Journal of Computer Networks and Communications
 Journal metrics
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Acceptance rate15%
Submission to final decision85 days
Acceptance to publication23 days
CiteScore6.400
Journal Citation Indicator0.430
Impact Factor-

Multi-Controller Placement Optimization Using Naked Mole-Rat Algorithm over Software-Defined Networking Environment

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Journal of Computer Networks and Communications publishes original research and review articles that investigate both the theoretical and practical aspects of computer networks and communications.

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Journal of Computer Networks and Communications maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

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Research Article

Performance and Improvement Analysis of the Underwater WSN Using a Diverse Routing Protocol Approach

The planet Earth is the most water-rich place because oceans cover more than 75% of its land area. Because of the extraordinary activities that occur in the depths, we know very little about oceans. Underwater wireless sensors are tools that can continuously transmit data to one of the source sensors while also monitoring and recording the physical and environmental parameters of their surroundings. An underwater wireless sensor network (UWSN) is the name given to the network created by the collection of these underwater wireless sensors. This particular technology is the most efficient way to analyse performance parameters. A network path is chosen to send traffic by using the routing method, a process that is also known as a protocol. The routing protocols ad-hoc on-demand distance vector (AODV), dynamic source routing (DSR), dynamic manet on demand routing protocol (DYMO), location-aided routing 1 (LAR 1), optimized link state routing (OLSR), source-tree adaptive routing optimum routing approach (STAR-ORA), zone routing protocol (ZRP), and STAR-least overhead routing approach (STAR-LORA) are a few models of routing techniques. By changing the number of nodes in the model and the maximum speed of each node, performance parameters such as average transmission delay, average jitter, percentage of utilisation, and power used in transmit and receive modes are explored. The results obtained using QualNet 7.1 simulator suggest the suitability of routing protocols in the UWSN.

Research Article

An Optimized and Energy-Efficient Ad-Hoc On-Demand Distance Vector Routing Protocol Based on Dynamic Forwarding Probability (AODVI)

MANET (mobile ad-hoc network) is a wireless ad-hoc network made up of mobile devices that use peer-to-peer routing to provide network access instead of using a preexisting network infrastructure. Despite the network infrastructure’s simplicity, it faces issues such as changeable connection capacity, dynamic topology, node battery power exhaustion, and inadequate physical security. Broadcasting is a standard MANET approach for sending messages from a source node to all other nodes in the network. Flooding is a frequent method for broadcasting route request (RREQ) packets, which is susceptible to broadcast storms. The high retransmission rate is caused by the standard flooding technique, which causes media congestion and packet collisions, which can drastically reduce throughput and network performance. In a mobile ad-hoc network, efficient broadcasting focuses on selecting a compact forward node set while assuring broadcast coverage. The goal is to find a limited number of forward nodes that will provide complete coverage. In this paper, we propose an optimized and energy-efficient routing protocol for MANET (mobile ad-hoc network) based on dynamic forwarding probability in general and AODV (ad hoc on-demand distance vector) in particular, in which the route request packets are randomly controlled to increase the network lifetime and reduce packet loss in the flooding algorithm. We tested and assessed the results of our proposed solution using various network performance factors after implementing and integrating it into NS-2. According to simulation findings, our proposed technique effectively reduced route request propagation messages (RREQ). The suggested technique is more efficient, has a longer network lifetime, and uniformly utilizes node residual energy, enhancing network throughput and minimizing routing overhead when compared to regular and modified AODV protocols.

Research Article

Chaotic Dynamics in Joint Price QoS Game with Heterogeneous Internet Service Providers

This paper tries to investigate the complex characteristics of the communication market where Internet service providers (ISP) lease network access services and compete to serve a large pool of subscribers. For this purpose, we analyze the dynamics of a mixed duopoly game with two decision parameters: price and quality of service (QoS). We calculate and discuss the stability of each equilibrium solution by using the nonlinear system. A numerical simulation is used to show the flip bifurcation to chaos by the decisions of ISPs with different statuses. We discovered that the Nash equilibrium loses stability when the speed of adjustment and transmission fee increase. We show that the system parameter changes the stability of the communication market. In addition, we use a control method to keep the communication market in a stable state.

Research Article

Improved Convolutional Neural Image Recognition Algorithm based on LeNet-5

Convolutional neural network (CNN) is a very important method in deep learning, which solves many complex pattern recognition problems. Fruitful results have been achieved in image recognition, speech recognition, and natural language processing. Compared with traditional neural network, convolutional weight sharing, sparse connection, and pooling operations in convolutional neural network greatly reduce the number of training parameters, reduce size of feature map, simplify network model, and improve training efficiency. Based on convolution operation, pooling operation, softmax classifier, and network optimization algorithm in improved convolutional neural network of LeNet-5, this paper conducts image recognition experiments on handwritten digits and face datasets, respectively. A method combining local binary pattern and convolutional neural network is proposed for face recognition research. Through experiments, it is found that adding LBP image information to improved convolutional neural network of LeNet-5 can improve accuracy of face recognition to 99.8%, which has important theoretical and practical significance.

Research Article

Optimal Management of Computer Network Security in the Era of Big Data

As the “new oil of the future,” big data is becoming the leading industry of the new economy, the core asset of the country and enterprises, the “new blue ocean” to be pursued, and the national strategy to be developed by all countries. The development of big data and its related technology supports and promotes a new round of technological innovation, making a new generation of information security technology reform and innovation, bringing opportunities and challenges to optimize, and consolidating national information security. In the era of big data, what kind of challenges and impacts will information security face? and is it crucial to explore the response strategies? At present, China has risen to become the world’s largest number of Internet users and the largest number of people using smartphones, but because China’s information security is the initial stage, involving information security, especially national information security laws and regulations are not much, the national social supervision and monitoring mechanisms are not much, the application level of science and technology content is relatively backward, the core technology has a patent technology not much, resulting in the flood of network data nowadays. Therefore, the underground illegal “data industry chain” activities are rampant. Therefore, this paper proposes a security-aware model based on the combination of distributed data analysis technology and data features. The model uses data features to dynamically generate a library of situational anomalies, effectively solving the problem of analyzing and processing rapidly and dynamically generated data streams, increasing the detection rate to more than 98%, effectively reducing the possibility of false detection, and having good results on large-scale datasets.

Review Article

SMAC-Based WSN Protocol-Current State of the Art, Challenges, and Future Directions

Wireless Sensor Networks (WSNS) have become an indispensable tool in this epoch of technological advancements, particularly for progress made in the Internet of things. Wireless sensor nodes are deployed to collect and transmit vital data from the environment to a base station for analysis. Nevertheless, the limited battery power of the sensor nodes is rapidly drained when they stay awake for an extended period. Research has shown that significant sources of energy dissipation of sensor nodes are idle listening, packet collision, control overhead, and overhearing. One optimal solution is employing a low duty cycle mac protocol, particularly the sensor mac (SMAC) protocol. It is essential to have a detailed knowledge of the challenges identified in SMAC and solutions suggested to mitigate these challenges and the future directions. In this paper, we review techniques in SMAC protocols implemented in WSNS. In particular, we provide highlights of recent developments in the schemes used in SMAC for mitigating the challenges in SMAC and present research gaps in SMAC protocol. Finally, we discuss open issues that need to be addressed to advance the design and implementation of SMAC in WSN applications.

Journal of Computer Networks and Communications
 Journal metrics
See full report
Acceptance rate15%
Submission to final decision85 days
Acceptance to publication23 days
CiteScore6.400
Journal Citation Indicator0.430
Impact Factor-
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