Optimized Ensemble Classifier Based Network Intrusion Detection System for RPL Based Internet of Things

With the increase in user demand for internet access on move, spectrum resource seems to deplete and leads to spectrum crunch. Recent researches reports that this spectrum crunch is not due to spectrum scarcity but due to spectrum underutilization because of legacy static spectrum allocation of spectrum bands. This spectrum utilization and efficiency can be improved by using Dynamic Spectrum Access (DSA) techniques, which correlate with cognitive radio technology in one way or the other. There are three basic approach of communication for cognitive radio technology: Inter-weaved approach, Underlay approach and Overlay approach. Extensive researches has been proposed so far based on the inter-weaved approach and little or negligible using underlay or overlay approach. Using these modes the cognitive users can coexist with the primary users at same geographic time and location. In this paper simple and unique Adaptive Power Control (APC) technique for underlay approach for cognitive radio mobile network is proposed. This techniques introduces a Power Adaptive Transmission (PAT) metric which overcomes three major issues. Firstly, this proposed techniques work efficiently over highly active licensed networks with marginal increased throughput of 0.2 Mbps. Secondly, APC this technique adapts to the requirement of cognitive user and Lastly, primary user power is monitored, to prevent interference and maintain the Quality of Service (QoS) of primary user. Under simulation testing the proposed APC technique outperforms various other underlay as well hybrid techniques for power control under cognitive radio environment with 11% increase in throughput and 32% decrease in delay using APC.

     

Correction to: An Enhanced Crow Search Inspired Feature Selection Technique for Intrusion Detection Based Wireless Network System

Wireless Personal Communications -     

Asynchronous parallel simulation of parallel programs

Parallel simulation of parallel programs for large datasets has been shown to offer significant reduction in the execution time of many discrete event models. The paper describes the design and implementation of MPI-SIM, a library for the execution driven parallel simulation of task and data parallel programs. MPI-SIM can be used to predict the performance of existing programs written using MPI for message passing, or written in UC, a data parallel language, compiled to use message passing. The simulation models can be executed sequentially or in parallel. Parallel execution of the models are synchronized using a set of asynchronous conservative protocols. The paper demonstrates how protocol performance is improved by the use of application-level, runtime analysis. The analysis targets the communication patterns of the application. We show the application-level analysis for message passing and data parallel languages. We present the validation and performance results for the simulator for a set of applications that include the NAS Parallel Benchmark suite. The application-level optimization described in the paper yielded significant performance improvements in the simulation of parallel programs, and in some cases completely eliminated the synchronizations in the parallel execution of the simulation model     

Secure Data Sharing with Confidentiality,Integrity and Access Control in Cloud Environment

Cloud storage is an incipient technology in today’s world. Lack of security in cloud environment is one of the primary challenges faced these days. This scenario poses new security issues and it forms the crux of the current work. The current study proposes Secure Interactional Proof System (SIPS) to address this challenge. This methodology has a few key essential components listed herewith to strengthen the security such as authentication, confidentiality, access control, integrity and the group of components such as AVK Scheme (Access List, Verifier and Key Generator). It is challenging for every user to prove their identity to the verifier who maintains the access list. Verification is conducted by following Gulliou-Quisquater protocol which determines the security level of the user in multi-step authentication process. Here, RSA algorithm performs the key generation process while the proposed methodology provides data integrity as well as confidentiality using asymmetric encryption. Various methodological operations such as time consumption have been used as performance evaluators in the proposed SIPS protocol. The proposed solution provides a secure system for firm data sharing in cloud environment with confidentiality, authentication and access control. Stochastic Timed Petri (STPN) Net evaluation tool was used to verify and prove the formal analysis of SIPS methodology. This evidence established the effectiveness of the proposed methodology in secure data sharing in cloud environment.     

