International Journal of Engineering Trends and Technology (IJETT) – Volume 4 Issue 5- May 2013
Adaptive Opportunistic Routing based on Hamlet
Framework for Wireless Ad Hoc Networks
Ch.Rajitha, student, Department of Computer Science,
Vignan’s Nirula Institute of Technology & Science for Women, Guntur, AP, India,
P.Radhika, Professor (Principal), Department of Computer Science,
Vignan’s Nirula Institute of Technology & Science for Women, Guntur, AP, India
K.V. Narasimha Reddy , Asst. Professor, Department of Computer Science,
Vignan’s Nirula Institute of Technology & Science for Women, Guntur, AP, India
Abstract— This paper introduces a cooperation-based database
caching system for Mobile Ad Hoc Networks (MANETs). The
heart of the system is the nodes that cache submitted queries.
The queries are used as indices to data cached in nodes that
previously requested them. We discuss how the system is formed
and how requested data is found if cached, or retrieved from the
external database and then cached. The system comprises Proxy
Caches (PCs), for acting as the interface to remote Web services
and the internally cached service responses, Request Directories
(RDs) for caching the cache keys that act as indexes to the
responses, and finally, the Caching Nodes (CNs) that cache the
responses. This paper based on Hamlet framework allows
MANET users to take caching decisions on content that they
have retrieved from the network. The impact of the Zipf
distribution exponent on the performance of the cache
replacement strategies. We recall that an exponent that is equal
to zero implies perfect homogeneity. Describes a distributed
system designed for environments to cache proxies of consumed
web services and responses of their invoked methods.
Keywords— Privacy-preserving, data publishing, functional
dependency, utility, data reconstruction.
I. INTRODUCTION
Web services have emerged as a popular middleware for
offering Remote Method Invocation. In case of Mobile Ad
hoc Networks (MANET’s) connectivity to external
information source gets disrupted due to device mobility and
disconnection results in empty out the battery power and
device gets switched off. Therefore by using the caching
strategy in the whole MANET’s allows for improvement in
the network as a whole. Cached response of the web service
will be useful only if the future calls use same arguments as
those of response cached. In many situations same calls may
be made in the case of popular web services. Caching the
proxies makes the system to save the time and subsequent call
to the same service doesn’t require downloading (Web Service
Definition Language) WSDL file as done initially.
Web services were built by XML technologies to aid IT
developers to help heterogeneous applications. The
architecture of prevalent web services have three main roles:
service provider, service consumer and integrated registry and
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discover current technology Web services discovery based on
UDDI are designed for such Web services that can provide the
necessity of user dutiful and their necessity of user undutiful
such service qualities are greatly ignored in discovery. With
increasing the number of web services on web, it may be
caused problems as services on web, it may be caused
problems as services are returned that are useless Regardless
details, web services are applications that can be published,
located and invoked by network, for example: [9].
Web services are application components which are based
on XML [2]. Web services can be used by any application
irrespective of platform in which it is developed. Web service
description is provided in WSDL document. It can be
accessed from internet using SOAP protocol. In industry,
many applications are built by calling different web services
available on internet. These applications are highly dependent
on discovering correct and efficient web service. The
discovered web service must match with the input, output,
preconditions and effects specified by the user. Even after
functional matching, QoS parameters also need to be matched
to have best web service from available web services. Web
services developed by different vendors are published on
internet using UDDI [1]. UDDI is the mechanism for
registering and discovering web services. It is platform
independent registry as it is based on extensible markup
language. It allows businesses to give list of services and
describe how they interact with each other. In literature, many
approaches for web service discovery are described some of
which work on UDDI. Search in UDDI is based on keyword
matching which is not efficient as huge number of web
services may match a keyword and it is difficult to find the
best one. Other approaches take advantage of semantic web
concept where web service matching is done using ontologies.
Discovering web services automatically without human
interface is an important concern. Different approaches to for
automatic discovery of web services are also suggested by
authors. This paper is organized as follows: section 2 gives
overview of web service discovery process. Section 3
describes service discovery approaches. We conclude the
paper in section 4.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 4 Issue 5- May 2013
-Taking information of portfolio cost
- Obtaining weather report
- Reserving airport ticket
Web services may use of other web services to perform
their works [5] [9]. In simple word, it can be said that web
service is a traditional web service (like nominating service,
weather report service producing electronic and etc) that is
available by network. Web service follows of a set of
standards that is caused service-consumers who follow of
them to obtain them by network. These standards make the
architecture core of web component [2]. A web service is a
kind of web component. This component makes application
which use of it able to apply this web service methods [7].
Nowadays the security problems are the biggest preventative
ways on deploying the web services. However many efforts
have made in the context of the web services. Still, some of
the problems haven't been solved totally. Such as, to
compatible of access control in the web services.[13][15] The
architecture with weak and distributed connection for the web
services creates challenges in surveying on patents and
applying the access control on different references. Such
architecture hasn't been yet created to control the access of
web services, as they are composed for a special operation.
Different departments have roles with different accesses, so,
the registration of specifications or clients roles is difficult
between different systems [13],[17].
II. BACKGROUND WORK
As format for sending web service request is fixed, some
information in user’s request is lost during transforming user’s
request to formalized one. To overcome this limitation,
context aware web service discovery approach is suggested by
Wenge Rong and Kecheng Liu [4]. Context aware discovery
is useful for request optimization, result optimization and
personalization. As concept of context is very complex, they
suggest with an example that context should be domain
oriented or problem oriented. The context in web service
discovery is formally defined as any information that
explicitly and implicitly affects the user’s web service request
generation. They divide context in two categories as Explicit
and implicit. Explicit context is directly provided by the user
during matchmaking process such as Q&A information.
