A routing Ad Hoc network for disaster scenarios

In this work we study the wireless networks without infrastructure especially in emergency situations where groups of rescuers must be on site to accomplish emergency tasks, which is necessary to establish a wireless communication in real time between individuals or groups. The nature of MANET (Mobile Ad Hoc network) makes it suitable to be used in the context of emergencies and that, when the existing infrastructure is down or severely overloaded. In emergency cases Ad Hoc networks can be used to deploy quickly small spontaneous networks. Since nodes are mobile, the network topology may change rapidly and randomly.

The increasing mobility of terminals makes them progressively dependent on their autonomy from the power source; this is illustrated by introducing many mobility models and using many scenario of mobility in emergency situation. Energy efficiency in emergency scenario is the main objective of this paper, achieved by the combination of a low-power mode algorithm and a power-aware routing strategy. A selected set of simulation studies indicate a reduction in energy consumption and a significant increase in node lifetime whereas network performance is not affected significantly. This is the big interest of our works in emergency situation, by increasing life time of nodes individuals can communicate longer and give more chance to rescuers to find them.

Value Is in the Eye of the Beholder: Early Visual Cortex Codes Monetary Value of Objects during a Diverted Attention Task

A central concern in the study of learning and decision-making is the identification of neural signals associated with the values of choice alternatives. An important factor in understanding the neural correlates of value is the representation of the object itself, separate from the act of choosing. Is it the case that the representation of an object within visual areas will change if it is associated with a particular value? We used fMRI adaptation to measure the neural similarity of a set of novel objects before and after participants learned to associate monetary values with the objects. We used a range of both positive and negative values to allow us to distinguish effects of behavioral salience (i.e., large vs. small values) from effects of valence (i.e., positive vs. negative values).

During the scanning session, participants made a perceptual judgment unrelated to value. Crucially, the similarity of the visual features of any pair of objects did not predict the similarity of their value, so we could distinguish adaptation effects due to each dimension of similarity. Within early visual areas, we found that value similarity modulated the neural response to the objects after training. These results show that an abstract dimension, in this case, monetary value, modulates neural response to an object in visual areas of the brain even when attention is diverted.

Energy-efficient privacy homomorphic encryption scheme for multi-sensor data in WSNs

The recent advancements in wireless sensor hardware ensures sensing multiple sensor data such as temperature, pressure, humidity, etc. using a single hardware unit, thus defining it as multi-sensor data communication in wireless sensor networks (WSNs). The in-processing technique of data aggregation is crucial in energy-efficient WSNs; however, with the requirement of end-to-end data confidentiality it may prove to be a challenge. End-to-end data confidentiality along with data aggregation is possible with the implementation of a special type of encryption scheme called privacy homomorphic (PH) encryption schemes. This paper proposes an optimized PH encryption scheme for WSN integrated networks handling multi-sensor data. The proposed scheme ensures light-weight payloads, significant energy and bandwidth consumption along with lower latencies.

The performance analysis of the proposed scheme is presented in this paper with respect to the existing scheme. The working principle of the multi-sensor data framework is also presented in this paper along with the appropriate packet structures and process. It can be concluded that the scheme proves to decrease the payload size by 56.86% and spend an average energy of 8-18 mJ at the aggregator node for sensor nodes varying from 10-50 thereby ensuring scalability of the WSN unlike the existing scheme.

Enhancing Optical-CDMA Confidentiality With Multicode-Keying Encryption

Optical codes with large cardinality and tree structures of multiple subsets of codewords for adjustable code performance and cardinality have recently been proposed. As studied in this paper, these characteristics support multicode-keying encryption for enhancing physical-layer confidentiality in optical code-division multiple-access systems and networks.

The concept of the multicode-keying encryption technique is introduced. The associated all-optical hardware is designed and validated with OptiSystem™ simulation. The theoretical analyses of confidentiality improvement by means of rapid codeword switching and multicode-keying encryption are formulated.

Dynamic chaining of Virtual Network Functions in cloud-based edge networks

This manuscript investigates the issue of implementing chains of network functions in a “softwarized” environment where edge network middle-boxes are replaced by software appliances running in virtual machines within a data center. The primary goal is to show that this approach allows space and time diversity in service chaining, with a higher degree of dynamism and flexibility with respect to conventional hardware-based architectures.

The manuscript describes implementation alternatives of the virtual function chaining in a SDN scenario, showing that both layer 2 and layer 3 approaches are functionally viable. A proof-of-concept implementation with the Mininet emulation platform is then presented to provide a practical example of the feasibility and degree of complexity of such approaches.

