Optimal Bandwidth Assignment for Multiple-Description-Coded Video

Optimal Bandwidth Assignment for Multiple-Description-Coded Video

ABSTRACT:

In video streaming over multicast network, user bandwidth requirement is often heterogeneous possibly with orders of magnitude difference (say, from hundreds of kb/s for mobile devices to tens of Mb/s for high-definition TV). Multiple descriptions coding (MDC) can be used to address this bandwidth heterogeneity issue. In MDC, the video source is encoded into multiple independent descriptions. A receiver, depending on its available bandwidth, joins different descriptions to meet their bandwidth requirements. An important but challenging problem for MDC video multicast is how to assign bandwidth to each description in order to maximize overall user satisfaction. In this paper,we investigate this issue by formulating it as an optimization problem, with the objective to maximize user bandwidth experience by taking into account the encoding inefficiency due to MDC. We prove that the optimization problem is NP-hard. However, if the description number is larger than or equal to a certain threshold (e.g., if the minimum and maximum bandwidth requirements are 100 kb/s and 10 Mb/s, respectively, such threshold is seven descriptions), there is an exact and simple solution to achieve maximum user satisfaction, i.e., meeting all the bandwidth requirements. For the case when the description number is smaller, we present an efficient heuristic called simulated annealing for MDC bandwidth assignment (SAMBA) to assign bandwidth to each description given the distribution of user bandwidth requirement. We evaluate our algorithm using simulations. SAMBA achieves virtually the same optimal performance basedon exhaustive search. By comparing with other assignment algorithms, SAMBA significantly improves user satisfaction. We also show that, if the coding efficiency decreases with the number of descriptions, there is an optimal description number to achieve maximal user satisfaction.

EXISTING SYSTEM

· In media streaming, the Internet’s intrinsic heterogeneity continues a challenging problem. End users may have different edge bandwidth for data receiving or forwarding, especially in large-scale streaming with hundreds of thousands of users.

· Description coding rates have straightforward impact to the delivery performance. If a description has a high coding rate, some network paths may not have enough bandwidth to support its delivery. The loss rate of the description will be high. On the other hand, if descriptions have low coding rates, the number of descriptions and accordingly the coding cost will be high.

PROPOSED SYSTEM

• We propose an adaptive approach to adjust description coding rates according to the user bandwidth distribution.
• Our target is to provide the best streaming quality under certain network bandwidth constraint.
• We formulate the problem and address it by an adaptive solution. Our results show that arbitrary description rates may severely degrade system performance and an optimal solution can make significant improvement on the use of network bandwidth.

Hardware Requirements:

• System : Pentium IV 2.4 GHz.

• Hard Disk : 40 GB.

• Floppy Drive : 1.44 Mb.

• Monitor : 15 VGA Colour.

• Mouse : Logitech.

• Ram : 256 Mb.

Software Requirements:

• Operating system : - Windows XP Professional.

• Coding Language : - Java.

• Tool Used : - Eclipse.

ALGORITHM & EXPLANATION

Using our algorithm, an optimal streaming rate and a set of optimal description rates could be computed. While the algorithm has been shown to be efficient through simulations, there are still many practical issues unaddressed. One challenge is how frequently the descriptions rates should be adjusted. If the network is highly dynamic, a highly frequent adjustment may better serve users. However, the cost for calculation would accordingly increase. We need to achieve proper tradeoff between the solution performance and the cost. Another challenge is to refine the problem formulation by considering very small descriptions. That is, some description rates from the optimal solution may be too low for practical MDC encoding. We should set a lower bound for the description coding rate, and prevent the algorithm from generating descriptions with lower rates than the bound.

Modules:

1. Source Partitioning.
2. Bandwidth Optimization.
3. Encodes Streaming Data.

Module Description:

Source Partitioning

The media source data will be converted into multiple streaming data. The original data will be partitioning into multiple streaming data for sets the descriptions. These partitions based on network bandwidth like its based on the users.

