On a Cooperation of Broadcast Scheduling and Base Station Caching in the Hybrid Wireless Broadcast Environment

Transcription

1 On a Cooperation of Broadcast Scheduling and Base Station Caching in the Hybrid Wireless Broadcast Environment Jing Cai, Tsutomu Terada, Takahiro Hara, and Shojiro Nishio

2 Outline Background Hybrid Wireless Broadcast (HWB) model Efficient control of HWB system Consider heterogeneous and homogeneous access Cooperate broadcast scheduling and base station caching Experimental results Conclusion

3 Background Wireless information service Hotspot service 3G, 4G service Data broadcasting Satellite data broadcast Terrestrial data broadcast Hybrid data delivery Combination &. management

4 HWB Model [Cai 05] (1/2) (Hybrid Wireless Broadcast ) Internet Broadcast Server Base Station Client

5 HWB Model [Cai 05] (2/2) Broadcast Server A B C E D DB Main Channel Sub Channel Wireless Channel Client Base Station

6 Application Example Here is the guide Main channel Here is the guide Sub channel Internet Where is the Osaka Univ.? Broadcast Server Base No cache Station / Long W. T. Client Here is the guide

7 Complementary Features (1/2) Channel Dissemination Data Mode Service Range Bandwidth Main Channel Push-based broadcast Periodically Schedule Global High Sub Channel Pull-based broadcast Non-periodically Ondemand Global Middle Wireless Channel of BS Pull-based point-to-point wireless communication Ondemand Local Low

8 Complementary Features (2/2) Channel Merit Demerit Main Channel Sub Channel Wireless Channel of BS Response not affected by the query load Meet requirements of global clients On-demand response can be shared Meet requirements of local clients Provide efficient local information Access latency depends on the volume of broadcast Access latency increase with the number of different queries On-demand response cannot be shared

9 Control of HWB System Broadcast scheduling Flat broadcast Multi-Disks (MD) broadcast Caching of base station Probability-based caching PIX caching

10 Related techniques (1/5) Broadcast scheduling Flat broadcast Multi-Disks (MD) broadcast A B C D E F G H I J K

11 Related techniques (2/5) Broadcast scheduling Flat broadcast Multi-Disks (MD) broadcast Hot A B C D E F G H I J K Cold

12 Related techniques (3/5) Broadcast scheduling Flat broadcast Multi-Disks (MD) broadcast Caching Probability-based caching PIX caching

13 Related techniques (4/5) Broadcast Disks all Database Schedule PIX Client Cache PIX PIX PIX=Access Probability / Broadcast Frequency

14 Related techniques (5/5) Cooperation of broadcast scheduling and cache management Push-based broadcasting Cache at client side Extended consideration Hybrid broadcasting environments? Heterogeneous and homogeneous access?

15 Research Purpose Efficient control of HWB system Cooperate base station caching with broadcast scheduling Take account of heterogeneous and homogeneous access of clients Take advantage of the HWB data dissemination

16 Cooperative Control in HWB (1/3) Cooperation in the HWB environment Base station cache Consider homogeneous access of local clients Increase cache hits Broadcast of main channel Consider heterogeneous access in different regions Shorten broadcast cycle (no_ca scheduling) On demand sub channel Pull the items disappeared in the main channel and without the required cache-resident

17 Cooperative Control in HWB (2/3) no_ca data Database Schedule Main Channel Sub Channel Base Station Cache

18 Cooperative Control in HWB (3/3) Two-phase access probability Local Access Probability (LAP) For each base station Global Access Probability (GAP) For the broadcast server

19 Access Probability GAP LAP LAP LAP Broadcast Server Base Station Client Query

20 Cooperation Strategy Scheduling Caching GAP no_ca GAP-no_Ca all GAP-all LAP LAP-no_Ca LAP-all PIX PIX-no_Ca PIX-all

21 GAP - no_ca no_ca Database Schedule GAP Base Station Cache GAP GAP GAP

22 LAP - no_ca no_ca Database Schedule LAP Base Station Cache LAP LAP LAP

23 LAP - all all Database Schedule LAP Base Station Cache LAP LAP LAP

24 Simulation Environment Parameters Average waiting time Success rate Values Database Size [ Data Items ] 10,000 Data Item Size [ KB ] 100 Number of Base Station (BS) 10 Cache Size of BS [ Data Items ] 200 Main Channel Bandwidth [ Mbps ] 100 Sub Channel Bandwidth [ Mbps ] 10 Wireless Channel Bandwidth [ Mbps ] 5 Number of Disks 3 Broadcast Frequency of Disk 1, 2, 3 4, 2, 1 Size of Disk 1, 2, 3 [ Data Items ] 500, 1000, uncertain

25 Impact of Query Frequency Average Waiting Time (s) GAP-no_Ca LAP-no_Ca LAP-all PIX-all Query Interval (ms) Success Rate GAP-no_Ca LAP-no_Ca LAP-all PIX-all Query Interval (ms)

26 Impact of Query Deviation GAP-no_Ca Average Waiting Time (s) Success Rate LAP-no_Ca LAP-all PIX-all Deviation for Skewed Query GAP-no_Ca LAP-no_Ca LAP-all PIX-all Deviation for Skewed Query

27 Summary of Evaluation LAP-no_Ca outperforms the others under ordinary condition Shorten average waiting time Heighten success rate Advantage Effective use of the HWB data dissemination Efficient cooperation of base station caching and broadcast scheduling Further improvement Under a dynamic complicated circumstance

28 Conclusion An efficient integrated control of the HWB system Cooperation of broadcast scheduling and base station caching A set of simulation studies Performance confirmation Future work Dynamic control of the HWB system

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