N.Ch.S.N. Iyengar

LSCrawler: A Framework for an Enhanced Focused Web Crawler Based on Link Semantics

The traditional process of focused Web crawler is to harvest a collection of Web documents that are focused on the topical subspaces. The intricacy of focused crawlers is identifying the next most important and relevant link to follow. Focused crawlers mostly rely on probabilistic models for predicting the relevancy of the documents. The Web documents are well characterized by the hypertext and the hypertext can be used to determine the relevance of the document to the search domain. The semantics of the link characterizes the semantics of the document referred. In this article, a novel, and distinctive focused crawler named LSCrawler has been proposed. This LSCrawler system retrieves documents by speculating the relevancy of the document based on the keywords in the link and the surrounding text of the link. The relevancy of the documents is reckoned measuring the semantic similarity between the keywords in the link and the taxonomy hierarchy of the specific domain. The system exhibits better recall as it exploits the semantic of the keywords in the link

Optimal channel allocation algorithm with efficient channel reservation for cellular networks

Today, there is a rapid growth of mobile users. As the available frequency spectrum is limited, it must be efficiently utilised. This paper proposes a dynamic channel allocation scheme with efficient channel reservation for handoff calls. The proposed algorithm deals with both originating calls and handoff calls. In the proposed algorithm, we reserve some channels for handoff calls. Later, it increments or decrements, the reserved channels dynamically based on the traffic. Quality of Service (QoS) may be improved further by reserving the channels for handoff calls based on the user mobility and type of cell. The reservation factor, which varies the number of reserved channels, is based on both the blocking probability and the dropping probability. The results indicate clearly that the proposed channel allocation scheme exhibits better performance by considering the above said user mobility and type of cells. Also, it reduces the call dropping rate than the existing channel allocation schemes.

Sequencing technique: an enhancement to 802.11 medium access control to improve the performance of wireless networks

This paper presents a technique known as sequencing on MAC layer for wireless networks. MAC layer issues are very important while accessing channel over wireless networks. Normally, communication uses Request To Send/Clear To Send (RTS/CTS) mechanism to access channel for transmission of data. Mostly, it is observed that RTS/CTS handshake may introduce some delay especially in case of wireless networks. Hence, a sequencing method is proposed where selected RTS packets are dropped based on a node sequence number to improve overall throughput of the network although individual performance of the transmission is reduced.

An efficient Hash Table-Based Node Identification Method for bandwidth reservation in hybrid cellular and ad-hoc networks

Hybrid cellular and wireless ad-hoc network architectures are currently considered to be promising alternative solutions to the standalone cellular or ad-hoc network architectures. In this paper, we propose an efficient Hash Table-Based Node Identification (HTNI) Method using which bandwidth for various flows can be reserved in such network environments. Bandwidth reservation depends on the type of the traffic and its priorities. We define a bandwidth reservation factor for use in such hybrid network environments. We propose a cross-layer-based architecture for bandwidth reservation to maintain Quality-of-Service (QoS). We use a priority re-allocation method for flows which starve for long time. The proposed method is useful for finding the position of nodes with low communication cost.

An intelligent knowledge mining model for kidney cancer using rough set theory

Medical diagnosis processes vary in the degree to which they attempt to deal with different complicating aspects of diagnosis such as relative importance of symptoms, varied symptom pattern and the relation between diseases themselves. Rough set approach has two major advantages over the other methods. First, it can handle different types of data such as categorical, numerical etc. Secondly, it does not make any assumption like probability distribution function in stochastic modeling or membership grade function in fuzzy set theory. It involves pattern recognition through logical computational rules rather than approximating them through smooth mathematical functional forms. In this paper we use rough set theory as a data mining tool to derive useful patterns and rules for kidney cancer faulty diagnosis. In particular, the historical data of twenty five research hospitals and medical college is used for validation and the results show the practical viability of the proposed approach.