Bandwidth Optimization

One traditional solution is to offer multi-rate video at the source side and to allow users to receive video data at different rates according to their respective bandwidth. MDC is one example of multi-rate video coding method. In MDC, data are encoded into several descriptions, which are independent of each other. When all the descriptions are received, the original data can be reconstructed without distortion. If only subsets of the descriptions are received, the quality of the reconstruction degrades gracefully. Therefore, in MDC, an end user can choose to receive the maximum number of descriptions under its edge bandwidth constraint.

Encodes Streaming Data

The source encodes streaming data into multiple descriptions. The number of descriptions and the coding rate of each description are computed by the source according to the network condition. In our formulation, we set some constraint on the user receiving rate but not user sending rate. Hence, an end user may fetch data from the source or from other users. Our model is applicable to both client/server networks and P2P networks. Our target is to provide the best streaming quality under certain network bandwidth constraint. We formulate the problem and address it by an adaptive solution.

Reference:

Pengye Xia, S.-H. Gary Chan, and Xing Jin, “Optimal Bandwidth Assignment for Multiple-Description-Coded Video”, IEEE Transaction on Multimedia, Vol. 13, No.2, April 2011.

NYMBLE: BLOCKING MISBEHAVING USERS IN ANONYMIZING NETWORKS

Nymble: Blocking Misbehaving Users in

Anonymizing Networks

Abstract:

Anonymizing networks such as Tor allow users to access Internet services privately by using a series of routers to hide the client’s IP address from the server. The success of such networks, however, has been limited by users employing this anonymity for abusive purposes such as defacing popular websites. Website administrators routinely rely on IP-address blocking for disabling access to misbehaving users, but blocking IP addresses is not practical if the abuser routes through an anonymizing network. As a result, administrators block all known exit nodes of anonymizing networks, denying anonymous access to misbehaving and behaving users alike. To address this problem, we present Nymble, a system in which servers can “blacklist” misbehaving users, thereby blocking users without compromising their anonymity. Our system is thus agnostic to different servers’ definitions of misbehavior — servers can blacklist users for whatever reason, and the privacy of blacklisted users is maintained.

Existing System:

Existing users’ credentials must be updated, making it impractical. Verifier-local revocation (VLR) fixes this shortcoming by requiring the server (“verifier”) to perform only local updates during revocation. Unfortunately, VLR requires heavy computation at the server that is linear in the size of the blacklist.

Proposed System:

We present a secure system called Nymble, which provides all the following properties: anonymous authentication, backward unlinkability, subjective blacklisting, fast authentication speeds, rate-limited anonymous connections, revocation auditability (where users can verify whether they have been blacklisted), and also addresses the Sybil attack to make its deployment practical In Nymble, users acquire an ordered collection of nymbles, a special type of pseudonym, to connect to websites. Without additional information, these nymbles are computationally hard to link,and hence using the stream of nymbles simulates anonymous access to services.

Websites, however, can blacklist users by obtaining a seed for a particular nymble, allowing them to link future nymbles from the same user — those used before the complaint remain unlinkable. Servers can therefore blacklist anonymous users without knowledge of their IP addresses while allowing behaving users to connect anonymously. Our system ensures that users are aware of their blacklist status before they present a nymble, and disconnect immediately if they are blacklisted. Although our work applies to anonymizing networks in general, we consider Tor for purposes of exposition. In fact, any number of anonymizing networks can rely on the same Nymble system, blacklisting anonymous users regardless of their anonymizing network(s) of choice

• Blacklisting anonymous users. We provide a means by which servers can blacklist users of an anonymizing network while maintaining their privacy.

• Practical performance. Our protocol makes use of inexpensive symmetric cryptographic operations to significantly outperform the alternatives.

• Open-source implementation. With the goal of contributing a workable system, we have built an opensource implementation of Nymble, which is publicly available. We provide performance statistics to show that our system is indeed practical.

Implemented Modules:

1. NYMBLE MANAGER:

Servers can therefore blacklist anonymous users without knowledge of their IP addresses while allowing behaving users to connect anonymously. Our system ensures that users are aware of their blacklist status before they present a nymble, and disconnect immediately if they are blacklisted. Although our work applies to anonymizing networks in general, we consider Tor for purposes of exposition. In fact, any number of anonymizing networks can rely on the same Nymble system, blacklisting anonymous users regardless of their anonymizing network(s) of choice.

