Location Estimation Based on Semi-Supervised Locally Linear Embedding (SSLLE) Approach for Indoor Wireless Networks

Location aware computing is popularized and location information use has important due to huge application of mobile computing devices and local area wireless networks. In this paper, we have proposed a method based on Semi-supervised Locally Linear Embedding for indoor wireless networks. Previous methods for location estimation in indoor wireless networks require a large amount of labeled data for learning the radio map. However, labeled instances are often difficult, expensive, or time consuming to obtain, as they require great efforts, meanwhile unlabeled data may be relatively easy to collect. So, the use of semi-supervised learning is more feasible. In the experiment 101 access points (APs) have been deployed so, the RSS vector received by the mobile station has large dimensions (i.e. 101). At first, we use Locally Linear Embedding to reduce the dimensions of data, and then we use semi-supervised learning algorithm to learn the radio map. The algorithm performs nonlinear mapping between the received signal strengths from nearby access points and the user??s location. It is shown that the proposed scheme has the advantage of robustness and scalability, and is easy in training and implementation. In addition, the scheme exhibits superior performance in the nonline-of-sight (NLOS) situation. Experimental results are presented to demonstrate the feasibility of the proposed SSLLE algorithm.     

An SIRS epidemic model on a dispersive population

The spatial spread of a disease in an SIRS epidemic model with immunity imparted by subclinical infection on a population has been considered. The incidence rate of infection and the rate of immunization are both of nonlinear type. The dynamics of the infectious disease and its endemicity in local and global sense have been investigated.     

A proactive defense method for the stealthy EDoS attacks in a cloud environment

Cloud computing technology provides flexibility to Cloud Service Provider (CSP) for providing the cloud resources based on the users' requirements. In on‐demand pricing model, the attackers exploit this feature and cause unwanted scaling‐up of the cloud resources without any intent to pay for them. The associated cost for the unpaid malicious usage burdens the CSP, and over a long period, economic losses occur at the CSP end. Thus, the resources and services offered by the CSP become unsustainable, and the attack is termed as Economic Denial‐of‐Sustainability (EDoS) attack. The existing defense approaches for EDoS attacks are reactive. Thus, the associated attack detection/mitigation cost is high; consequently, the approaches are not suitable for the Small and Medium Enterprises (SMEs). The aim of this paper is to detect and mitigate, internal and external, stealthy EDoS attacks proactively. The attack is detected using average CPU utilization threshold and utility function (in terms of cost for the utilized cloud computing resources) and mitigated using virtual firewalls. Amazon Elastic Compute Cloud (Amazon EC2) is used to evaluate the performance of the proposed approach. The proposed approach accurately detects the EDoS attack and mitigates its effect as well with reduced cost. It is observed that the approach provides competitive response time, victim service downtime, and attack reporting time. Thus, the overall performance is improved.     

Detection of Low-Rate Cloud DDoS Attacks in Frequency Domain Using Fast Hartley Transform

Distributed Denial-of-Service (DDoS) attack has been a serious threat to the availability feature of cloud computing. As traditional DDoS attacks are implemented using a huge volume of malicious traffic, the detection of such attacks becomes a naive task. To evade this detection, attackers are moving towards the Low-Rate DDoS (LRDDoS) attacks. The stealthy behavior of LRDDoS attack makes it difficult to get detected due to its low volume traffic. The existing frequency-domain approaches for LRDDoS detection are not feasible in terms of computational and storage requirements. This paper aims to propose a lightweight, accurate, and adaptive approach for the detection of LRDDoS attacks in frequency-domain. In this paper, the LRDDoS attack is detected by analyzing the power spectral distribution. The novelty of the proposed approach is to calculate the power spectral density using Fast Hartley Transform (FHT). The FHT processes real-valued input data, and has low computational and storage complexities. The approach is implemented on OpenStack cloud platform, and the aggregate network traffic (external and internal) is captured and analyzed. Experimental results show that the computational and storage complexities involved in FHT are lower than other transformation algorithms’ complexities. Thus, the approach provides faster response with an average detection time of 60.16 s. The average true negative and true positive rates obtained by the proposed approach are 99.83% and 99.46% respectively, which are competitive.

     

A review on rendezvous based data acquisition methods in wireless sensor networks with mobile sink

Wireless Networks - Solutions for energy hole problem in wireless sensor networks (WSNs) have been excessively explored using mobile sink (MS). Although, MS provides a considerable amount of energy...     

