1 / 16

Paper: COOP- A cooperative caching service in MANETs

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

meryl
Download Presentation

Paper: COOP- A cooperative caching service in MANETs

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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.

More Related