2. PSEUDONYM MANAGER

The user must first contact the Pseudonym Manager (PM) and demonstrate control over a resource; for IP-address blocking, the user must connect to the PM directly (i.e., not through a known anonymizing network), ensuring that the same pseudonym is always issued for the same resource.

3. BLACKLISTING A USER

Users who make use of anonymizing networks expect their connections to be anonymous. If a server obtains a seed for that user, however, it can link that user’s subsequent connections. It is of utmost importance, then,

that users be notified of their blacklist status before they present a nymble ticket to a server. In our system, the user can download the server’s blacklist and verify her status. If blacklisted, the user disconnects immediately.

IP-address blocking employed by Internet services. There are, however, some inherent limitations to using IP addresses as the scarce resource. If a user can obtain multiple addresses she can circumvent both nymble-based and regular IP-address blocking. Subnet-based blocking alleviates this problem, and while it is possible to modify our system to support subnet-based blocking, new privacy challenges emerge; a more thorough description is left for future work.

4. NYMBLE-AUTHENTICATED CONNECTION:

Blacklistability assures that any honest server can indeed block misbehaving users. Specifically, if an honest server complains about a user that misbehaved in the current linkability window, the complaint will be successful and the user will not be able to “nymble-connect,” i.e., establish a Nymble-authenticated connection, to the server successfully in subsequent time periods (following the time of complaint) of that linkability window.

Rate-limiting assures any honest server that no user can successfully nymble-connect to it more than once within any single time period. Non-frameability guarantees that any honest user who is legitimate according to an honest server can nymble-connect to that server. This prevents an attacker from framing a legitimate honest user, e.g., by getting the user blacklisted for someone else’s misbehavior. This property assumes each user has a single unique identity.

When IP addresses are used as the identity, it is possible for a user to “frame” an honest user who later obtains the same IP address. Non-frameability holds true only against attackers with different identities (IP addresses).

A user is legitimate according to a server if she has not been blacklisted by the server, and has not exceeded the rate limit of establishing Nymble-connections. Honest servers must be able to differentiate between legitimate and illegitimate users.

Anonymity protects the anonymity of honest users, regardless of their legitimacy according to the (possibly corrupt) server; the server cannot learn any more information beyond whether the user behind (an attempt to make) a nymble-connection is legitimate or illegitimate

Hardware Requirements:

PROCESSOR : PENTIUM IV 2.6 GHz

RAM : 512 MB DD RAM

MONITOR : 15” COLOR

HARD DISK : 20 GB

FLOPPY DRIVE : 1.44 MB

CDDRIVE : LG 52X

KEYBOARD : STANDARD 102 KEYS

MOUSE : 3 BUTTONS

Software Requirements:

Front End : Java, RMI, JFC (Swing)

Server : apache-tomcat-6.0.18(Web Server)

Backend : Ms-Access

Tools Used : Eclipse 3.3

Operating System: Windows XP/7

MODELING AND DETECTION OF CAMOUFLAGING WORM

MODELING AND DETECTION OF CAMOUFLAGING WORM

ABSTRACT:-

Active worms pose major security threats to the Internet. This is due to the ability of active worms to propagate in an automated fashion as they continuously compromise computers on the Internet. Active worms evolve during their propagation and thus pose great challenges to defend against them. In this paper, we investigate a new class of active worms, referred to as Camouflaging Worm (C-Worm in short). The C-Worm is different from traditional worms because of its ability to intelligently manipulate its scan traffic volume over time. Thereby, the C-Worm camouflages its propagation from existing worm detection systems based on analyzing the propagation traffic generated by worms. We analyze characteristics of the C-Worm and conduct a comprehensive comparison between its traffic and non-worm traffic (background traffic). We observe that these two types of traffic are barely distinguishable in the time domain. However, their distinction is clear in the frequency domain, due to the recurring manipulative nature of the C-Worm. Motivated by our observations, we design a novel spectrum-based scheme to detect the C-Worm. Our scheme uses the Power Spectral Density (PSD) distribution of the scan traffic volume and its corresponding Spectral Flatness Measure (SFM) to distinguish the C-Worm traffic from background traffic. Using a comprehensive set of detection metrics and real-world traces as background traffic, we conduct extensive performance evaluations on our proposed spectrum-based detection scheme. The performance data clearly demonstrates that our scheme can effectively detect the C-Worm propagation. Furthermore, we show the generality of our spectrum-based scheme in effectively detecting not only the C-Worm, but traditional worms as well.

