Authors: Md. Mohsin Ali* Md. Amjad Hossain Md. Kowsar Hossain G. M. Mashrur-E-Elahi Md. Asadul Islam

Transcription

1 Authors: Md. Mohsin Ali* Md. Amjad Hossain Md. Kowsar Hossain G. M. Mashrur-E-Elahi Md. Asadul Islam Khulna University of Engineering & Technology (KUET)

2 2 Introduction Components of Wireless Mobile Networks: Mobile Host (MH) End-user device Base Station (BS) Transmits signals to Cell Cell Contains one BS Registration Area (RA) Contains several Cells Mobile Switching Center (MSC) Used for call switching Visitor Location Resister (VLR) Distributed database Contains MH s current Cell information Home Location Register (HLR) Centralized database Contains MH s current VLR information 2

3 3 Introduction (Contd.) Basic operations of location management: Location update On VLR On HLR MH move from one Cell to another one Intra-subnet handoff MH move from one RA to another one Inter-subnet handoff Call delivery To find out called MH Finding out serving VLR Finding out serving Cell Call establishment between calling and called MHs Location server s load On VLR On HLR Depends on frequency of call forwarded to its RA Relatively low load Depends on total call generation in the whole network Relatively high load 3

4 Related Work Basic IS-41 scheme 4 Centralized database scheme Hashing and caching scheme 4

5 5 Related Work (Contd.) Basic IS-41 scheme Centralized HLR Distributed VLR No VLR cache Query on HLR for every call Centralized database scheme Centralized HLR Distributed VLR But, VLR cache Cache is replicated where more call is generated For each call delivery Query on cache at first for called MH: if cache hit, then call is established Otherwise query on HLR for that No cache update For each call receiving No cache update 5

6 6 Related Work (Contd.) Hashing and caching scheme Distributed HLR With identical replicated database Distributed VLR VLR cache All VLR own caches For each call delivery Query on cache at first for called MH: if cache hit, then call is established Otherwise query on HLR (selected by hashing function) for that Cache update Calling MH s cache is updated with called MH s ID For each call receiving No cache update One call, one location update in cache 6

7 7 Proposed Method New hashing and caching approach Distributed HLR With identical replicated database Distributed VLR VLR cache All VLR own caches For each call delivery Query on cache at first for called MH: if cache hit, then call is established Otherwise query on HLR (selected by hashing function) for that Cache update Calling MH s cache is updated with called MH s ID For each call receiving Cache update Called MH s cache is updated with calling MH s ID One call, two location updates in cache 7

8 8 Proposed Method (Contd.) Hashing Function SERVERID = f (MHID, VLRID, m) = (MHID + VLRID) mod m Used to select one of m HLRs Distributes HLR s load to m HLRs Handoff Select new SERVERID for new location MH s new location is updated to that server Multicasts this to remaining (m - 1) HLRs 8

9 Proposed Method (Contd.) Start 9 Call receiving Call arrival, or receiving or handoff? Handoff Select new location server for MHs new location using hashing function No MH s location information in cache? Cache hit? Yes No Yes Call established Yes MH s location informatio n in cache? Call arrival Yes Cach e hit? No MHs new location information is updated in that new server This server multicasts this information to remaining m-1 location servers Update or save MH s location information in cache No Find MHs location from server selected by hashing function Come back to that location server Go to VLR containing the address of called MH Fig. 4. Flow chart of the proposed method. 9

10 Analytical Model HLR 10 Call delivery cost C h C h C h C h Basic IS-41 scheme Database access cost Calling VLR Calling VLR (D v ), HLR (D h ), called VLR (D v ) Total access cost = 2D v + D h Signaling cost Two signaling between calling VLR and HLR (2C h ) Two signaling between HLR and called VLR (2C h ), One signaling between calling VLR and called VLR (C v ). Total signaling cost = 4C h + C v Total call delivery cost, C b = 4C h + C v +2D v + D h C v Fig. 5. Access and signaling costs Called VLR 10

11 11 Analytical Model (Contd.) Call delivery cost (Contd.) Hashing and caching scheme Let q = Probability that the location information is in the cache p = Cache hit ratio C ch = Average call delivery cost if the location information is in the cache λ = Mean call arrival rate λ max = Maximum call arrival rate µ m = Mean mobility rate Cache access and update cost is negligible Average call delivery cost, Where C ch =p C v +(1 p) (C v +C b ) p = q = λ ( λ+μ m ) λ λ max C c =q C ch +(1 q) C b 11

