Meenu Chawla

A Technical Review for Efficient Virtual Machine Migration

This paper presents the recent technical research survey on the efficient live migration of virtual machines. Virtual machine migration is required for many reasons like load balancing, energy reduction, dynamic resizing, and to increase availability. Live migration is an important feature of virtualization technology. Virtualization technology has gained toehold with ascend of cloud computing. Simply, virtualization runs multiple virtual machines on the single physical machine. Virtual machine is a software based component which is an abstraction of the underlying hardware provided by the virtualization technology. Availability can be efficiently achieved by managing the virtual machines properly. For this, there is a need to migrate virtual machine from one physical machine to another, without expending long migration time and downtime. Virtual machine is running, while the migration is in progress is known as live migration. There are many techniques proposed to enhance the live migration, and reduce its duration This paper reviews the different approaches which have been proposed by researchers to improve the live migration by decreasing the downtime and total migration time. This paper can be useful for the researchers to work on this field.

Node stability based clustering algorithm for mobile ad hoc networks

Node mobility is an important factor at the time of clustering in ad hoc network because it directly affects the stability of cluster. In the proposed work a distributed clustering algorithm which uses node mobility as a main concern with battery power and connectivity in terms of no. of neighbouring nodes for selecting cluster heads to achieve better stability is being introduced. The proposed node stability based clustering algorithm (NSBCA) improves cluster stability, manageability and energy efficiency in MANET. The algorithm does not require to know the location of the node to be monitored by external means like GPS or mobility to be calculated by monitoring signal strength, the node itself monitor and records its movement and uses this information to elect cluster-head.

Spatial Domain Image Steganography based on Security and Randomization

In the present digital scenario secure communication is the prime requirement. Commonly, cryptography used for the said purpose. Another method related to cryptography is used for the above objective is Steganography. Steganography is the art of hiding information in some medium. Here we are using image as a means for covering information. Spatial domain image Steganography has been used for the work because of its compatibility to images. Objective of the paper is to increase the capacity of hidden data in a way that security could be maintained. In the current work MSB of the randomly selected pixel have been used as indicator. Result analysis has been performed on the basis of different parameters like PSNR, MSE and capacity.

Privacy preservation for WSN: A Survey

This paper presents a review of privacy-preserving techniques for wireless sensor networks (WSN). A lot of work has been done to enhance efficient use of power and resources in wireless sensor networks with the help of specific routing algorithms and different layers’ protocols. As the popularity and uses of wireless sensor network increase, privacy of individuals is of very high demand. In this paper two main categories of privacy preserving techniques for WSN have been presented, data-oriented and context-oriented. Some interesting open challenges for future research have also been introduced. This paper should provide some fruitful help for further research in privacy preservation for WSN.

Enhanced ad hoc on demand Distance Vector Local Repair Trial for MANET

Ad hoc On-demand Distance Vector (AODV) is a routing schema for delivering messages in a connected Mobile Ad hoc Network (MANET). Connectivity between any sources to destination pair in the network exists when they are in radio range of each other. Local Repair is an important issue in routing protocol which is needed for minimizing flooding and performance improvement. Routes can be locally repaired by the node that detects the link break along the end to end path. In this paper, the existing Local Repair Trial method in AODV is extended to achieve broadcasting and minimizing the flooding. The enhanced protocol first creates the group of mobile nodes then broadcasting can be done and if the link breaks then local repair technique can be applied. In the network the numbers of intermediate nodes are increased by using Diameter Perimeter Model. Enhanced AODV-Local Repair Trial (EAODVLRT) protocol is implemented on NS2 network simulator. Simulations are performed to analyze and compare the behavior of proposed protocol (EAODVLRT) for varying parameters such as size of network, node load etc. Proposed protocol has been compared with the existing AODV-LRT in terms of routing load, Data delivery ratio.