EXISTING SYSTEM:

Existing worm detection schemes will not be able to detect such scan traffic patterns, it is very important to understand such smart-worms and develop new countermeasures to defend against them. Existing detection schemes are based on a tacit assumption that each worm-infected computer keeps scanning the Internet and propagates itself at the highest possible speed. Furthermore, it has been shown that the worm scan traffic volume and the number of worm-infected computers exhibit exponentially increasing patterns. Nevertheless, the attackers are crafting attack strategies that intend to defeat existing worm detection systems. In particular, ‘stealth’ is one attack strategy used by a recently-discovered active worm called “Attack” worm and the “self-stopping” worm circumvent detection by hibernating (i.e., stop propagating) with a pre-determined period. Worm might also use the evasive scan and traffic morphing technique to hide the detection

PROPOSED SYSTEM:

Proposed Worm detection schemes that are based on the global scan traffic monitor by detecting traffic anomalous behavior, there are other worm detection and defense schemes such as sequential hypothesis testing for detecting worm-infected computers, payload-based worm signature detection. . In presented both theoretical modeling and experimental results on a collaborative worm signature generation system that employs distributed fingerprint filtering and aggregation and multiple edge networks... In presented a state-space feedback control model that detects and control the spread of these viruses or worms by measuring the velocity of the number of new connections an infected computer makes. Despite the different approaches described above, we believe that detecting widely scanning anomaly behavior continues to be a useful weapon against worms, and that in practice multifaceted defense has advantages

Modules

1. C-WORM DETECTION MODULE:

Camouflaging Worm (C Worm) the C-Worm has a self-propagating behavior similar to traditional worms, i.e., it intends to rapidly infect as many vulnerable computers as possible. However, the C Worm is quite different from traditional worms in which it camouflages any noticeable trends in the number of infected computers over time. The camouflage is achieved by manipulating the scan traffic volume of worm-infected computers. Such a manipulation of the scan traffic volume prevents exhibition of any exponentially increasing trends or even crossing of thresholds that are tracked by existing detection schemes

2. WORMS ARE MALICIOUS DETECTION MODULE OR ANOMALY DETECTION

Worms are malicious programs that execute on these computers, analyzing the behavior of worm executables plays an important role in host based detection systems. Many detection schemes fall under this category. In contrast, network-based detection systems detect worms primarily by monitoring, collecting, and analyzing the scan traffic (messages to identify vulnerable computers) generated by worm attacks. Many detection schemes fall under this category. Ideally, security vulnerabilities must be prevented to begin with, a problem which must addressed by the programming language community. However, while vulnerabilities exist and pose threats of large-scale damage, it is critical to also focus on network-based detection, as this paper does, to detect wide spreading worms.

3. PURE RANDOM SCAN (PRS) MODULE

C-Worm can be extended to defeat other newly developed detection schemes, such as destination distribution-based detection. In the following, Recall that the attack target distribution based schemes analyze the distribution of attack targets (the scanned destination IP addresses) as basic detection data to capture the fundamental features of worm propagation, i.e., they continuously scan different targets.

4. WORM PROPAGATION MODULE

Worm scan traffic volume in the open-loop control system will expose a much higher probability to show an increasing trend with the progress of worm propagation. As more and more computers get infected, they, in turn, take part in scanning other computers. Hence, we consider the Cworm as a worst case attacking scenario that uses a closed loop control for regulating the propagation speed based on the feedback propagation status.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

PROCESSOR : PENTIUM IV 2.6 GHz

RAM : 512 MB DD RAM

MONITOR : 15” COLOR

HARD DISK : 20 GB

FLOPPY DRIVE : 1.44 MB

CDDRIVE : LG 52X

KEYBOARD : STANDARD 102 KEYS

MOUSE : 3 BUTTONS

SOFTWARE REQUIREMENTS:

Front End : Java, JFC (Swing)

