Paper: COOP- A cooperative caching service in MANETs

1. Paper: COOP- A cooperative caching service in MANETs Author:Y. Du and S. K. S. Gupta Proceedings:ICAS-ICNS 2005. Joint International Conference on, Tahiti, French Polynesia, pp 58-63, Oct. 23-28, 2005 Presented By: Aarti Munjal PhD(CSE) Arizona State University CSE 535: Mobile Computing Paper presentation

2. Contents • Background • Motivation • Related Work & Contributions • COOP - Overview • Cache Resolution • Cache Management • Performance Evaluation • Related to class • Use in Project • Future Work

3. Background • Mobile ad hoc networks(MANETs) are constrained in terms of resources and lack of infrastructure. • Routing techniques need to take care of these facts. • There are disconnections(among nodes) and failures(at node level due to battery power etc.) which lead to loss of data. • Real-time data availability becomes a challenge in such a scenario.

4. Motivation • Performance of routing protocols can be improved either by providing MAC layer, network or transport layer solutions. • One more possibility exists that is explored by this paper: solution at application layer. • Nodes can cooperate to localize the communication which leads to conservation of energy, time as well as bandwidth. • Solution has to be • efficient - due to constrained resources. • self-adaptive - due to dynamic nature of the network. • Scalable – increase in number of nodes does not affect the performance.

5. Related Work & Contributions • Caching has been used as solution to reduce the data access time • Hierarchical caching [1] • Directory based caching [2] • Hash-table based [3] • Cache data, cache path and hybrid cache [4] 1 Node 1 2 Node 3 …

6. COOP - Overview • Aim: • To improve data availability and access efficiency. • Cooperative Caching: • Cache Resolution: where to fetch the data requested by the user. • Cache Management: due to memory constraints involved, which data to purge to make room for the other information. Figure 1: System Model

7. Cache Resolution • Adaptive Flooding: • Flooding • to know neighbors and introduce yourself. • affects the performance of a protocol. • Calculates proper flooding range. • Cost of fetching data : x + Ls (distance of cache containing data) (distance to original data source) • Average Cost: • Pd = probability that each node caches data. • λ = average node density. • λπx2 =number of nodes in x-hop range. • 1- (1 - Pd) λπx2=probability to discover data in cache within x-hop range • X + Ls(1 - Pd) λπx2= average cost of fetching.

8. Adaptive Flooding contd… Few important points: i) To achieve minimum average data fetching cost, the optimal flooding range increases very slowly. ii) If λ increases, x shall be reduced accordingly. iii) Limited flooding minimizes the average data fetching cost. Figure 2 : Average data fetching cost vs flooding range

9. Profile-based Resolution • Avoids duplicate flooding by storing history of previous requests in Recent Requests Table (RRT). • Each entry of RRT contains: • On a data request, every node checks its local cache first. • Upon cache miss, RRT is searched for the corresponding entry. Data source selected = mindistance {matching entry , original data source }, if a match is found in RRT Adaptive flooding used and corresponding entry removed , otherwise

10. Cocktail Resolution Scheme • Roadside Resolution • Data request needs to be forwarded to original data source. • Request starts from sender to target. • Any forwarding node in the path checks its own cache first, if cache hit then stops forwarding the request and sends the data back. • In case no data is found, if it finds another data source nearby, it redirects the data request to that node. • Otherwise, the request is juts forwarded towards the target node. Figure 3: The Cocktail Resolution Scheme

11. Cache Management • Maximizes distinct data availability by reducing duplicated cache in short-distance neighborhood. • Data categorized: • Primary data - data unavailable in neighborhood (neighborhood range is customizable). • Secondary data - data available in neighborhood. • Rules deciding the category of a data item • Inter-category rule • Fetched a data item, label of data = primary, if comes from outside neighborhood range or from within neighborhood but has been labeled secondary there and the primary copy holder is out of range. secondary, otherwise. • Intra-category rule • For data items within the same category (primary/secondary). • LRU is used for the same purpose.

12. Performance Evaluation • Access probability of i-thpopular data item. • Request Success ratio: shows data availability • Average Response Delay: time efficiency Figure 4: Average response delay Figure 5: Request success ratio

13. Relevance to Mobile Computing • Disconnections and failures in mobile environments are quite frequent(due to several reasons). • In order to make sure that data availability is not affected due to that, there are several solutions that can be looked at. • Caching the data is one among those solutions. • Caching can be very extensive depending upon the applications. • For instance, context-awareness can be added which leads us to cache the data and change the caching strategy depending upon the context. • These are few topics we have looked at in ’Mobile Computing’ course – CSE 535.

14. Relevance to our project –A Context Aware Caching Scheme for Real-Time Health Monitoring Systems • Multi-tier architecture adopted to improve scalability. • To provide real-time data even during disconnections and failure, caching is required. • Cache Resolution • Cache Management Server H7 H8 H1 H2 H3 H4 H5 H6 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 Figure 6: Multi-tier architecture

15. Conclusions & Future Work • Cooperative Caching – higher data availability. • Time cost reduced by using cock-tail approach for cache resolution. • Inter-category and intra-category rules used to minimize the data redundancy. • Caching scheme can be associated with context-awareness to make it adaptive so that it suits the very nature of MANETs. • To make it suitable for energy-efficient routing, few modifications can be made, for instance incorporating ‘remaining energy of a node’. • Different radius values(cooperation zones) can be employed to see the effect of cooperation among nodes.

16. References: • A. Chankhunthod et al. A hierarchical internet object cache. In USENIX Annual Technical Conference, 1996. • L. Fan et al. Summary cache: a scalable wide-area web cache sharing protocol. In Sigcomm, 1998. • S. Lyer et al. Squirrel: A decentralized peer-to-peer web cache. In PODC, 2002. • G. Cao et al. Cooperative cache based data access in ad hoc networks. IEEE Computer, 37(2):32–39, Feburary 2004.