maintain the

real-time locations, of mobile clients

When the mobility increases, the cost of locating the mobile clients become very

high

Hence, the mobility patterns of the users in different cells should be considered

while organizing the location databases.


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Continued

The location databases should be properly organized, so as not to let the

location management cost go very high.

The location update cost depends on the distance of the two cells.

The cost of communicating with a mobile client is linearly proportional to the cost

of locating the mobile client therefore, consideration of the efficiency of the

proposed techniques is critical.

These techniques are further enhanced with the use of caching, replication,

forwarding pointers and portioning.

Continuous advancements are being made to develop techniques that are more

efficient, thus making the field of mobile computing an active area of research.


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References

[1] Chen Jixiong, Li Guohui, Xu Huajie, Cai Xia, Yang Bing, Location DatabaseClustering to Achieve Location Management Time Cost Reduction in A

Mobile Computing System, IEEE 2005.

[2] Evaggelia Pitoura and George Samaras, Locating Objects in Mobile

Computing, to appear in IEEETransactions on Knowledge and DataEngineering.

[3] Guo-Hui Li, Kam-Yiu Lam and Tei-Wei Kuo, Location Update Generation

in Cellular Mobile Computing Systems, proceedings of the 15th IEEE

International Parallel and Distributed Processing Symposium,2001.

[4] Guo-Hui Li, Kam-Yiu Lam, Tei-Wei Kuo and Shi-Wu Lo, Location

Management in Cellular Mobile Computing Systems with DynamicHierarchical Location Databases.

[5] J. S. M. Ho and I. F. Akyildiz, Dynamic Hierarchical Database Architecture

for Location Management in PCS Networks, IEEE/ACM Transactions on

Networking, 5(5), 1997.

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Mobile Clients - Location Management Strategies