Forthcoming and Online First Articles

International Journal of Smart Grid and Green Communications

International Journal of Smart Grid and Green Communications (IJSGGC)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression "in press". For example: Smith, J. (in press). Article Title. Journal Title.

Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase.

Online First articles are published online here, before they appear in a journal issue. Online First articles are fully citeable, complete with a DOI. They can be cited, read, and downloaded. Online First articles are published as Open Access (OA) articles to make the latest research available as early as possible.

Open AccessArticles marked with this Open Access icon are Online First articles. They are freely available and openly accessible to all without any restriction except the ones stated in their respective CC licenses.

Register for our alerting service, which notifies you by email when new issues are published online.

We also offer which provide timely updates of tables of contents, newly published articles and calls for papers.

International Journal of Smart Grid and Green Communications (9 papers in press)

Regular Issues

  • Nature inspired firefly algorithm for efficient tasks management in smart grid   Order a copy of this article
    by Basetty Mallikarjuna 
    Abstract: In smart grid environment the increase in network bandwidth, energy management, and power management are a challenging issues. The demand for integrated services like IoT-based cloud infrastructure, at the end of the network of fog computing, it optimises the resource utilisation and effective management of tasks makes a significant role. The tasks are moved from one resource to another resource in an important paradigm of cloud-fog platform (CFP) for efficient resource allocation. This paper proposes an efficient firefly algorithm (FFA) to maximise the resource utilisation and provided effective management of tasks provided by the service level agreement (SLA). The effective management of task contains several factors such as allocation of tasks to virtual machines (VMs), data centres and fog nodes. This paper provides an improved performance of quality of service (QoS) parameters like execution time, response time, makespan, migration of tasks. And also this paper compared FFA algorithm with the existing algorithm honey bee behaviour load balancing algorithm (HBLBA). The proposed FFA algorithm provides effective management of tasks in terms of QoS metrics.
    Keywords: cloud-fog platform; CFP; IoT-based cloud; service level agreement; SLA; quality of service; QoS; virtual machines; makespan; migration of tasks; fog nodes; data centres.

  • FDMA approach for smart grid and green communications   Order a copy of this article
    by Basetty Mallikarjuna 
    Abstract: The goal of this article is a new approach for competitors in the area of smart grid and green communications. The integrated services like internet of things (IoT)-based cloud begins up in the smart grid environment provides consciousness for new cross-disciplinary research. In this article, a suggested feedback-based data management assistance (FDMA) offers networking services, large storage, huge computation, and data processing to the end-users and among IoT-based cloud contains integrated environment of smart grid. The real-time applications of IoT, like smart home, smart car, smart city to achieve smart country and demand less latency and response time to process the enormous amount of data. The anticipated feedback-based data management plan offers a new resource management method, which is comprised of a unified structural design and retains the SLA and QoS parameters. The simulated environment analysed with the ThingSpeak open source platform and derives the smart parking application and examined the iFogSim with MATLAB tool kits has demonstrated that the intended methodology is efficient and appropriate for smart interaction in IoT-based cloud.
    Keywords: internet of things; IoT; iFogSim; quality of service; QoS; service-level agreement; SLA; feedback-based data management assistance; FDMA; ThingSpeak; cloud data centres.

  • FBDP approach in IoT-based cloud for self-treatment in healthcare using smart grid   Order a copy of this article
    by Basetty Mallikarjuna 
    Abstract: This paper throws lights on the idea of integrating architecture of IoT and cloud for smart grid environment, the IoT devices organised with the IoT-layer, supported by the cloud service providers. Feedback-based data processing (FBDP) design is proposed to maintain the quality of service (QoS) metrics and the service level agreement (SLA) between the IoT-based cloud environment and effective data transmission required for movements of the patients and necessity of self-treatment. The proposed (FBDP) model elaborates the credibility while IoT devices are connected through the smartphone and provides a service through the gateway as a smart device. The proposed idea is mostly useful for healthcare applications and for self-treatment like tele-medicine. This model also able to deal with the QoS metrics such as service discovery, energy optimisation, makespan, response time, network bandwidth and security. The performance of the proposed model is simulated with the iFogSim toolkit and tested with the real time database. The results proved that the proposed model is efficient for smart grid environment in healthcare applications.
    Keywords: integrated architecture; feedback-based data processing; FBDP; QoS metrics; iFogSim; sensor nodes; tele-medicine; IoT-based cloud; gateway.