Secure communication scheme for wireless sensor networks to maintain anonymity

In wireless sensor networks it is becoming more and more important for sensor nodes to maintain anonymity while communicating data because of security reasons. Anonymous communication among sensor nodes is important, because sensor nodes want to conceal their identities either being a base station or being a source node. Anonymous communication in wireless sensor networks includes numerous important aspects, for instance base station anonymity, communication association anonymity, and source node anonymity. From the literature, we can observe that existing anonymity schemes for wireless sensor networks either cannot realize the complete anonymities, or they are suffering from various overheads such as enormous memory usage, complex computation, and longcommunications.

This paper is presenting an efficient secure anonymity communication protocol (SACP) for wireless sensor networks that can realize complete anonymities offering minimal overheads with respect to storage, computation and communication costs. The given secure anonymitycommunication protocol is compared with various existing anonymity protocols, and the performance analysis shows that our protocol accomplishes all three anonymities: sender node anonymity, base station anonymity, and communication association anonymity while using little memory, lowcommunication cost, and small computation costs.

A smart communication architecture for ambient assisted living

Intelligent systems and communication technologies have experienced huge advances in the last few years. AAL can benefit from mixing both research fields. This article presents an intelligentcommunication architecture for AAL. It uses artificial intelligence to process the information gathered from several types of communication (e.g., wireless sensor networks, wireless ad hoc networks, wireless mesh networks) over any type of communication technologies (e.g., device-to-device, machine-to-machine, sensor-actuator), know what is happening in the network, and detect if elderly people need assistance.

The article shows the main intelligent algorithms included in the AAL system and the developed software application. Several real measurements validate the operation of our proposal.

Performance Evaluation of a VANET Simulation System Using NS-3 and SUMO

In this paper, we investigate the performance of HWMP, OLSR and DD protocols in a VANET crossroad scenario. The mobility patterns of vehicles are generated by means of SUMO (Simulation of Urban Mobility) and as communication protocol simulator is used NS3 (Network Simulator 3). For the simulations, we used IEEE 802.11p standard, Two Ray Ground Propagation Loss Model and sent multiple CBR flows over UDP between 20 source-destination pairs.

We use Packet Delivery Ratio (PDR), throughput and delay as evaluation metrics. We compared the performance of three protocols and the simulation results shows that the DD protocol has better PDR and throughput compared with HWMP and OLSR protocol. However, the DD protocol has a long delay because is a delay tolerant protocol.

Mining VRSEC student learning behaviour in moodle system using datamining techniques

Predicting the performance of the students and helping them to improve their knowledge in subjects is one of the jobs of the educational universities. It is a laborious work to track many students in the universities. So, the universities started using content management systems to track the record of the student’s marks, grades and performance. Even then, the tutor have to evaluate manually to finalize the list of low grade students. As this is a problematic method, in this paper, the best method is explained for this purpose. There are many e-learning systems helping the institutions to evaluate their student’s skills. In this paper, the comparison for those existing ones are made and the better one is selected i.e., Moodle. Being an open source software, providing the users flexibility in updating the tasks and excelling in its security it is opted to store VRSEC student’s performance records.

The further step is to analyze the students’ performance and predict the grades. For this, Rapid miner an open source tool is used. Primarily the records of the VRSEC students are stored in the Moodle and are then extracted into Rapid miner environment. Certain parameters are defined to complete the pre-processing concept. Then classification algorithm is applied to predict the grades of the students. By applying various classification algorithms, it is observed that decision tree algorithm gave greatest accuracy of 85% and with weighted mean of recall and precision as 75.00% and 89.63% respectively.

Medical Data Compression and Transmission in Wireless Ad Hoc Networks

A wireless ad hoc network (WANET) is a type of wireless network aimed to be deployed in a disaster area in order to collect data of patients and improve medical facilities. The WANETs are composed of several small nodes scattered in the disaster area. The nodes are capable of sending (wirelessly) the collected medical data to the base stations. The limited battery power of nodes and the transmission of huge medical data require an energy efficient approach to preserve the quality of service of WANETs. To address this issue, we propose an optimization-based medical data compression technique, which is robust to transmission errors.

We propose a fuzzy-logic-based route selection technique to deliver the compressed data that maximizes the lifetime of WANETs. The technique is fully distributed and does not use any geographical/location information. We demonstrate the utility of the proposed work with simulation results. The results show that the proposed work effectively maintains connectivity of WANETs and prolongs network lifetime.