Implicit context is collected in automatic or semi-automatic
manner. Implicit context is more applicable to web service
discovery as user is not directly involved. Context awareness
is again divided in four categories depending on how context
is collected.
The categories are Personal profile oriented context, Usage
history oriented context, Process oriented context and other
context. Personal profile oriented context is collected using
user’s personal profile which contains personal data,
preferences and other information. Personalization
information such as location, time and user’s situation is used
for decomposing the discovery goal, setting selection criteria
and supplying parameters. Limitation of this method is, it
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makes system architecture more complicated when new
attributes and constraints are introduced. Usage history
oriented context is collected for predicting user’s next
behavior. It is based on assumption that web service requests
by specific user are similar during a certain period of time.
Usage history oriented context is again divided in two
categories as Personal usage history oriented context and
Group usage history oriented context. User’s previous system
interaction can be stored in system log. Log records can be
used to provide recommendation for service selection decision.
But the user may not have similar requirements afterwards. So
Group usage history oriented context is used where web
service matchmaking is based on behavior information of
other user groups in similar situation. One of the examples of
Group oriented context awareness is collaborative filtering
(CF) which may be memory based or content based. Group
oriented context can also be collected from observation data in
particular community. Process oriented context is built from
user sessions.
User reactions to retrieved web services are understood in
particular request session and the discovery is optimized. This
feed based process oriented context can be built using
Probabilistic Latent Semantic Analysis (PLSA) [5]. In case
where single web service is not sufficient to complete user
request, composition of multiple web services is carried out.
In this case, context should be built considering composite
web service discovery process. This approach is better than
traditional keyword matching used in UDDI as user intension
is understood better. By considering that the network
deployment affects the implementation of the context data
distribution in real-world systems, this section discusses
existing and emerging network deployment scenarios. Of
course, the adopted network deployment can lead to different
degrees of connectivity among nodes, and it could implicitly
either favor or hinder the coordination and the communication
among context data sources and sinks. For the sake of clarity,
this section presents the main categories of possible network
deployments; Section 5 compares surveyed solutions to
highlight the main effects of the network deployment on the
context data distribution. First of all, we consider three
principal broad categories of network deployment: i) fixed,
that simply extends the traditional (wired) Internet with
wireless Access Points (APs); ii) ad-hoc, where mobile
entities communicate directly (without infrastructure); and iii)
hybrid, that combines the two previous approaches. In fixed
infrastructure, the context data distribution uses some service
reachable through the wireless infrastructure.
III. METHODS
The Hamlet framework allows wireless users to take
caching decisions on content that they have retrieved from the
network. The process that we devise allows users to take such
decisions by leveraging a node’s local observation, i.e., the
node’s ability to overhear queries and information messages
on the wireless channel. In particular, for each information
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International Journal of Engineering Trends and Technology (IJETT) – Volume 4 Issue 5- May 2013
item, a node records the distance (in hops) of the node that
issues the query, i.e., where a copy of the content is likely to
be stored, and the distance of the node that provides the
information. Based on such observations, the node computes
an index of the information presence in its proximity for each
of the I items. Then, as the node retrieves content that it
requested, it uses the presence index of such an information
item to determine Benchmarking Hamlet: We set the
deterministic caching time in DetCache to 40 s, and we couple
DetCache and Hamlet with both the mitigated flooding and
Eureka techniques for query propagation. We are interested in
the following two fundamental metrics: 1) the ratio of queries
that were successfully solved by the system and 2) the amount
of query traffic that was generated. The latter metric, in
particular, provides an indication of the system effectiveness
in preserving locally rich information content: if queries hit
upon the sought information in one or two hops, then the
query traffic is obviously low. However, whether such a
wealth of information is the result of a resource-inefficient
cache-all-you-see strategy or a sensible cooperative strategy.
Impact of the Zipf Distribution Skewness:
Finally, we study the impact of the Zipf distribution
exponent on the performance of the cache replacement
strategies. We recall that an exponent that is equal to zero
implies perfect homogeneity, i.e., Zipf distribution that
degenerates into a uniform distribution, whereas the difference
in popularity among
content becomes much more unbalanced as the exponent
[16]
grows. We focus on a network where ten items are available
and each node can cache at most one complete item.
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[6]
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CH.Rajitha M.Tech (CSE) Department of Computer Science & Engineering
at Vignan’s Nirula Institute Of Technology & Science for Women, Guntur.
IV. CONCLUSION
This paper presented a novel system that enables nodes
joining the network to take advantage of Web services already
consumed by the network and to contribute by consuming
additional services so that they would be used by other nodes.
The system provides benefits to mobile devices through
reducing the average wait time associated with requesting data
that is supplied by Web services and by decreasing the amount
of traffic in the network which will translate directly to saving
battery power consumption since devices in the network also
forward data packets in addition to being the sources and
destinations of transmitted data.
P.Radhika Professor (Principal) Department of Computer
Science & Engineering at Vignan’s Nirula Institute Of Technology &
Science for Women, Guntur. He guided many projects in the area of
image processing for CSE & IT Departments. His research interests are
in the areas of Datamining and Image Processing.
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ISSN: 2231-5381
K.V.Narasimha Reddy received the B.Tech(CSE) from JNTUH,
M.Tech(C.S.E) from JNTUK he is currently working as an Assistant
Professor & Head of the Department of Computer Science & Engineering at
Vignan’s Nirula Institute Of Technology & Science for Women, Guntur. He
guided many projects in the area of image processing for CSE & IT
Departments. His research interests are in the areas of Datamining and Image
Processing.
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