Current Issue - September 2021, Volume 13, Number 5 - International Journal of Computer Networks & Communications (IJCNC)

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The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.

Engineering

International Journal of Computer Networks &
Communications (IJCNC)
ISSN 0974 - 9322 (Online); 0975 - 2293 (Print)
(Scopus, ERA Listed, WJCI Indexed)
http://airccse.org/journal/ijcnc.html
Current Issue: September 2021, Volume 13, Number 5
Threshold based VM Placement Technique for Load Balanced Resource Provisioning
using Priority Scheme in Cloud Computing
Mayank Sohani and Dr. S. C. Jain, Rajasthan Technical University, India
A New Efficient Cache Replacement Strategy for Named Data Networking
Saad Al-Ahmadi, King Saud University, Saudi Arabia
An Effective Control of Hello Process for Routing Protocol in MANETs
Dhirendra Kumar Sharma and Nitika Goenka, University of Petroleum and Energy Studies, India
Sector Tree-Based Clustering for Energy Efficient Routing Protocol in Heterogeneous
Wireless Sensor Network
Nguyen Duy Tan, Vu Khanh Quy, Pham Ngoc Hung and Le Van Vinh, Hung Yen University of
Technology and Education, Vietnam
Dynamic Task Scheduling based on Burst Time Requirement for Cloud Environment
Linz Tom1
and Bindu V.R.2
, 1
Assumption College, India, 2
Mahatma Gandhi University, India
Investigating Multilayer Omega-Type Networks Operating with the Cut-Through
Technique under Uniform or Hotspot Traffic Conditions
Eleftherios Stergiou1
, John Garofalakis2
, Dimitrios Liarokapis1
and Spiridoula
Margariti1
, 1
University of Ioannina, Greece, 2
University of Patras and Computer Technology
Institute and Press- “DIOPHANTUS” (CTI) Patras, Greece
Privacy-Preserving Authentication Scheme for Roaming Service in Global Mobility
Networks
Sung Woon Lee1
and Hyunsung Kim2, 3
, 1
Tongmyong University, Korea, 2
University of Malawi,
Malawi, 3
Kyungil University, Korea
https://airccse.org/journal/ijc2021.html

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Current Issue - March 2022, Volume 14, Number 2 - International Journal of Co...

IJCNCJournal

The growth of Internet and other web technologies requires the development of new algorithms and architectures for parallel and distributed computing. International journal of Distributed and parallel systems is a bi monthly open access peer-reviewed journal aims to publish high quality scientific papers arising from original research and development from the international community in the areas of parallel and distributed systems. IJDPS serves as a platform for engineers and researchers to present new ideas and system technology, with an interactive and friendly, but strongly professional atmosphere.

Trends in heterogeneous computing in 2020

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Cloud computing helps enterprises transform business and technology. Companies have begun to look for solutions that would help reduce their infrastructures costs and improve profitability. Cloud computing is becoming a foundation for benefits well beyond IT cost savings. Yet, many business leaders are concerned about cloud security, privacy, availability, and data protection. To discuss and address these issues, we invite researches who focus on cloud computing to shed more light on this emerging field. This peer-reviewed open access Journal aims to bring together researchers and practitioners in all security aspects of cloud-centric and outsourced computing, including (but not limited to):

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Vehicular ad-hoc networks (VANETs) are characterized by limited network resources such as limited bandwidth and battery capacity. Hence, it is necessary that unnecessary use of network resources (such as unnecessary packet transfers) is reduced in such networks so that the available power can be conserved for efficient multicast communications. In this paper, we have presented a Transmit Packet Coding (TPC) Network Coding in VANET to ensure reliable and efficient multicasting. With network coding, the number of transmitted packets over the network can be reduced, ensuring efficient utilization of network devices and resources. Here, the trust-based graph optimization is performed using Cuckoo search algorithm to select the secure relay nodes. The experimental results showed the superiority of the presented approach compared to the existing techniques in terms of throughput, latency, hop delay, packet delivery ratio, network decoder outage probability, and block error rate.

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Energy is a serious resource parameter in Wireless Sensor Networks. Utilizing energy in an effectual manner is a challenging task in Wireless Sensor Networks. This paper presents an overview on various energy efficient routing protocols which fulfills the criteria of QoS parameters. Various energy effective and QoS based routing protocols have been compared. To improve the QoS in a network, data fusion and data accumulation is considered to be one of major energy saving technique. The routing protocols based on data aggregation, reduced cost routing and secure routing are also discussed in detail. Simulation tools like NS2, NS3, OMNET etc can be used to evaluate the network performance.

ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORKS BASED ON QOS

IAEME Publication

ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORKS BASED ON QOS

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International Journal of Computer Networks & Communications (IJCNC)

IJCNCJournal

Current Issue-Table of Contents-April 2019, Volume 9, Number ½

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The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.

International Journal of Computer Science & Information Technology (IJCSIT)-...

AIRCC Publishing Corporation

A mobile adhoc network is a collection of wireless mobile nodes that communicate with one another without any fixed networking infrastructure. Since the nodes in this network are mobile, the power management and energy conservation become very critical in mobile adhoc network. The nodes in this network have limited battery power and limited computational power with a small amount of memory. Such nodes must conserve energy during routing to prolong their usefulness and increase network lifetime. This research paper proposes a scheme that takes into consideration the power awareness during route selection. This scheme observes power status of each and every node in the topology and further ensures the fast selection of routes with minimal efforts and faster recovery. The scheme is incorporated with the AODV protocol and the performance has been studied through simulation over NS-2.

Power Management in Mobile Adhoc Network

drboon

Scope & Topics With the availability of low cost, short range sensor technology along with advances in wireless networking, sensor networks has become a hot topic of discussion. The International Journal of Advanced Smart Sensor Network Systems is an open access peer-reviewed journal which focuses on applied research and applications of sensor networks. While sensor networks provide ample opportunities to provide various services, its effective deployment in large scale is still challenging due to various factors. This journal provides a forum that impacts the development of high performance computing solutions to problems arising due to the complexities of sensor network systems. It also acts as a path to exchange novel ideas about impacts of sensor networks research.

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Non-orthogonal multiple access (NOMA) has been recognized as a potential solution for enhancing the throughput of next-generation wireless communications. NOMA is a potential option for 5G networks due to its superiority in providing better spectrum efficiency (SE) compared to orthogonal multiple access (OMA). From the perspective of green communication, energy efficiency (EE) has become a new performance indicator. A systematic literature review is conducted to investigate the available energy efficient approach researchers have employed in NOMA. We identified 19 subcategories related to EE in NOMA out of 108 publications where 92 publications are from the IEEE website. To help the reader comprehend, a summary for each category is explained and elaborated in detail. From the literature review, it had been observed that NOMA can enhance the EE of wireless communication systems. At the end of this survey, future research particularly in machine learning algorithms such as reinforcement learning (RL) and deep reinforcement learning (DRL) for NOMA are also discussed.

Energy-efficient non-orthogonal multiple access for wireless communication sy...

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Optical network is an emerging technology for data communication inworldwide. The information is transmitted from the source to destination through the fiber optics. All optical network (AON) provides good transmission transparency, good expandability, large bandwidth, lower bit error rate (BER), and high processing speed. Link failure and node failure haveconsistently occurred in the traditional methods. In order to overcome the above mentioned issues, this paper proposes a robust software defined switching enabled fault localization framework (SDSFLF) to monitor the node and link failure in an AON. In this work, a novel faulty node localization (FNL) algorithm is exploited to locate the faulty node. Then, the software defined faulty link detection (SDFLD) algorithm that addresses the problem of link failure. The failures are localized in multi traffic stream (MTS) and multi agent system (MAS). Thus, the throughput is improved in SDSFLF compared than other existing methods like traditional routing and wavelength assignment (RWA), simulated annealing (SA) algorithm, attackaware RWA (A-RWA) convex, longest path first (LPF) ordering, and biggest source-destination node degree (BND) ordering. The performance of the proposed algorithm is evaluated in terms of network load, wavelength utilization, packet loss rate, and burst loss rate. Hence, proposed SDSFLF assures that high performance is achieved than other traditional techniques.

SDSFLF: fault localization framework for optical communication using softwar...

International Journal of Reconfigurable and Embedded Systems

Over the past decades, computer networks have experienced an outbreak and with that came severe congestion problems. Congestion is a crucial determinant in the delivery of delay-sensitive applications (voice and video) and the quality of the network. in this paper, the Lagrangian optimization rate, delay, packet loss, and congestion approach (LORDPC) are presented. A congestion avoidance routing method for device-to-device (D2D) nodes in an ad hoc network that addresses the traffic intensity problem. The method of Lagrange multipliers is utilized for active route election to dodge heavy traffic links. To demonstrate the effectiveness of our proposed method, we applied extensive simulation that presents path discovery and selection. Results show that LORDPC decreases delay and traffic intensity while maintaining a high bitrate and low packet loss rate and it outperformed the ad hoc on-demand distance vector (AODV) protocol and the Lagrangian optimization rate, delay, and packet loss, approach (LORDP).