12 12 Analytical Model (Contd.) Call delivery cost (Contd.) New hashing and caching scheme (Proposed) Also let λ r = Mean call receiving rate λ r = Maximum call receiving rate max Average call delivery cost,, C cr =C c =q C ch +(1 q) C b but it is different from hashing and caching scheme with respect to q and p Where C ch = same as that of hashing and caching scheme p = if λ r = λ, then p = q = if λ r = λ and λ r =λ, then max max q = λ ( λ r +1) {λ ( λ r +1)+μ m } λ +(1 λ ) λ r λ max λ max 2λ λ2 λ max λ max 2 λ r max λ 2 +λ ( λ 2 +λ+μ m ) 12

13 Analytical Model (Contd.) 13 Location server s load Basic IS-41 scheme One location server (HLR) Call arrival time are independent and exponentially distributed with parameter λ Service time are also exponentially distributed Modeled as M/M/1 queuing system So, system throughput is equal to λ 13

14 Analytical Model (Contd.) 14 Location server s load (Contd.) Hashing and caching scheme m location servers (HLR) Also let x c = Throughput of anyone of the m location servers λ s = Call arrival rate at server i, i = 1, 2,, m p r i = Probability of querying to server i λ. s =λ p r i (1 q) Each server is selected uniformly, so Modeled as m number of M/M/1 queuing system Throughput of location server, server i, x c =λ s =λ 1 q m q = λ, where p r i = 1 m λ max 14

15 Analytical Model (Contd.) 15 Location server s load (Contd.) New hashing and caching scheme (Proposed) Throughput of location server, server i, x c =λ s =λ 1 q m, where q = if λ r = λ and, then q = λ +(1 λ ) λ r λ max λ max 2λ λ2 λ max λ max 2 λ r max λ r max =λ max 15

16 Experimental Results Average call delivery cost 16 Fig. 6. Performance comparison of basic IS-41, hashing and caching and proposed schemes based on average call delivery cost. 16

17 Experimental Results (Contd.) Location server s load 17 Fig. 7. Performance comparison of basic IS-41, hashing and caching and proposed schemes based on location server s load. 17

18 18 Conclusion One call, two location updates in cache in new proposed method During call delivery and receiving But, one call one location update in cache in most recent previous method During call delivery time only So, The more call, the more cache update The more cache update, the higher values of p and q The higher values of p and q, the lower values of call delivery cost and location server s load 18

19 19 Future Work More appropriate hashing function Location server s load and congestion minimization 19

20 20 References EIA/TIA. Cellular radio-telecommunications intersystem operations, Tech. Rep. IS- 41 Revision B, EIA/TIA, December M. Mouly and M.B. Pautet, The GSM system for mobile communications, 49 rue Louise Bruneau, Palaiseau, France, Telecom Publishing, January Chang Woo Pyo, Jie Li, Hisao Kameda, and Xiaohua Jia, Dynamic Location Management with Caching in Hierarchical Databases for Mobile Networks, DNIS 2002, LNCS 2544, Springer-Verlag, vol. 2544, pp , Berlin/Heidelberg, December Weiping He and Athman Bouguettaya, Using Hashing and Caching for Location Management in Wireless Mobile Systems, MDM 2003, LNCS 2574, Springer-Verlag, vol. 2574, pp , Berlin/Heidelberg, January I. Akyildiz, J. McNair, J. Ho, H. Uzunalioglu, and W. Wang, Mobility management in next-generation wireless systems, In Proceedings of the IEEE, vol. 87, no. 8, pp , August Y. Bejerano and I. Cidon, An efficient mobility management strategy for personal communication systems, In The Fourth Annual ACM/IEEE International Conference on Mobile Computing and Networking, ACM Publishers, pp , Dallas, Texas, United States, October A. Bouguettaya, On the construction of mobile database management systems, In The Australian Workshop on Mobile Computing & Databases & Applications, Melbourne, Australia, February E. Pitoura and G. Samaras, Data Management for Mobile Computing, vol. 10, Kluwer Academic Publishers, R. Prakash and M. Singhal, Dynamic hashing + quorum = efficient location management for mobile computing systems, In Proceedings of the Sixteenth Annual ACM Symposium on Principles of Distributed Computing, ACM Press Publisher, pp. 291, August

21 21 Thank you very much 21