International Journal of Computer Networks and Applications

103 - 115

Authors: D. Somashekhara Reddy, C. Chandrasekhar

In a Wireless Sensor Network (WSN), seamless mobility management can change the current mobile node’s location point to another network devoid of any link failure during communication. The seamless mobility system is very useful to detect the nearest base station over the wireless network without any distinct interference. In this paper, a novel technique called Support Vector Regressive Dragonfly Optimization based Shift Invariant Deep Neural Learning (SVRDO-SIDNL) is introduced for improving the seamless data transmission with minimum delay. The Shift Invariant Deep Neural Learning comprises of many layers to learn the series of input. For each layer, the different processes are carried out to accomplish the traffic optimized seamless data delivery. The input layer of the deep neural learning receives mobile nodes with coverage region and then is sent to the hidden layer. The mobile nodes' signal strength is analyzed by applying the support vector regression at the hidden layer. Then, the node with weak signal strength is identified and performs the handover. Through oppositional learned multi-objective dragonfly optimization technique, recognition of nearby attachment points with greater bandwidth availability is performed for the handover process. Then, the mobile node connection is altered from the existing attachment point to a new attachment point without losing connectivity. The simulation results reveal that the SVRDO-SIDNL technique offers a greater delivery rate, throughput with lesser packet loss at less delay.

82 - 92

Authors: G. Kiruthiga, S. Mary Vennila

Scheduling of tasks in a cloud environment has larger influence on time and energy depletion. Different heuristic models were developed to solve the NP-hard task scheduling problem based on time. However, ideal task scheduling algorithms must also maximize energy efficiency with good load balancing and ensure better Quality-of-Service (QoS). An innovative multi-objective Chaotic Darwinian Chicken Swarm Optimization (CDCSO) system is suggested in this article to provide energy efficient QoS and load balancing aware task scheduling. The multi-objective CDCSO algorithm incorporates the chaotic and Darwinian Theory to the standard Chicken Swarm Optimization to increase its global exploration and maximize the convergence rate. This performance enhanced CDCSO algorithm models the cloud task scheduling problem as NP-hard and utilizes the optimization principles to solve them based on multiple objective parameters. The multi-objective fitness function used in CDCSO is modelled based on the objective parameters namely energy, cost, task completion time, response time, throughput and load balancing index. Based on this multi-objective function, the CDCSO effectively allocates the tasks to the suitable energy efficient, cost and time minimized Virtual machines (VMs) which are also optimally load balanced. CloudSim simulations were conducted and the obtained results illustrated that the proposed multi-objective CDCSO has provided better task scheduling with minimized energy, cost, time and optimal load balancing.

28 - 42

Authors: M. Usha, J. Sathiamoorthy, R. Ashween, Bhagavath Nishanth Ramakrishnan

Underwater communication is a newer addition to the ad hoc network arena as it opens several avenues of research that can be carried out under water. It has a varied range of applications which it carries out with the help of Autonomous Underwater Vehicles (AUV).Acoustic waves are used for sending out the network signals because they tend to have a lower attenuation under water. Underwater Acoustic Communication (UWAC) is used to send and receive signals underwater. Since UWAC is a relatively new field, there are still a lot of challenges to overcome. Unlike terrestrial communication, UWAC has to encounter factors like limited bandwidth, longer propagation delay, Doppler Effect, and channel availability problems. All of these factors have a direct effect on the throughput. Clustering the network can effectively help in managing the network efficiently. We have proposed an Energy Efficient Minimum Cost Cluster routing Protocol (EEMCCP), which routes packets with the help of clusters. The clustering of the network is efficiently achieved by using the Chaotic Algae Algorithm (CAA).After clustering the network, one node from each cluster acts as the Cluster Head (CH). The proposed protocol does not require any node position information and also ensures that, only a minimal number of nodes are involved in the end to end routing process. Some of the Cluster Heads are selected as gateway nodes based on their RSSI (Received Signal Strength Indictor) values of the Hello packets. Selected CHs are appointed as gateway nodes that are responsible for supplying the data to the AUV nodes that are nearer to them. When these gateway CH nodes exhaust their energy, back up nodes act as gateway nodes thus making the protocol a flexible one. In fact, the node location and position are not taken into consideration. The AUV nodes transfer the acquired information to a communication link which in turn transfers the data to a terrestrial destination. The EEMCCP focuses towards a cost effective solution for transmitting data. The performance of EEMCCP is compared with the existing protocols employed for underwater communication. From the analysis, we find that EEMCCP achieves a good throughput and PDR than the existing protocols.

10 - 18

Authors: Istteffanny Isloure Araujo, Hassan Kazemian

This article analyses the ways malicious executable files hides with Steganography on the most used files of our daily basis such as PDF, Word, Text, and Image. It demonstrates how data is hidden and gathers innovative ways of identifying potential attacks to prevent them by engaging the safety and exploitation of files distributed online. It is concerned with infected files that can have malicious executable applications embedded, executing itself upon the opening of the original file. Several experiments are detailed exploiting gaps in PDF, email and image files in order to draw awareness to security professionals and Ethical hackers' trainees.

100 - 109

Authors: Hushmat Amin Kar, G.M. Rather

Internet of Things (IoT) is improving the overall quality of our lives by helping us to connect, measure and control the different parameters of the system in an automated manner. The IoT devices are generating massive volumes of data that needs to be processed and on the basis of the results, decisions are made. The IoT devices have limited resource capabilities, so these devices utilize the services of the cloud servers. The issue in utilizing the services of the cloud is that it fails to provide support for real-time and time-critical applications. In order to reduce the response time of the system, another service layer is added to the architecture i.e. Edge computing. The IoT devices will now send their requests to the edge servers. Utilizing the services of the edge servers will reduce both the network traffic to the cloud and response time of the system. This paper presents a detailed survey of Edge-based IoT taking various parameters like architecture, bandwidth, security, energy, payload, etc. into consideration.