Modified Different Neighbor History Spray and Wait using PROPHET in Delay Tolerant Network

Delay Tolerant Networks or Disruption Tolerant Networks are intermittent networks that may lack continuous connectivity as most of the time there does not exist a direct link between source and destination for message transmission. In this paper, Modified DNH (Different Neighbor-History) Spray and Wait using PROPHET is proposed. It improves the wait phase of Different Neighbor-History Spray and Wait. This protocol calculates number of message copies to be forwarded based on performance of receiver node in spray phase and in wait phase the waiting node uses probabilistic routing protocol using history of encounters and transitivity for transmission. Simulation results show that this method improves delivery probability and average latency of transmission as compared to Spray and Wait and also DNH-Spray and Wait routing scheme. General Terms Delay Tolerant Network, Opportunistic Network Environment Simulator

A Survey of Android Malware Detection Strategy and Techniques

The expeditious growth of Android malwares has posed a serious challenge in front of researchers. The researchers are continuously proposing countermeasures and developing tools to mitigate against such attacks. In this paper, widely used techniques that have been proposed recently by researchers have been explored. The key contributions of each of these techniques along with their limitations have been analyzed. All these techniques were compared based on nine parameters and it was identified that Mobile Sandbox tool is the best when time factor is not considered because it possess the capability of both a static and dynamic analysis, native API call tracking and web accessibility. If time factor is considered, then Dendroid performs best among all. This is due to the reason that it applies text mining to get the signature of malware and it can also classify unknown malware sample through 1-NN classifier.

Image Encryption using Block Shuffling and Affine Transform: A Review

The rapid development of communication technology due to the global spread of the internet and the digital information revolution has given rise to a huge increase in the use and transmission of multimedia information. Encryption technology is studied in this paper, and a new image encryption algorithm based on correlation of pixels is proposed. The main goal of this paper is security management. Researchers have proposed incompatible methods to encrypt images. So, here we go through a new way of image encryption and decryption using block based image encryption using affine transform. First of all the plain image is divided into fixed size blocks. All these blocks then shuffled according to the proposed algorithm and we get a block shuffled image. At last the encrypted algorithm of affine is used iteratively for each of the pixels. It uses the keys for the purpose of encryption.

I-2ACK: Preventing Routing Misbehavior in Mobile Ad hoc Networks

Mobile Ad hoc NETwork (MANET) is considered as network without infrastructure where communication between the mobile nodes solely depends on the routing protocols which work on assumption that nodes are fully cooperative. In the presence of misbehaving nodes, most of the routing protocols show dropped performance and in some case whole of the network fails. Misbehaving nodes interrupt the data flow by either by dropping or refusing to forward the data packets thus forcing routing protocol to restart the route-discovery or to select an alternative route if available which may again include some misbehaving nodes, thereby forming a loop, enforcing source node to conclude that data cannot be further transferred. In this paper, a new reputation based approach is proposed which deals with such misbehaving nodes and can be integrated on top of any source routing protocol Proposed approach consists of detection and isolation of misbehaving nodes and based on sending acknowledgement packets back for reception of data packets.

Viable Crop Prediction Scenario in BigData Using a Novel Approach

Agriculture leads a vital role in the human surveillance where it lies as the initial step for the human civilization. Due to the excessive need for food, the agricultural practices are in large-scale production as a business which is termed as “Agribusiness”. Modern agriculture allows both biological and technological developments such as plant breeding, agrochemicals, genetic breeding, remote sensing, crop monitoring, sensor nodes, and automatic maintenance system. The integration of sensor nodes in the farming field leads to the generation of huge data which can need a learning algorithm for analyses to determine a specific solution. There are various machine learning algorithms in practices which are not suitable for handling large datasets. In this paper, a novel algorithm “Agrifi-prediction algorithm” is created which has the functionality of loading the dataset in hdfs and comparing the previous dataset with the current processing dataset. The experimental process is carried out by using the Hadoop framework with MapReduce programming model by analyzing the meteorological and soil dataset and finally compared with the machine learning algorithm to evaluate the accuracy.