The International Journal of Communication Systems publishes research papers on public and private communication technology systems. This communications journal welcomes submissions that provide in-depth analyses of research and development work, emerging communications trends, and practical applications of communication technologies. Our authors and readers include telecommunications researchers, technical managers, and communications and television engineers.

 

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RESEARCH ARTICLE

Improving rate wireless sensor network with collaborative energy among nodes with fusion center and multiple antennas sensors using game theory and energy harvesting

  •  27 February 2024

Graphical Abstract

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This paper investigates optimizing the collaborative energy power consumption between nodes with energy harvesting capability at the fusion center (FC) and multi-antenna sensors using game theory. Modes are suggested to minimize the collaborative energy among sensors for transmitting the data and energy among sensors. Suggestions have been studied based on the number of antenna to transmit, using the cooperative games in sharing the data and the energy and auction game in transmitting to FC.

RESEARCH ARTICLE

A novel arc‐shaped four‐port wideband (21.8–29.1 GHz) MIMO antenna with improved characteristics for 5G NR networks

  •  27 February 2024

Graphical Abstract

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The prescribed four-port MIMO antenna features a broad frequency range of 7.3 GHz from 21.8 to 29.1 GHz, a peak gain of 5.76 dBi at 29 GHz, and a good isolation less than −18 dB. The designed MIMO model has been fabricated on a Rogers RT/duroid 5880 substrate of 31.891 × 37.5885 × 0.508 mm3. The suggested antenna offers excellent diversity performance by offering superior ECC and DG metrics.

RESEARCH ARTICLE

A Bayesian approach using spatiotemporal features for suitable next hop selection in opportunistic networks

  •  26 February 2024

Graphical Abstract

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Bayesian approach using spatiotemporal features for suitable next hop selection in opportunistic networks (BPPR) is an OppNet routing protocol based on Bayesian posterior probability that uses spatiotemporal features of a node mobility to determine the movement pattern of the nodes among several “area of interests” or cluster points, determined dynamically within the network. The major contribution of this work includes determining the cluster points within the network where a specific number of nodes generally gather, recording the spatiotemporal features of node movement within these clusters with respect to time duration of day and day of week, and finally predicting the future location of a node using Bayes' posterior probability. On analysis, it is found that this model outperforms the benchmark protocols—Epidemic, Prophet, HBPR, NexT, and EBC in terms of delivery probability, hop count average, overhead ratio, and number of messages dropped.

RESEARCH ARTICLE

Development of an indoor corridor localization system based on a WCL method with corridor area selection and distance compensation

  •  26 February 2024

Graphical Abstract

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In this paper, an RSSI-based WCL method for indoor corridor scenarios is developed. The possible corridor area where the target node should be located is automatically selected, and distance values converted from measured RSSIs are also compensated to alleviate the RSSI variation problem. The proposed method outperforms the original WCL method by 53.053%, as indicated by average localization errors, while all estimated positions fall within the corridor areas by 100%.

RESEARCH ARTICLE

OHRDBN: An optimized hybrid model of RBF and DBN for obstacle‐aware routing with optimal path selection in VANET sector

  •  25 February 2024

Graphical Abstract

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The main aspect of the proposed work is to detect the obstacle and determine the path availability. The parameter optimization in the Hybrid classifier model is done with the help of the Adaptive Chimp Optimization Algorithm (ACOA). Finally, the objective function for the proposed work is constructed by considering various constraints like distance, energy, link availability, life span, link duration, and mobility. The outcome of the suggested model demonstrates that it attains better result than the other approaches.

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The following is a list of the most cited articles based on citations published in the last three years, according to CrossRef.

Internet of Things

  •  1101-1102
  •  29 August 2012
No abstract is available for this article.

Novel methods for energy charging and data collection in wireless rechargeable sensor networks

  •  10 September 2015

Graphical Abstract

Description unavailable

We study the problem of scheduling minimum mobile devices to periodically recharge and collect data from sensors subject to the limited charging range, electric capacity, and memory storage, such that the network lifetime can be guaranteed to be prolonged without limits. For the problem, several algorithms are proposed to find a set of anchor points and schedule minimum mobile devices to visit the generated anchor points. Simulation results show that our proposed methods provide good performance.

Detection and defense of DDoS attack–based on deep learning in OpenFlow-based SDN

  •  8 January 2018

Graphical Abstract

Description unavailable

This paper introduces a DDoS detection model and defense system based on deep learning in Software Defined Network (SDN) environment. The model can learn patterns from sequences of network traffic and trace network attack activities in a historical manner. The experimental results demonstrate the much better performance of our model compared with conventional machine learning ways. Moreover, the implemented defense system based on the model can effectively clean the DDoS attack traffic.

A novel dynamic clustering approach for energy hole mitigation in Internet of Things‐based wireless sensor network

  •  10 April 2021

Graphical Abstract

Description unavailable

The dynamic clustering is proposed to alleviate energy hole problem. As the sink is placed outside the network, the one gateway node (GN) is located in each half of the network area. In each cluster, two CHs are selected, only one is active at one moment. However, when the energy of active CH drops by 60% of its initial energy, it goes to sleep mode. This process is repeated till both nodes come to the same level of energy. Thereafter, only one CH becomes active and other becomes cluster member. The selection of CH and GN is done based on energy, distance, number of neighbour nodes and network's residual energy.

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