Optimized reduction approach of congestion in mobile ad hoc network based on...

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Hybrid medium access control (MAC) scheme is one of the prominent mechanisms to offer energy efficiency in wireless sensor network where the potential features for both contention-based and schedule-based approaches are mechanized. However, the review of existing hybrid MAC scheme shows many loopholes where mainly it is observed that there is too much inclusion of time-slotting or else there is an inclusion of sophisticated mechanism not meant for offering flexibility to sensor node towards extending its services for upcoming applications of it. Therefore, this manuscript introduces a novel hybrid MAC scheme which is meant for offering cost effective and simplified scheduling operation in order to balance the performance of energy efficiency along with data aggregation performance. The simulated outcome of the study shows that proposed system offers better energy consumption, better throughput, reduced memory consumption, and faster processing in contrast to existing hybrid MAC protocols.

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The efficient use of energy in wireless sensor networks is critical for extending node lifetime. The network topology is one of the factors that have a significant impact on the energy usage at the nodes and the quality of transmission (QoT) in the network. We propose a topology control algorithm for software-defined wireless sensor networks (SDWSNs) in this paper. Our method is to formulate topology control algorithm as a nonlinear programming (NP) problem with the objective to optimizing two metrics, maximum communication range, and desired degree. This NP problem is solved at the SDWSN controller by employing the genetic algorithm (GA) to determine the best topology. The simulation results show that the proposed algorithm outperforms the MaxPower algorithm in terms of average node degree and energy expansion ratio.

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The integration of artificial intelligence technology with a scalable Internet of Things (IoT) platform facilitates diverse smart communication services, allowing remote users to access services from anywhere at any time. The multi-server environment within IoT introduces a flexible security service model, enabling users to interact with any server through a single registration. To ensure secure and privacy preservation services for resources, an authentication scheme is essential. Zhao et al. recently introduced a user authentication scheme for the multi-server environment, utilizing passwords and smart cards, claiming resilience against well-known attacks. This paper conducts cryptanalysis on Zhao et al.'s scheme, focusing on denial of service and privacy attacks, revealing a lack of user-friendliness. Subsequently, we propose a new multi-server user authentication scheme for privacy preservation with fuzzy commitment over the IoT environment, addressing the shortcomings of Zhao et al.'s scheme. Formal security verification of the proposed scheme is conducted using the ProVerif simulation tool. Through both formal and informal security analyses, we demonstrate that the proposed scheme is resilient against various known attacks and those identified in Zhao et al.'s scheme.

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In -Vehicle Ad-Hoc Network (VANET), vehicles continuously transmit and receive spatiotemporal data with neighboring vehicles, thereby establishing a comprehensive 360-degree traffic awareness system. Vehicular Network safety applications facilitate the transmission of messages between vehicles that are near each other, at regular intervals, enhancing drivers' contextual understanding of the driving environment and significantly improving traffic safety. Privacy schemes in VANETs are vital to safeguard vehicles’ identities and their associated owners or drivers. Privacy schemes prevent unauthorized parties from linking the vehicle's communications to a specific real-world identity by employing techniques such as pseudonyms, randomization, or cryptographic protocols. Nevertheless, these communications frequently contain important vehicle information that malevolent groups could use to Monitor the vehicle over a long period. The acquisition of this shared data has the potential to facilitate the reconstruction of vehicle trajectories, thereby posing a potential risk to the privacy of the driver. Addressing the critical challenge of developing effective and scalable privacy-preserving protocols for communication in vehicle networks is of the highest priority. These protocols aim to reduce the transmission of confidential data while ensuring the required level of communication. This paper aims to propose an Advanced Privacy Vehicle Scheme (APV) that periodically changes pseudonyms to protect vehicle identities and improve privacy. The APV scheme utilizes a concept called the silent period, which involves changing the pseudonym of a vehicle periodically based on the tracking of neighboring vehicles. The pseudonym is a temporary identifier that vehicles use to communicate with each other in a VANET. By changing the pseudonym regularly, the APV scheme makes it difficult for unauthorized entities to link a vehicle's communications to its real-world identity. The proposed APV is compared to the SLOW, RSP, CAPS, and CPN techniques. The data indicates that the efficiency of APV is a better improvement in privacy metrics. It is evident that the AVP offers enhanced safety for vehicles during transportation in the smart city.

