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A Signaling System for Quality of Service (QoS)-Aware Content Distribution in Peer-to-Peer Overlay Networks

Sasikumar Kandasamy1, Sivanandam Natarajan2, and Ayyasamy Sellappan3

1Department of Computer Science and Engineering, Tamilnadu College of Engineering, India.

2Department of Computer Science and Engineering, Karpagam College of Engineering, India.

3Department of Information Technology, Tamilnadu College of Engineering, India.

Abstract:  Peers are used to limit and expand the available facilities for different kind of devices, which should able to fetch the data according to the demand of users and available resources. Several factors such as latency, bandwidth, memory size, CPU speed, and reliability can affect the Quality of Service (QoS) of the peer-to-peer network. In this paper, we propose a signaling system for QoS-aware content distribution for Peer-to-Peer overlay networks where the signaling system is controlled through a set of data so that it can be operated dynamically. The flow of signal in the system enhances other devices to choose their own way with the requirement of applications. This system is able to reduce the traffic and utilize the available resources.

Keywords: signaling, bandwidth, delay, transmission, buffer, catch

Received October 3, 2013; accepted July 6, 2014

 

 

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Comparison of Dimension Reduction Techniques on

High Dimensional Datasets

Kazim Yildiz1, Ali Yilmaz Camurcu2, and Buket Dogan1

1Deparment of Computer Engineering, Marmara Unıversity, Turkey

2Department of Computer Engineering, Fatih Sultan Mehmet Waqf University, Turkey

Abstract: High dimensional data becomes very common with the rapid growth of data that has been stored in databases or other information areas. Thus clustering process became an urgent problem. The well-known clustering algorithms are not adequate for the high dimensional space because of the problem that is called curse of dimensionality. So dimensionality reduction techniques have been used for accurate clustering results and improve the clustering time in high dimensional space. In this work different dimensionality reduction techniques were combined with Fuzzy C-Means clustering algorithm. It is aimed to reduce the complexity of high dimensional datasets and to generate more accurate clustering results. The results were compared in terms of cluster purity, cluster entropy and mutual info. Dimension reduction techniques are compared with current Central Processing Unit (CPU), current memory and elapsed CPU time. The experiments showed that the proposed work produces promising results on high dimensional space.

Keywords: High Dimensional Data, Clustering, Dimensionality Reduction, Data Mining

Received October 23, 2014; accepted December 21, 2015

 

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Fuzzy Logic Based Decision Support System for Component Security Evaluation

Shah Nazir1, Sara Shahzad1, Saeed Mahfooz1, and Muhammad Nazir2

1Department of Computer Science, University of Peshawar, Pakistan

2Institute of Business and Management Sciences, The University of Agriculture, Pakistan

Abstract: Software components are imperative parts of a system which play a fundamental role in the overall function of a system. A component is said to be secure if it has a towering scope of security.  Security is a shield for unauthorized use as unauthorized users may informally access and modify components within a system. Such accessing and modifications ultimately affect the functionality and efficiency of a system. With an increase in software development activities security of software components is becoming an important issue. In this study, a fuzzy logic based model is presented to handle ISO/IEC 18028-2 security attributes for component security evaluation. For this purpose an eight input, single output model based on the Mamdani fuzzy inference system has been proposed. This component security evaluation model helps software engineers during component selection in conditions of uncertainty and ambiguity.

Keywords: Software Component, Component Security, Fuzzy Logic

Received May 1, 2015; accepted November 29, 2015

 

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Immunity inspired Cooperative Agent based

Security System

Praneet Saurabh and Bhupendra Verma

Department of Computer Science and Engineering, Technocrats Institute of Technology, India

Abstract: Artificial Immune System (AIS) has evolved substantially from its inception and is utilized to solve complex problems in different domains out of which computer security is one of them. Computer Security has emerged as a key research area because of the ever-growing attacks and its methodology. Various security concepts and products were developed to overcome this alarming situation but these systems by some means fall short to provide the desired protection against new and ever-increasing threats.  AIS enthused from Human Immune System (HIS) is considered as an excellent source of inspiration to develop computer security solution since the previous protect the body from various external and internal threats very effectively. This paper presents Immunity inspired Cooperative Agent based Security System (IICASS) that uses Enhanced Negative Selection Algorithm (E-RNS) which incorporate fine tuning of detectors and detector power in negative selection algorithm. These features make IICASS evolve and facilitate better and correct coverage of self or non-self. Collaboration and communication between different agents make the system dynamic and adaptive that helps it to discover correct anomalies with degree of severity. Experimental results demonstrate that IICASS show remarkable resilience in detecting novel unseen attacks with lower false positive.

Keywords: Anomaly, Human Immune System, Artificial Immune System, Agent

Received June 3, 2014; accepted May 24, 2016

 

 

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Idle Time Estimation for Bandwidth-Efficient Synchronization in Replicated Distributed File System

Fidan Kaya Gülağız, Süleyman Eken, Adnan Kavak, and Ahmet Sayar

Department of Computer Engineering, Kocaeli University, Turkey

Abstract: Synchronization is a promising approach to solve the consistency problems in replicated distributed file systems. The synchronization can be repeated periodically, with fixed time interval or a time interval which can be adjusted adaptively. In this paper, we propose a policy-based performance efficient distributed file synchronization approach, in which synchronization processes occur in varying time intervals and adjusted adaptively. The study is based on tracing network idle times by means of measuring and clustering Round Trip Time (RTT) values. K-means clustering is used to cluster RTT values as idle, normal, and busy. To estimate the most suitable synchronization time intervals, the measured RTT values are included into these classes with an algorithm similar to TCP Additive-Increase / Multiplicative-Decrease (AIMD) feedback control. The efficiency and feasibility of the proposed technique is examined on a distributed file synchronization application within the scope of Fatih project, which is one of the most important educational projects in Turkey.

Keywords: Idle time detection algorithm, cloud traffic, round trip time, K-means clustering, distributed file synchronization, policy-based synchronization.

Received October 4, 2015; accepted January 3, 2016

 

 

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