A Case for a Mobility Based Admission Control Policy Shahram Ghandeharizadeh 1, Tooraj Helmi 1, Shyam Kapadia 1, Bhaskar Krishnamachari 1,2 1 Computer Science Dept 2 Electrical Engineering Dept University of Southern California University of Southern California Los Angeles Los Angeles {

Outline What is admission control? What is admission control?  Admission control in C2P2 Architectural Framework Architectural Framework MAD (Mobility prediction based ADmission control policy) MAD (Mobility prediction based ADmission control policy) Results Results Conclusions & Future work Conclusions & Future work

Admission Control A request for a resource (usually data) A request for a resource (usually data)  To admit or not to admit….that is the question  Without disturbing the existing requests being serviced  Who decides?  Client, Server, Negotiation between the two  After how long is the decision made? If enough resources are available If enough resources are available  ADMIT Else Else  REJECT A certain level of QoS is guaranteed A certain level of QoS is guaranteed  End to End Delay  Bandwidth  Packet delivery ratio  Packet loss ratio  Others….

C2P2 C2P2 (Car-to-Car-Peer-to-Peer) Network C2P2 (Car-to-Car-Peer-to-Peer) Network  Example applications video-on-demand, Audio-on-demand etc. C2P2 device C2P2 device roles: Data producer (server), Data forwarder (router), Data consumer (client)

Admission Control in C2P2 Challenges Challenges  No central coordination point  Multiple simultaneous clip downloads  Resource constraints  Hiccups (jitters)  Startup latency  Mobility  Dynamic network connectivity  Resource availability prediction

Framework A request requires all blocks of clip X be downloaded within Tx time units. A request requires all blocks of clip X be downloaded within Tx time units.  Tx = maximum tolerable startup latency  Hiccup free display  E.g. Audio clip X  Display time = 12 minutes  Download time = 1 minute 3 classes of requests 3 classes of requests  K = A + R  A = A f + A g  K= total requests  R= total rejected requests  A g = total admitted requests serviced successfully  A f = total admitted requests that failed

Example illustration of Im and Rm S C Notation: C-Client, S-Server T = 3 minutes Tx = 1 minutes Td = 12 minutes Td = 12 minutes Clip size ~ 30MB Clip size ~ 30MB B download = 30MB/1 minute = 4Mbps < Bmax=10Mbps => ADMIT REQUEST

Framework (contd) Request Metric (R m ) Request Metric (R m )  Amount of resources required for a given request  R m = 100 * Size(X)/(T x *B max ) Information Metric (I m ) Information Metric (I m )  Depends on the state of the network 0<= I m, R m <= 100 0<= I m, R m <= 100 If (I m – R m > Θ) If (I m – R m > Θ)  Admit Else Else  Reject -100<= Θ <= <= Θ <= 100

MAD Client-centric decentralized Client-centric decentralized I m = Σ i=1 S T(s i,C2P2 d ) I m = Σ i=1 S T(s i,C2P2 d ) * *100 N ^ Tx N ^ Tx Notation: Notation:  N^ – total nodes reachable from client via probe  s i – a candidate server  S – total list of all servers  C2P2 d – C2P2 client making the request  T – Time for which s i and C2P2 d are in radio range Mobility prediction based ADmission control policy Mobility prediction based ADmission control policy  Conservative

Typical scenario S C Notation: C-Client, S-Server

Typical scenario

Utility models U M = w R (M)R + w Ag (M)A g + w Af (M)A f U M = w R (M)R + w Ag (M)A g + w Af (M)A f

Experimental Environment 3 servers serving 100 different titles 3 servers serving 100 different titles 13 Clients (1 per road stretch) 13 Clients (1 per road stretch) 10 Mbps per C2P2 device 10 Mbps per C2P2 device Client speed = 5 m/s Client speed = 5 m/s Reach the other end switch direction and move in the opposite direction Reach the other end switch direction and move in the opposite direction Clients chosen randomly once every 60 seconds Clients chosen randomly once every 60 seconds 100 total requests in the experiments 100 total requests in the experiments  Averaged over 10 random seeds Note: Custom simulator written in C# uses DSR as the routing protocol of choice. Road stretches