Tools Used : Eclipse 3.3

Operating System: Windows XP/7

Extended XML Tree Pattern Matching: Theories and Algorithms

Extended XML Tree Pattern Matching: Theories and Algorithms

ABSTRACT

As business and enterprises generate and exchange XML data more often, there is an increasing need for efficient processing of queries on XML data. Searching for the occurrences of a tree pattern query in an XML database is a core operation in XML query processing. Prior works demonstrate that holistic twig pattern matching algorithm is an efficient technique to answer an XML tree pattern with parent-child (P-C) and ancestor-descendant (A-D) relationships, as it can effectively control the size of intermediate results during query processing. However, XML query languages (e.g. XPath, XQuery) define more axes and functions such as negation function, order-based axis and wildcards.Here we research a large set of XML tree pattern, called extended XML tree pattern, which may include P-C, A-D relationships, negation functions, wildcards and order restriction. We establish a theoretical framework about “matching cross” which demonstrates the intrinsic reason in the proof of optimality on holistic algorithms. Based on our theorems, we propose a set of novel algorithms to efficiently process three categories of extended XML tree patterns. A set of experimental results on both real-life and synthetic data sets demonstrate the effectiveness and efficiency of our proposed theories and algorithms.

Existing System

Previous algorithms focus on XML tree pattern queries with only P-C and A-D relationships. Little work has been done on XML tree queries which may contain wildcards, negation function and order restriction, all of which are frequently used in XML query languages such as XPath and XQuery. In this article, we call an XML tree pattern with negation function, wildcards and/or order restriction as extended XML tree pattern. Previous XML tree pattern matching algorithms do not fully exploit the “optimality” of holistic algorithms.

Proposed System

We build a theoretical framework on optimal processing of XML tree pattern queries. We show that “matching cross” is the key reason to result in the sub-optimality of holistic algorithms. Intuitively, matching cross describes a dilemma where holistic algorithms have to decide whether to output useless intermediate result or to miss useful results. The fact that TwigStack is optimal for queries with only A-D relationships can be explained that no matching cross can be found for any XML document with respect to queries with A-D edges. We classify matching cross to bound and unbounded matching cross (BMC and UMC). We develop theorems to show that only part of UMC (i.e. UMC with mediator) can force holistic algorithms to potentially output useless intermediate results. Based on the theoretical analysis, we develop a series of holistic algorithms TreeMatch to achieve a large optimal query class for Q/,//,*. Our main technique is to use a concise encoding to present matching results, which leads to the reduction of useless intermediate results. We conducted an extensive set of experiment on synthetic and real data set for performance comparison. We compared TreeMatch with previous four holistic XML tree pattern matching algorithms. The experimental results show that our algorithm can correctly process extended XML tree patterns, achieving performance speedup for tested queries and data sets, even in their restricted focus. The improvement mainly owes to the reduction of the size of intermediate results.

Modules:

1. Optimality of holistic algorithm:

Previous XML tree pattern matching algorithms do not fully exploit the “optimality” of holistic algorithms. TwigStack guarantees that there is no useless intermediate result for queries with only Ancestor-Descendant (A-D) relationships. Therefore, TwigStack is optimal for queries with only A-D edges. Another algorithm TwigStackList enlarges the optimal query class of TwigStack by including Parent-Child(P-C) relationships in non-branching edges. A natural question is whether the optimal query class of TwigStackList can be further improved. Hence, the current open problems include (1) how to identify a larger query class which can be processed optimally and (2) how to efficiently answer a query which cannot be guaranteed to process optimally. This explores the challenges and shows the promise of a novel theoretical framework called “matching cross” to identify a large optimal query class for posing extended XML tree queries.

2. Return nodes in twig pattern queries:

In a practical application, only part of query nodes belong to return nodes (or called output nodes interchangeably). Take the XPath “//A[B]//C” as an example, only C element and its subtree are answers. The current “modus operandi” is that they first find the query answer with the combinations of all query nodes, and then do an appropriate projection on those return nodes. Such a post-processing approach has an obvious disadvantage: it outputs many matching elements of non-return nodes that are unnecessary for the final results. Here, we develop a new encoding method to record the mapping relationships and avoid outputting non-return nodes.