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Malware is one of the threats to security of computer networks and information systems. Since malware instances are available sufficiently, there is increased interest among researchers on usage of Artificial Intelligence (AI). Of late AI-enabled methods such as machine learning (ML) and deep learning paved way for solving many real-world problems. As it is a learning-based approach, accumulated training samples help in improving thequality of training and thus leveraging malware detection accuracy. Existing deep learning methods are focusing on learning-based malware detection systems. However, there is need for improving the state of the art through ensemble approach. Towards this end, in this paper we proposed a framework known as Deep Ensemble Framework (DEF) for automatic malware detection. The framework obtains features from training samples. From given malware instance a grayscale image is generated. There is another process to extract the opcode sequences. Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) techniques are used to obtain grayscale image and opcode sequence respectively. Afterwards, a stacking ensemble is employed in order to achieve efficient malware detection and classification. Malware samples collected fromthe Internet sources and Microsoft are used for theempirical study. An algorithm known as Ensemble Learning for Automatic Malware Detection (EL-AML) is proposed to realize our framework. Another algorithm named Pre-Process is proposed to assist the EL-AML algorithm for obtaining intermediate features required by CNN and LSTM.Empirical study reveals that our framework outperforms many existing methods in terms of speed-up and accuracy.

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With the emergence of smart devices and the Internet of Things (IoT), millions of users connected to the network produce massive network traffic datasets. These vast datasets of network traffic, Big Data are challenging to store, deal with and analyse using a single computer. In this paper we developed parallel implementation using a High Performance Computer (HPC) for the Non-Negative Matrix Factorization technique as an engine for an Intrusion Detection System (HPC-NMF-IDS). The large IoT traffic datasets of order of millions samples are distributed evenly on all the computing cores for both storage and speedup purpose. The distribution of computing tasks involved in the Matrix Factorization takes into account the reduction of the communication cost between the computing cores. The experiments we conducted on the proposed HPC-IDS-NMF give better results than the traditional ML-based intrusion detection systems. We could train the HPC model with datasets of one million samples in only 31 seconds instead of the 40 minutes using one processor), that is a speed up of 87 times. Moreover, we have got an excellent detection accuracy rate of 98% for KDD dataset.

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So far, Wireless Body Area Networks (WBANs) have played a pivotal role in driving the development of intelligent healthcare systems with broad applicability across various domains. Each WBAN consists of one or more types of sensors that can be embedded in clothing, attached directly to the body, or even implanted beneath an individual's skin. These sensors typically serve asingle application. However, the traffic generated by each sensor may have distinct requirements. This diversity necessitates a dual approach: tailored treatment based on the specific needs of each traffic typeand the fulfillment of application requirements, such asreliability and timeliness. Never the less, the presence of energy constraints and the unreliable nature of wireless communications make QoS provisioning under such networks a non-trivial task. In this context, the current paper introduces a novel Medium AccessControl (MAC) strategy for the regular traffic applications of WBANs, designed to significantly enhance efficiency when compared to the established MAC protocols IEEE 802.15.4 and IEEE 802.15.6, with a particular focus on improving reliability, timeliness, and energy efficiency.

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Cyber intrusion attacks increasingly target the Internet of Things (IoT) ecosystem, exploiting vulnerable devices and networks. Malicious activities must be identified early to minimize damage and mitigate threats. Using actual benign and attack traffic from the CICIoT2023 dataset, this WORK aims to evaluate and benchmark machine-learning techniques for IoT intrusion detection. There are four main phases to the system. First, the CICIoT2023 dataset is refined to remove irrelevant features and clean up missing and duplicate data. The second phase employs statistical models and artificial intelligence to discover novel features. The most significant features are then selected in the third phase based on cooperative game theory. Using the original CICIoT2023 dataset and a dataset containing only novel features, we train and evaluate a variety of machine learning classifiers. On the original dataset, Random Forest achieved the highest accuracy of 99%. Still, with novel features, Random Forest's performance dropped only slightly (96%) while other models achieved significantly lower accuracy. As a whole, the work contributes substantial contributions to tailored feature engineering, feature selection, and rigorous benchmarking of IoT intrusion detection techniques. IoT networks and devices face continuously evolving threats, making it necessary to develop robust intrusion detection systems.

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