A Survey on Path Planning Techniques for Mobile Sink in IoT-Enabled Wireless Sensor Networks

Wireless Personal Communications - Recently, the Internet of Things (IoT) had emerged very rapidly and became the most important technology in today’s era. In an IoT-based environment, every...     

Mobility prediction in mobile ad hoc networks using a lightweight genetic algorithm

A mobile ad hoc network is a collection of wireless mobile nodes creating a network without using any existing infrastructure. Much research has been carried out to find out an optimal routing protocol for the successful transmission of data in this network. The main hindrance is the mobility of the network. If the mobility pattern of the network can be predicted, it will help in improving the QoS of the network. This paper discusses a novel approach to mobility prediction using movement history and existing concepts of genetic algorithms, to improve the MANET routing algorithms. The proposed lightweight genetic algorithm performs outlier removal on the basis of heuristics and parent selection using the weighted roulette wheel algorithm. After performing the genetic operations a node to node adjacency matrix is obtained from which the predicted direction of each node is calculated using force directed graphs and vector calculations. The technique proposes a new approach to mobility prediction which does not depend on probabilistic methods and which is completely based on genetic algorithms.     

Synthesis and characterization of fully aliphatic polyimides from an aliphatic dianhydride with piperazine spacer for enhanced solubility,transparency, and low dielectric constant

A new series of fully aliphatic polyimide (API) based on a novel aliphatic dianhydride monomer‐2,2′‐(1,4‐piperazinediyl)‐disuccinic anhydride (PDA), in which two units of succinic anhydride have been connected by an aliphatic heterocyclic piperazine spacer that possesses aminomethylene (‐NCH₂) moiety in the aliphatic/alicylic backbone capable of inducing charge transfer (CT) interactions in the polyimide network, was successfully synthesized. The APIs were soluble in common polar organic solvents. The polyimide films of PDA with alicyclic diamines were almost colorless. T₁₀ (temperature of 10% weight loss) of APIs were ranged from 299–418 °C and T_g of API3‐API6 were in the temperature range of 170 to 237 °C. The light‐colored polyimide films of API3‐API6 possessed good mechanical properties with tensile strength of 54–72 Mpa, tensile modulus of 1.6–2.3 Gpa and elongation at break of 4–9%. The polyimide films of API3‐API6 were highly flexible and free‐standing which is quite rare in fully APIs. The dielectric constant of one of the synthesized API (API4) was as low as 2.14. © 2014 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2014 , 52, 2316–2328     

PEG-mediated catalyst-free expeditious synthesis of 2-substituted benzimidazoles and bis-benzimidazoles under solvent-less conditions

A wide variety of 2-substituted benzimidazoles and bis-benzimidazoles were synthesized in high yields by PEG-mediated catalyst-free synthesis under solvent-less conditions. The products were directly recrystallized from hot methanol. The reaction occurred giving excellent yields with low as well as high molecular weight PEGs.     

Gateway load balancing using multiple QoS parameters in a hybrid MANET

A Mobile ad hoc network (MANET) is a self configurable wireless network in which mobile nodes communicate with each other in a multihop fashion without any pre-installed infrastructure. A MANET can be considered to be a standalone network. To enhance the connectivity of a MANET it can be connected to the fixed network, thus forming a heterogeneous network. The integration of MANET and the Internet is called a hybrid MANET which is facilitated by special nodes called Internet gateway nodes. Load balancing among gateways is a challenging task when a MANET is connected to Internet. Gateway nodes with higher loads will lead to disconnected networks and depletes the node’s resources which include their batteries, memory and bandwidth quickly. Gateway selection based on the shortest path may increase traffic concentration on one particular gateway which leads to congestion and increases delay in the network. In this paper a QoS based load balancing mechanism has been proposed among multiple gateway nodes that provide communication between mobile nodes and fixed nodes in the Internet to select lightly loaded gateways so that more packets will be delivered to the fixed host in the Internet. The proposed QoS based scheme selects four QoS parameters that are (1) connecting degree, (2) interface queue length, (3) routing table entries and (4) hop count. A weight based method is used to select the gateway which combines all four QoS metrics. Simulation results demonstrate that when compared with individual parameter, the average ETE delay, queue size and traffic load of gateway generated by proposed algorithm is decreased by 17, 25 and 15 % respectively and when compared with existing schemes, the average ETE delay, queue size and traffic load of gateway is decreased by 25, 25 and 16 % respectively.