3. Modeling of XML data and extended tree pattern query:

An XML database D is usually modeled as a rooted, node labeled tree, element tags and attributes are mapped to nodes in the trees and the edges are used to represent the direct nesting relationships. Our primary focus is on element nodes; and it is not difficult to extend our methods to process the other types of nodes, including attribute and character data. For convenience, we distinguish between query nodes and database nodes by using the term “node” to refer to a query node and the term “element” to refer to a data element in D. An extended tree query Q describes a complex traversal of the XML document and retrieves relevant tree-structured portions of it. The nodes in Q include element tags, attributes and character data. We use “*” to denote the wildcard, which can match any single tree element. There are four kinds of query edges, which are the four combinations between (positive, negative) and (parent-child, ancestor-descendant).

4. Matching Cross:

“Matching cross” demonstrates the intrinsic reason for the sub-optimality of existing holistic algorithms.The purposes of our study are (i) to provide insight into the characteristics of the holistic algorithms, and thus promotes our understanding about their behaviors; and (ii) to lead to novel algorithms that can guarantee a larger optimal query class and realize better query performance. The existing holistic algorithms consist of two phases: (i) in the first phase, a list of path solutions is output as intermediate path solutions and each solution matches the individual root-to-leaf path expression; and (ii) in the second phase, the path solutions are merged to produce the final answers for the whole twig query. However, for queries with parent-child (P-C) relationships, the state-of-the-art algorithms cannot guarantee that each intermediate solution output in the first phase is useful to merge in the second phase. In other words, many useless intermediate results (i.e. path solutions) may be produced in the first phase, which is called the suboptimality of algorithms.

H/W System Configuration:-

Processor - Pentium –III

Speed - 1.1 Ghz

RAM - 256 MB(min)

Hard Disk - 20 GB

Floppy Drive - 1.44 MB

Key Board - Standard Windows Keyboard

Mouse - Two or Three Button Mouse

Monitor - SVGA

S/W System Configuration:-

v Operating System :Windows95/98/2000/XP

v Application Server : Tomcat5.0/6.X

v Front End : HTML, Java, Jsp

v Scripts : JavaScript.

v Server side Script : Java Server Pages.

v Database : MsAccess

v Database Connectivity : JDBC.

EFFECTIVE NAVIGATION OF QUERY RESULTS BASED ON CONCEPT HIERARCHIES

EFFECTIVE NAVIGATION OF QUERY RESULTS

BASED ON CONCEPT HIERARCHIES

Abstract:

Search queries on biomedical databases, such as PubMed, often return a large number of results, only a small subset of which is relevant to the user. Ranking and categorization, which can also be combined, have been proposed to alleviate this information overload problem. Results categorization for biomedical databases is the focus of this work. A natural way to organize biomedical citations is according to their MeSH annotations. MeSH is a comprehensive concept hierarchy used by PubMed. In this paper, we present the BioNav system, a novel search interface that enables the user to navigate large number of query results by organizing them using the MeSH concept hierarchy. First, the query results are organized into a navigation tree. At each node expansion step, BioNav reveals only a small subset of the concept nodes, selected such that the expected user navigation cost is minimized. In contrast, previous works expand the hierarchy in a predefined static manner, without navigation cost modeling. We show that the problem of selecting the best concepts to reveal at each node expansion is NP-complete and propose an efficient heuristic as well as a feasible optimal algorithm for relatively small trees. We show experimentally that BioNav outperforms state-of-the-art categorization systems with respect to the user navigation cost. We have implemented BioNav for the MEDLINE database at http://db.cse.buffalo.edu/bionav.

Existing System:

Existing search operation Information overload is a major problem when searching

Biomedical databases such as PubMed, where typically a large number of citations are returned, of which only a small subset is relevant to the user.

Proposed System:

The proposals dynamically categorize SQL query results by inferring a hierarchy based on the characteristics of the result tuples. Their domain is the tuple attributes and their problem is how to organize them hierarchically in order to minimize the navigation cost. They also decide the value ranges for each attribute, for both categorical and numerical ones, and how to rank them. One of the systems takes into consideration the user’s preferences during the inference for a more personalized experience. Once the hierarchy is inferred, they follow a static navigation method. BioNav is distinct since it offers dynamic navigation on a predefined hierarchy, as is the MeSH concept hierarchy. Hence, BioNav is complementary to these systems, since it can be used to optimize the navigation, after these systems construct the navigation tree.