Utility Results Standard Model U = A g - A f

Results (contd) Satisfied Requests (A g ) Unsatisfied Requests A f

Observations MAD outperforms no-admission control case in case of all the models MAD outperforms no-admission control case in case of all the models Choice of Θ is a function of the utility model Choice of Θ is a function of the utility model  Θ = -20 is conservative  No unsatisfied requests  Constant positive utility with all models  Good for standard and premium models

Related work Admission Control in wired networks Admission Control in wired networks  Erlang B,C QoS in MANETs QoS in MANETs  Part of routing protocol  INSIGNIA[4], CEDAR[6]  Application layer QoS [5, 7] over routing Mobility prediction Mobility prediction  NonStop[8]: Dynamic Data replication

Conclusions MAD   performs orders of magnitude better than the no admission control case   Hence admission control is needed in a C2P2 environment   Optimal threshold for MAD depends on the utility model

Future work Other scenarios   Mobile Servers   Clients with random speed Enhance MAD   Consider available bandwidth at the servers Streaming of clips in C2P2   Hic-cup rate Other topologies like grid etc. Data placement & delivery scheduling issues Replication issues

References [1] S. Ghandeharizadeh and T. Helmi, An Evaluation of Alternative Continuous Media Replication Techniques in Wireless Peer-to-Peer Networks. Third International ACM Workshop on Data Engineering for Wireless and Mobile Access (MobiDE), September [1] S. Ghandeharizadeh and T. Helmi, An Evaluation of Alternative Continuous Media Replication Techniques in Wireless Peer-to-Peer Networks. Third International ACM Workshop on Data Engineering for Wireless and Mobile Access (MobiDE), September [2] S. Ghandeharizadeh, B. Krishnamachari, S. Song, Placement of Continuous Media in Wireless Peer-to-Peer Networks. IEEE Transactions on Multimedia, April 2004 [2] S. Ghandeharizadeh, B. Krishnamachari, S. Song, Placement of Continuous Media in Wireless Peer-to-Peer Networks. IEEE Transactions on Multimedia, April 2004 [3] E. Knightly and S. Shroff, “Admission Control for Statistical QoS: Theory and Practice”, IEEE Network, vol. 13, no. 2, pp , 1999 [3] E. Knightly and S. Shroff, “Admission Control for Statistical QoS: Theory and Practice”, IEEE Network, vol. 13, no. 2, pp , 1999 [4] S. Le, G. Ahn, X. Zhang and A. Campbell, INSIGNIA: An IP-based Quality of Service Framework for Mobile Ad Hoc Networks., Journal of Parallel and Distributed Computing, 60(4): , 2000 [4] S. Le, G. Ahn, X. Zhang and A. Campbell, INSIGNIA: An IP-based Quality of Service Framework for Mobile Ad Hoc Networks., Journal of Parallel and Distributed Computing, 60(4): , 2000 [5] H. Xiao, W. Seah, A. Lo and K. Chua, A Flexible Quality of Service Model for Mobile Ad-Hoc Networks, IEEE VTC 2000 [5] H. Xiao, W. Seah, A. Lo and K. Chua, A Flexible Quality of Service Model for Mobile Ad-Hoc Networks, IEEE VTC 2000 [6] P. Sinha, R. Sivakumar and V. Bhargavan, CEDAR: A Core-Extraction Distributed Ad Hoc Routing Algorithm, INFOCOM 1999, pg [6] P. Sinha, R. Sivakumar and V. Bhargavan, CEDAR: A Core-Extraction Distributed Ad Hoc Routing Algorithm, INFOCOM 1999, pg [7] E. Pagani, G. Rossi, A Framework for Admission Control of QoS multicast traffic in mobile Ad Hoc Networks, Fourth International ACM Workshop on Wireless Multimedia 2001, pg [7] E. Pagani, G. Rossi, A Framework for Admission Control of QoS multicast traffic in mobile Ad Hoc Networks, Fourth International ACM Workshop on Wireless Multimedia 2001, pg 2-11.

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