DABPR: a large-scale internet of things-based data aggregation back pressure routing for disaster management

In this paper, we propose a data aggregation back pressure routing (DABPR) scheme, which aims to simultaneously aggregate overlapping routes for efficient data transmission and prolong the lifetime of the network. The DABPR routing algorithm is structured into five phases in which event data is sent from the event areas to the sink nodes. These include cluster-head selection, maximization of event detection reliability, data aggregation, scheduling, and route selection with multi attributes decision making metrics phases. The scheme performs data aggregation on redundant data at relay nodes in order to decrease both the size and rate of message exchanges to minimize communication overhead and energy consumption. The proposed scheme is assessed in terms of packet delivery, network lifetime, ratio, energy consumption, and throughput, and compared with two other well-known protocols, namely “information-fusion-based role assignment (InFRA)” and “data routing for in-network aggregation (DRINA)”, which intrinsically are cluster and tree-based routing schemes designed to improve data aggregation efficiency by maximizing the overlapping routes. Meticulous analysis of the simulated data showed that DABPR achieved overall superior proficiency and more reliable performance in all the evaluated performance metrics, above the others. The proposed DABPR routing scheme outperformed its counterparts in the average energy consumption metric by 64.78% and 51.41%, packet delivery ratio by 28.76% and 16.89% and network lifetime by 42.72% and 20.76% compared with InFRA and DRINA, respectively.

     

Nanoengineered Light‐Activatable Polybubbles for On‐Demand Therapeutic Delivery

Vaccine coverage is severely limited in developing countries due to inefficient protection of vaccine functionality as well as lack of patient compliance to receive the additional booster doses. Thus, there is an urgent need to design a thermostable vaccine delivery platform that also enables release of the bolus after predetermined time. Here, the formation of injectable and light‐activatable polybubbles for vaccine delivery is reported. In vitro studies show that polybubbles enable delayed burst release, irrespective of cargo types, namely small molecule and antigen. The extracorporeal activation of polybubbles is achieved by incorporating near‐infrared (NIR)‐sensitive gold nanorods (AuNRs). Interestingly, light‐activatable polybubbles can be used for on‐demand burst release of cargo. In vitro, ex vivo, and in vivo studies demonstrate successful activation of AuNR‐loaded polybubbles. Overall, the light‐activatable polybubble technology can be used for on‐demand delivery of various therapeutics including small molecule drugs, immunologically relevant protein, peptide antigens, and nucleic acids.     

Design of tensegrity structures using parametric analysis and stochastic search

Tensegrity structures are lightweight structures composed of cables in tension and struts in compression. Since tensegrity systems exhibit geometrically nonlinear behavior, finding optimal structural designs is difficult. This paper focuses on the use of stochastic search for the design of tensegrity systems. A pedestrian bridge made of square hollow-rope tensegrity ring modules is studied. Two design methods are compared in this paper. Both methods aim to find the minimal cost solution. The first method approximates current practice in design offices. More specifically, parametric analysis that is similar to a gradient-based optimization is used to identify good designs. Parametric studies are executed for each system parameter in order to identify its influence on response. The second method uses a stochastic search strategy called probabilistic global search Lausanne. Both methods provide feasible configurations that meet civil engineering criteria of safety and serviceability. Parametric studies also help in defining search parameters such as appropriate penalty costs to enforce constraints while optimizing using stochastic search. Traditional design methods are useful to gain an understanding of structural behavior. However, due to the many local minima in the solution space, stochastic search strategies find better solutions than parametric studies.     

A comparison of simultaneous state and parameter estimation schemes for a continuous fermentor reactor

This article proposes a maximum likelihood algorithm for simultaneous estimation of state and parameter values in nonlinear stochastic state-space models. The proposed algorithm uses a combination of expectation maximization, nonlinear filtering and smoothing algorithms. The algorithm is tested with three popular techniques for filtering namely particle filter (PF), unscented Kalman filter (UKF) and extended Kalman filter (EKF). It is shown that the proposed algorithm when used in conjunction with UKF is computationally more efficient and provides better estimates. An online recursive algorithm based on nonlinear filtering theory is also derived and is shown to perform equally well with UKF and ensemble Kalman filter (EnKF) algorithms. A continuous fermentation reactor is used to illustrate the efficacy of batch and online versions of the proposed algorithms.