A New Scheme for Minimizing Malicious Behavior of Mobile Nodes in Mobile Ad Hoc Networks

The performance of Mobile Ad hoc networks (MANET) depends on the cooperation of all active nodes. However, supporting a MANET is a cost-intensive activity for a mobile node. From a single mobile node perspective, the detection of routes as well as forwarding packets consume local CPU time, memory, network-bandwidth, and last but not least energy. We believe that this is one of the main factors that strongly motivate a mobile node to deny packet forwarding for others, while at the same time use their services to deliver its own data. This behavior of an independent mobile node is commonly known as misbehaving or selfishness. A vast amount of research has already been done for minimizing malicious behavior of mobile nodes. However, most of them focused on the methods/techniques/algorithms to remove such nodes from the MANET. We believe that the frequent elimination of such miss-behaving nodes never allowed a free and faster growth of MANET. This paper provides a critical analysis of the recent research wok and its impact on the overall performance of a MANET. In this paper, we clarify some of the misconceptions in the understating of selfishness and miss-behavior of nodes. Moreover, we propose a mathematical model that based on the time division technique to minimize the malicious behavior of mobile nodes by avoiding unnecessary elimination of bad nodes. Our proposed approach not only improves the resource sharing but also creates a consistent trust and cooperation (CTC) environment among the mobile nodes. The simulation results demonstrate the success of the proposed approach that significantly minimizes the malicious nodes and consequently maximizes the overall throughput of MANET than other well known schemes.Comment: 10 pages IEEE format, International Journal of Computer Science and Information Security, IJCSIS July 2009, ISSN 1947 5500, Impact Factor 0.42

Optimization and Job Scheduling in Heterogeneous Networks

The final publication is available at www.springerlink.comA heterogeneous network is a connected network of different platforms and operating systems. Job scheduling is a problem of selecting a free resource for unexecuted task from a pool of submitted tasks. Furthermore, it is required to find for every resource the best order of the tasks assigned to it. The purpose of this paper is to develop an efficient algorithm for job scheduling in heterogeneous networks. The algorithm should include parameters such as properties of resources and properties of jobs. The algorithm includes a cost function that is required to be optimized which includes parameters such as the total processing time, average waiting time. Our results demonstrate that the proposed algoritghm can be efficiently used to determine the performance of different job scheduling algorithms under different sets of loads.http://link.springer.com/chapter/10.1007%2F978-90-481-3662-9_4

Investigating the Effects of Trees and Butterfly Barriers on the Performance of Optimistic GVT Algorithm

The final publication is available at www.springerlink.comThere is two approaches for handling timing constraints in a heterogeneous network; conservatives and optimistic algorithms. In optimistic algorithms, time constraints are allowed to be violated with the help of a time wrap algorithm. Global Virtue Time (GVT) is a necessary mechanism for implementing time wrap algorithm. Mattern [2] has introduced an algorithm for GVT based computation using a ring structure. which showed high latency. The performance of this optimistic algorithm is optimal since it gives accurate GVT approximation. However, this accurate GVT approximation comes at the expense of high GVT latency. Since this resultant GVT latency is not only high but may vary, the multiple processors involve in communication remain idle during that period of time. Consequently, the overall throughput of a parallel and distributed simulation system degrades significantly In this paper, we discuss the potential use of trees and (or) butterflies structures instead of the ring structure. We present our analysis to show the effect of these new mechanisms on the latency of the system.http://link.springer.com/chapter/10.1007%2F978-90-481-3660-5_7

Discovery of Malicious Attacks to Improve Mobile Collaborative Learning (MCL)

Mobile collaborative learning (MCL) is highly acknowledged and focusing paradigm in eductional institutions and several organizations across the world. It exhibits intellectual synergy of various combined minds to handle the problem and stimulate the social activity of mutual understanding. To improve and foster the baseline of MCL, several supporting architectures, frameworks including number of the mobile applications have been introduced. Limited research was reported that particularly focuses to enhance the security of those pardigms and provide secure MCL to users. The paper handles the issue of rogue DHCP server that affects and disrupts the network resources during the MCL. The rogue DHCP is unauthorized server that releases the incorrect IP address to users and sniffs the traffic illegally. The contribution specially provides the privacy to users and enhances the security aspects of mobile supported collaborative framework (MSCF). The paper introduces multi-frame signature-cum anomaly-based intrusion detection systems (MSAIDS) supported with novel algorithms through addition of new rules in IDS and mathematcal model. The major target of contribution is to detect the malicious attacks and blocks the illegal activities of rogue DHCP server. This innovative security mechanism reinforces the confidence of users, protects network from illicit intervention and restore the privacy of users. Finally, the paper validates the idea through simulation and compares the findings with other existing techniques.Comment: 20 pages and 11 figures; International Journal of Computer Networks and Communications (IJCNC) July 2012, Volume 4. Number

Artificial Neural Fuzzy Inference in Task-Based Learning Support System for Distance Education

Distance education learning systems have become one of the major investigation areas nowadays because the various categories of graduate learning are studied exclusively through the distance learning system. It provides the desired knowledge in various applications under the same domain or category in a well-organized manner. But the distance education learning system also has some major issues. In order to solve the problem of the distance education learning system, in this paper we present a novel sentiment analysis-based learning algorithm to learn the result of each learner in earlier classes and the level of each learner. The proposed sentiments analysis-based Fuzzy Neural Network learning methods analyze the results of previous classes’ positive and negative comments specified by the learner and the task result of the learner. Initially, to convey the message or information about the individual learner, the system is connected to the videoconferencing, and then the camera is connected to avoid delay problems during the conversation. To increase the teacher closeness and social occurrence, it proposes a learning method to review the comments of the previous classes and perform some of the tasks, such as taking tests on 10 min from previous classes and make a review on that the task based on the sentiment analysis mining methods to develop the learning participation, training efficiency, and value of communication in the distance education learning system. After the learning results are found from each one of the students in the class, they are sent to the teacher. The instructors and learners are exactly identified based on the face and speech recognition performed using the automation recognition system

Detecting Bad Posture using Postuino among Engineering Graduate Students

Poster also presented at the Northeast Section American Society for Engineering Education 2015 at Northeastern University in Boston, MA on 2015-04-30.To understand how good posture minimizes computer related injury’s pain, we developed Postuino. A device that warns the computer users if they are leaning too close towards computer screen. Postuino has an accompanying web application that visualizes the collected data and displays a chart to simplify comparing be-tween straight time and slouch time. Also, the app suggests taking frequent breaks to minimize the risk of injuries and to increase productivity. Then, we designed an experiment with different factors to evaluate the efficiency of Postuino. In our study, 24 subjects first use the computer for 3 hours after disabling Postuino’s alert system. Afterwards, they use the computer again for another 3 hours after enabling the alert system. We collected data, analyzed it, and presented the results in this paper

Femto Cells: Current Status and Future Directions

This is a survey paper on the recently developed and rapidly evolving field of femtocells. Quite often, it is noticed that cell-phone signals are strongly attenuated, when indoors, leading to call dropping or poor call quality. Femtocells are mini base stations that are deployed in users’ homes so that the user can directly connect to the cellular network through the femtocell instead of the outdoor macrocell, thereby increasing call quality. In the later stages of the paper, we also discuss the integration of the femtocell into the 3G architecture, as well as the various interference issues that the femtocell faces