1. A New Broadcasting Technique for An Adaptive Hybrid Data Delivery in Wireless Mobile Network Environment JungHwan Oh, Kien A. Hua, and Kiran Prabhakara Proceeding of IEEE International Conference on Performance, Computing and Communications, 2000.

2. Broadcast Structure  ATI (Access Time for Index)  TTI (Tuning Time for Index)  ATD (Access Time for Data)  CTD (Complete Time for Data)

3. Broadcast Structure  An index segment broadcasts only once during one broadcast cycle.  Problem: The ATI is almost one whole broadcast cycle in worst case. The ATI is almost one whole broadcast cycle in worst case.

4. Modified Broadcast Structure  The index segment broadcasts several times (say, d times) during one broadcast cycle.  Problem: To find an optimal value of d is not easy, especially, under a real situation such that the client demanding patterns cannot be predicted in advance. To find an optimal value of d is not easy, especially, under a real situation such that the client demanding patterns cannot be predicted in advance.

5. Modified Broadcast Structure  Index segments are not interleaved with data blocks but separated independently.  Problem: How much bandwidth should be assigned to the index broadcasting or whether the bandwidth amount assigned to the index broadcasting should be fixed or variable. How much bandwidth should be assigned to the index broadcasting or whether the bandwidth amount assigned to the index broadcasting should be fixed or variable.

6. Non-Uniform Broadcasting (Sequential Push)  A hybrid of broadcast and unicast (on-demand) to get full advantages of each.  Non-uniform broadcasting can broadcast more popular data objects more frequently.  Problem1: previous broadcast cycle: non-popular  discard  previous broadcast cycle: non-popular  discard  current broadcast cycle: many explicit requests  insert current broadcast cycle: many explicit requests  insert next broadcast cycle: nobody wants this data object next broadcast cycle: nobody wants this data object ( because it is impossible to perceive the rapidly changing ( because it is impossible to perceive the rapidly changing clients’ access patterns at once) Solution1 clients’ access patterns at once) Solution1 Solution1

7. Non-Uniform Broadcasting (Sequential Push)  Problem2: It can only broadcast a data object 2 k times (where k=0,1,2,…) more frequently than others, so it cannot broadcast very closely to the popularity of data objects. It can only broadcast a data object 2 k times (where k=0,1,2,…) more frequently than others, so it cannot broadcast very closely to the popularity of data objects. Solution2 Solution2 Solution2

8. Non-Uniform Broadcasting (Sequential Push)  Problem3: ◎ If a client misses the desired data block through current index segment, it should wait one whole broadcasting cycle. index segment, it should wait one whole broadcasting cycle. ◎ ATD is one whole broadcasting cycle in worst case. ◎ ATD is one whole broadcasting cycle in worst case. ◎ One broadcasting cycle is much longer in non-uniform ◎ One broadcasting cycle is much longer in non-uniform broadcasting. Solution3 broadcasting. Solution3 Solution3

9. New Broadcasting Structure (Parallel Push)  The total bandwidth is divided into three parts logically: ◎ Broadcasting index block ◎ Broadcasting data blocks ◎ Unicasting (on-demand) data blocks ◎ Unicasting (on-demand) data blocks  The amount of bandwidth assigned for each part changes dynamically according to client’s request patterns.

10. New Broadcasting Structure (Parallel Push)  The total bandwidth is divided into equal size and as many as possible number of channels.  more bandwidth  more popular  more explicit requests  add channels (until few explicit requests)  few explicit requests (for a certain period)  reduce channels  still fewer or no explicit requests  reduce channels (eventually omit the data object)  still fewer or no explicit requests  reduce channels (eventually omit the data object)  The popularity of the data objects is determined interactively and dynamically.

11. New Broadcasting Structure (Parallel Push)  Solution1: decreasing channels  if receive explicit requests, reincrease channels; otherwise, keep decreasing channels Problem1 if receive explicit requests, reincrease channels; otherwise, keep decreasing channels Problem1 Problem1

12. New Broadcasting Structure (Parallel Push)  Solution2: ◎ Since the channel is relatively small, a server can precisely assign the necessary bandwidth for each precisely assign the necessary bandwidth for each data according to its popularity. data according to its popularity. ◎ A server can run the service smoothly since it can ◎ A server can run the service smoothly since it can avoid abrupt increases of explicit requests. Problem2 avoid abrupt increases of explicit requests. Problem2 Problem2

13. New Broadcasting Structure (Parallel Push)  Solution3: ◎ ATD is zero. ◎ ATD is zero. ◎ A client can download at anytime. ◎ A client can download at anytime. Problem3 Problem3 Problem3

14. Simulation  The access frequency of requesting various data objects is assumed to be governed by the Zipf-like distribution as, where v is the total number of different data objects in the system, z (skew factor) is Zipf parameter., where v is the total number of different data objects in the system, z (skew factor) is Zipf parameter.  A larger z corresponds to a more skewed condition, i.e., z=0.8 means that around 80% of total requests will be for a particular 20% subset of the data objects. of the data objects.

15. Simulation  Pure-Push (pure broadcasting)  Hybrid (Hybrid with non-uniform broadcasting)  AHS (Adaptive Hybird data delivery Scheme)

16. Simulation  ATI (Access Time for Index)  TTI (Tuning Time for Index)  ATD (Access Time for Data)  CTD (Complete Time for Data)  AT (Access Time) = ATI + TTI + ATD  CT (Complete Time) = AT + CTD

17. Effect of Arrival Rate

18. Effect of Skew Factor

19. Effect of Dynamic Workloads