HARDWARE REQUIREMENTS:

v Processor - Pentium –IV 2GHz

v RAM - 512 MB (min)

v Hard Disk - 20 GB

v Floppy Drive - 1.44 MB

v Key Board - Standard Windows Keyboard

v Mouse - Two or Three Button Mouse

v Monitor - VGA

SOFTWARE REQUIREMENTS:

v Operating System : Windows XP

v Application Server : Tomcat5.0/6.X

v Front End : J2EE-(HTML, Java, Jsp, Servlet )

v Scripts : JavaScript.

v Development tool : Net beans 6.0.1

v Build tool : Ant

v Server side Script : Java Server Pages.

v Database : MsAccess

v Database Connectivity : JDBC.

Modules:

BIOMEDICAL SEARCH SYSTEMS:

PubMed– using a keyword search interface. Currently, in an exploratory scenario where the user tries to find citations relevant to her line of research and hence not known a priori, she submits an initially broad keyword- based query that typically returns a large number of results. Subsequently, the user iteratively refines the query, if she has an idea of how to, by adding more keywords, and re-submits it, until a relatively small number of results are returned. This refinement process is problematic because after a number of iterations the user is not aware if she has over-specified the query, in which case relevant citations might be excluded from the final query result.

Query on PubMed is using the MeSH static concept hierarchy, thus utilizing the initiative of the US National Library of Medicine (NLM) to build and maintain such a comprehensive structure. Each citation in MEDLINE is associated with several MeSH concepts in two ways: (i) by being explicitly annotated with them, and (ii) by mentioning those in their text. Since these associations are provided by PubMed, a relatively straightforward interface to navigate the query result would first attach the citations to the corresponding MeSH concept nodes and then let the user navigate the navigation tree

DYNAMIC NAVIGATION TREE:

Navigation tree Fig displays a snapshot of such an interface where shown next to each node label is the count of distinct citations in the sub tree rooted at that node. A typical navigation starts by revealing the children of the root ranked by their citation count, and is continued by the user expanding on or more of them, revealing their ranked children and so on, until she clicks on a concept and inspects the citations attached to it. A similar interface and navigation method is used by e-commerce sites, such as Amazon and eBay. For this example, we assume that the user will navigate to the three indicated concepts corresponding to three independent lines of research related to prothymosin.

BioNav introduces a dynamic navigation method that depends on the particular query result at hand and is demonstrated in Fig The query results are attached to the corresponding MeSH concept nodes as in Fig. but then the navigation proceeds differently. The key action on the interface is the expansion of a node that selectively reveals a ranked list of descendant (not necessarily children) concepts, instead of simply showing all its children.

HIERARCHY NAVIGATION WEB (INTERFACE) SEARCH:

BioNav belongs primarily to the categorization class, which is ideal for this domain given the rich concept hierarchies (e.g., MeSH ) available for biomedical data. We augment our categorization techniques with simple ranking techniques. BioNav organizes the query results into a dynamic hierarchy, the navigation tree. Each concept (node) of the hierarchy has a descriptive label. The user then navigates this tree structure, in a top-down fashion, exploring the concepts of interest while ignoring the rest.

QUERY WORKLOAD ONLINE OPERATION:

On-Line Operation Upon receiving a keyword query from the user, BioNav executes the same query against the MEDLINE database and retrieves only the IDs (Pub Med Identifiers) of the citations in the query result. This is done using the ESearch utility of the Entrez Programming Utilities (eUtils) . eUtils are a collection of web interfaces to PubMed for issuing a query and downloading the results with various levels of detail and in a variety of formats. Next, the navigation tree is constructed by retrieving the MeSH concepts associated with each citation in the query result from the BioNav database. This is possible since MeSH concepts have tree identifiers encoding their location in the MeSH hierarchy, which are also retrieved from the BioNav database. This process is done once for each user query.