A Small e-Health Care Information System with Agent Technology

Nowadays, health care is one of the most important subjects in our life. Increasing level of patients demand across the world obliges health care services in a more flexible and uniform manner. So that patients can get useful health services in the home environment without going to the health center personally. The e-healthcare is new kinds of health care system and it is very popular at this time. Where patients can exchange their confidential information via internet to the organization and from the organization get the services via internet also. So lots of time will be saved and patient can get services efficiently without unnecessary harassments of travel to the organization. In this system all the transaction of data are processed by Patient Agents (PA), Doctor Agents (DA) and Controller Agent (CA). The user uses the Patient Agent (PA) to connect with the controlling server of the e-health care system. The Controller Agent (CA) is control the demand of the patients as well as activity of the doctors. When the doctor wants to check-up the patient then he/she connects with the Doctor Agent (DA). Using the Doctor Agent (DA), every doctor prescribed some medicine to the patient about the query and if required then refer the patient to another doctor. The Agent computing in a network of workstations is powerful paradigm for building distributed applications. The agent technology is used to enhance the patients needs which include availability, speedy response time, and efficiency. Agent for e-Health care creates connectivity on an anytime-anywhere-any-device-basis to provide the specific service from the doctor required by the patients.

Detection of distributed denial of service attacks in cloud computing by identifying spoofed IP

Cloud computing is a booming field which will be predominating the IT industries soon. Cloud computing is a virtual dynamic version of the present day internet resource access which is static. Cloud computing provides high availability of various large-scale geographically distributed resources for users ranging from small to large-scale on demand. The two key advantages of this model are ease of use and cost effectiveness, i.e., cost as per the usage and maximum resource utilisation. The main issue identified in cloud computing is security. In the specific case of cloud computing systems, the impact of a flooding attack is expected to be amplified drastically as and when the cloud computing operating system notices the high workload on the flooded service, it will start to provide more computational power to cope with the additional workload. The attacker can flood a single, cloud-based address in order to perform a full loss of availability on the intended service. In this paper, the proposed spoofing detection algorithm to detect DDos attacks launched against a server inside a cloud.

Algebraic Properties of Rough Set on Two Universal Sets based on Multigranulation

The rough set philosophy is based on the concept that there is some information associated with each object of the universe. The set of all objects of the universe under consideration for particular discussion is considered as a universal set. So, there is a need to classify objects of the universe based on the indiscernibility relation (equivalence relation) among them. In the view of granular computing, rough set model is researched by single granulation. The granulation in general is carried out based on the equivalence relation defined over a universal set. It has been extended to multi-granular rough set model in which the set approximations are defined by using multiple equivalence relations on the universe simultaneously. But, in many real life scenarios, an information system establishes the relation with different universes. This gave the extension of multi-granulation rough set on single universal set to multi-granulation rough set on two universal sets. In this paper, we define multi-granulation rough set for two universal sets U and V. We study the algebraic properties that are interesting in the theory of multi-granular rough sets. This helps in describing and solving real life problems more accurately.

Escape-on-Sight: An Efficient and Scalable Mechanism for Escaping DDoS Attacks in Cloud Computing Environment

Abstract Availability is one of the primary security issues in Cloud computing environment. The existing solutions that address the availability related issues can be applied in cloud computing environment, but because of their unique characteristics, such as on-demand self service, rapid elasticity, etc., there is a need to develop a detection mechanism that must satisfy the characteristics and an optimal profit for the Cloud Service Provider (CSP). A solution named Escape-on- Sight (EoS) algorithm is proposed in this paper that helps in detecting the attacker’s characteristics by analyzing traffic conditions stage by stage and protects the Data Center (DC) from malicious traffic. The profit analysis shows that the proposed approach has a reasonable chance of deploying EoS mechanism at DCs that are prone to DDoS attacks.

Trilateral Trust Based Defense Mechanism against DDoS Attacks in Cloud Computing Environment

Abstract Distributed Denial of Service (DDoS) in a Cloud leads to a high rate of overload conditions, which subverts the Data Center (DC) performance and ends up in resource unavailability. This work proposes a “Trilateral Trust mechanism” which helps in detecting different kinds of attack groups at different points of time. It is the direct trust based defense mechanism for segregating legitimate and attack groups from the vast number of incoming requestors. It is a hybrid mechanism of trusts that follows the zero trust approach initially and eventually supports both Mutual trust and Momentary trust. This combinatorial trust mechanism helps in detecting almost all kinds of overload conditions at a cautionary period. Detecting the high rate of an attack at an earlier moment of time could reduce the traffic impact towards DC. The simulation results and profit analysis proved that the mechanism proposed is deployable at an attack-prone DC for resource protection, which would eventually benefit the DC economically as well.