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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

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

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.

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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.

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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]

Node 1 Data i

Node 2. . . .

Data j. . . .

Node 1

Node 3

1

…

2

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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

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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.

Adaptive Flooding contd…

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Figure 2 : Average data fetching cost vs flooding range

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.

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

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Sender Target Timestamp

Cocktail Resolution Scheme

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Figure 3: The 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.

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.

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Performance Evaluation

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o Access probability of i-th popular data item.

o Request Success ratio: shows data availability

o Average Response Delay: time efficiency

Figure 4: Average response delay

Figure 5: Request success ratio

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.

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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

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Server

H8

P5

H3H2H1 H4 H5 H6

P6 P7 P9 P10 P11 P12P8P4P2P1 P3

H7

Figure 6: Multi-tier architecture

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.

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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.

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