Distributed Cooperative Caching in SWNET

Distributed Cooperative Caching in Social

Wireless Networks

ABSTRACT:

This paper introduces cooperative caching policies for minimizing electronic content provisioning cost in Social Wireless Networks (SWNET). SWNETs are formed by mobile devices, such as data enabled phones, electronic book readers etc., sharing common interests in electronic content, and physically gathering together in public places. Electronic object caching in such SWNETs are shown to be able to reduce the content provisioning cost which depends heavily on the service and pricing dependences among various stakeholders including content providers (CP), network service providers, and End Consumers (EC). Drawing motivation from Amazon’s Kindle electronic book delivery business, this paper develops practical network, service, and pricing models which are then used for creating two object caching strategies for minimizing content provisioning costs in networks with homogenous and heterogeneous object demands. The paper constructs analytical and simulation models for analyzing the proposed caching strategies in the presence of selfish users that deviate from network-wide cost-optimal policies. It also reports results from an Android phone based prototype SWNET, validating the presented analytical and simulation results.

Architecture Diagram:

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EXISTING SYSTEM:

With the existence of such SWNETs, an alternative approach to content access by a device would be to first search the local SWNET for the requested content before downloading it from the CP’s server. The expected content provisioning cost of such an approach can be significantly lower since the download cost to the CSP would be avoided when the content is found within the local SWNET. This mechanism is termed as cooperative caching. In order to encourage the End-Consumers (EC) to cache previously downloaded content and to share it with other end-consumers, a peer-to-peer rebate mechanism is proposed. This mechanism can serve as an incentive so that the end-consumers are enticed to participate in cooperative content caching in spite of the storage and energy costs. In order for cooperative caching to provide cost benefits, this peer-to-peer rebate must be dimensioned to be smaller than the content download cost paid to the CSP. This rebate should be factored in the content provider’s overall cost.

Disadvantages:

Due to their limited storage,the main server speed could become slow. This means after downloading and using a content, a content to be stored in local cache.

PROPOSED SYSTEM:

In this paper drawing motivation from Amazon’s Kindle electronic book delivery business, this paper develops practical network, service, and pricing models which are then used for creating two object caching strategies for minimizing content provisioning costs in networks with homogenous and heterogeneous object demands. The paper constructs analytical and simulation models for analyzing the proposed caching strategies in the presence of selfish users that deviate from network-wide cost-optimal policies

Advantages:

- Based on a practical service and pricing case, a stochastic model for the content provider’s cost computation is developed.
- A cooperative caching strategy, Split Cache, is proposed, numerically analyzed, and theoretically proven to provide optimal object placement for networks with homogenous content demands.
- A benefit-based strategy, Distributed Benefit, is proposed to minimize the provisioning cost in heterogeneous networks consisting of nodes with different content request rates and patterns.
- The impacts of user selfishness on object provisioning cost and earned rebate is analyzed.

Implementation Modules:

1. Network Model
2. Search Model
3. Pricing Model

Network Model:

We consider two types of SWNETs. The first one involves stationary SWNETpartitions. Meaning, after a partition is formed, it is maintained for sufficiently long so that the cooperative object caches can be formed and reach steady states. We also investigate a second type to explore as to what happens when the stationary assumption is relaxed. To investigate this effect, caching is applied to SWNETs formed using human interaction traces obtained from a set of real SWNET nodes .

Search Model:

We search the file means,itfirst searches its local cache. If the local search fails, itsearches the object within its SWNET partition using limitedbroadcast message. If the search in partition also fails, theobject is downloaded from the CP’s server. In this paper, we have modeledobjects such as electronic books, music, etc., which are timenonvarying, and therefore cache consistency is not a criticalissue. Thepopularity-tag of an object indicates its global popularity; italso indicates the probability that an arbitrary request in thenetwork is generated for this specific object.

Pricing Model:

We use a pricing model similar to the Amazon Kindle business model in which the CP pays a download cost Cd to the CSP when an End-Consumer downloads an object from the CP’s server through the CSP’s cellular network. Also, whenever an EC provides a locally cached object to another EC within its local SWNET partition, the provider EC is paid a rebate Cr by the CP. Optionally, this rebate can also be distributed among the provider EC and the ECs of all the intermediate mobile devices that take part in content forwarding .The selling price is directly paid to the CP by an EC through an out-of-band secure payment system. A digitally signed rebate framework needs to be supported so that the rebate recipient ECs can electronically validate and redeem the rebate with the CP. We assume the presence of these two mechanisms on which the proposed caching mechanism is built.

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System Configuration:

HARDWARE REQUIREMENTS :

Hardware - Pentium

Speed - 1.1 GHz

RAM - 1GB

Hard Disk - 20 GB

Floppy Drive - 1.44 MB

Key Board - Standard Windows Keyboard

Mouse - Two or Three Button Mouse

Monitor - SVGA

SOFTWARE REQUIREMENTS:

Operating System : Windows

Technology : Java and J2EE

Web Technologies : Html, JavaScript, CSS

IDE : My Eclipse

Web Server : Tomcat

Tool kit : Android Phone

Database : My SQL

Java Version : J2SDK1.5