  • Communication technologies and standards in smart grid: a survey of state-of-the-art   Order a copy of this article
    by Vimal Tiwari, Salil Madhav Dubey, Hari Mohan Dubey, Manjaree Pandit 
    Abstract: The existing power grid has undergone drastic changes within a decade, in order to deal with the increase in energy demand. With the integration of different distributed energy resources (DERs) for a set of different loads which are interconnected to each other within a well-defined electrical area, Microgrid came into existence. However, with the increased use of effective communication, automation and monitoring skills the microgrid based power grid are switched to a technologically advanced and fast response grid termed as smart grid. In smart grid, efficient and reliable communication is incorporated to improve the efficiency, sustainability, and stability of the whole system. This paper presents a review on the different types of available communication methods and protocols which are used for data communication within and outside a smart grid based power supply system.
    Keywords: smart grid; communication methods; communication protocols; communication standards; microgrid.
    DOI: 10.1504/IJSGGC.2022.10050458
  • Scheduling of multi-fuel energy resources in microgrid using grey wolf optimisation   Order a copy of this article
    by Salil Madhav Dubey, Hari Mohan Dubey, Manjaree Pandit 
    Abstract: Implementation of a microgrid (MG) to establish an independent, efficient, and cost-effective power supply system is the need of the hour. The generation in MG can be conventional or non-conventional. Still, due to increasing power demand, high fuel prices, scarcity of fossil fuels, and degrading the environment, there is a growing demand for renewable energy sources (RS) for power generation. Multi-fuel power sources like solar, wind, fuel cells, etc., improve the adequacy, and increase supply reliability, provide a dynamic response. This paper discusses the dynamic scheduling of MGs in two different systems with distinguishing distributed generation (DG) units. Grey wolf optimisation (GWO), a meta-heuristic technique inspired by the hierarchical hunting mechanism of grey wolves, is used in this paper to solve a multi-objective problem in a dynamic environment. The performance and effectiveness of GWO are compared and validated with methods like CSA, ABC, DE, and PSO.
    Keywords: microgrid; renewable energy integration; grey wolf optimisation; GWO; dynamic scheduling; fuel cells; wind power units; distribution generation; solar plants; multi-objective scheduling.
    DOI: 10.1504/IJSGGC.2022.10049383
  • Performance evaluation of energy aware QoS-enabled routing protocol for wireless mesh networks   Order a copy of this article
    by Y. Mallikarjuna Rao, M.V. Subramanyam, K. Satya Prasad 
    Abstract: This paper proposes an energy aware routing protocol for wireless mesh network (WMNs). In such applications the mesh nodes may not expect the fixed power supply connections for their normal operation. Hence, mesh nodes may rely on ambient energy. In such untenable cases, we require energy aware routing protocols to prevent deterioration of the network performance due to power outages of the nodes. This paper proposes an energy aware QoS-enabled routing (EAQER) protocol based on the node weight and path preference probability. The EAQER is analysed and shown superior performance compared to baseline routing protocols in terms of route request messages, route reply messages, average throughput, end to end delay, jitter, and packet delivery ratio.
    Keywords: node weight; path preference probability; quality of service; routing; wireless mesh networks; WMNs.

  • An interpretable COVID-19 chest X-ray classification through transfer learning and discriminative localisation-based deep learning techniques   Order a copy of this article
    by Lavanya Yamathi, K. Sandhya Rani 
    Abstract: The present time is marked by the upsurge of coronavirus (COVID-19) pandemic, which persists and has catastrophic consequences on global health and well-being. In addition to RT-PCR test, CT scan and chest X-ray have become essential in detecting and treating COVID-19 patients. Several deep learning frameworks have been put forward in recent times for the COVID-19 chest X-ray classification. Therefore, to overcome the challenges of data scarcity and lack of interpretability, also to increase the performance of COVID-19 chest X-ray classification, a first of its kind of model is proposed in which transfer learning (TL) and discriminative localisation (DL) are successfully adopted. To verify the superior classification performance of the TL-DL-based C-19CXC model, a set of experiments are conducted on widely used eight pre-trained models like MobileNet, SqueezeNet, etc., on publicly available large datasets. The MobileNet based model outcome accuracy is 98.73% followed by Xception-based framework with 98.34% accuracy.
    Keywords: COVID-19; discriminative localisation; deep learning; transfer learning; convolutional neural network; CNN.
    DOI: 10.1504/IJSGGC.2022.10050900
  • Querying and retrieving data from graphs stored in distributed architecture (QRDA)   Order a copy of this article
    by N. Mithili Devi, Sandhya Rani Kasireddy 
    Abstract: The ability to handle huge amount of data using big graphs and graph data structures plays a vital role in ever growing areas like IOT, social networking, e-commerce and bioinformatics applications. Querying graphs and extracting data in an effective manner is very crucial in big graph processing. This paper presents a framework that focuses on reassignment of vertices among partitions based on query graph so that entire query related information gets shifted to one partition to the extent possible leading to minimised query execution time. This technique first finds the partitions in which the query graph nodes are present and performs searching only in those partitions leading to minimised retrieval time. The proposed QRDA technique is compared with various state-of-art graph querying practices and the outcomes show that QRDA performance is better over other approaches.
    Keywords: big graphs; graph searching; query graph; query latency; query locality; querying; retrieval time; reassignment.
    DOI: 10.1504/IJSGGC.2022.10051740
  • Osmosis machine learning load balancing of healthcare tasks in cutting edge technologies with smart grid   Order a copy of this article
    by Basetty Mallikarjuna 
    Abstract: Smart grid communication requires an embedded approach on IoT-based cloud, fog computing and big data. In order to provide e-health and m-health services, the allocation of tasks on resources in healthcare services is crucial. The primary need for users in the healthcare industry is the solution to the bottleneck of service level agreement (SLA) and accomplishes the quality of service (QoS) parameters. The add-on objective is to achieve effective resource utilization and satisfaction of the end-user application for effective communication and load balancing of tasks on cutting edge technologies. The machine learning approach in osmosis load balancing of tasks at the end of the fog service provider (FSP) level reduces the network utilisation time, latency, usage of energy, etc. The results proves that fog nodes are efficient than the cloud nodes, and also the experimental results proved that the proposed model is efficient than the various other existing approaches.
    Keywords: smart grid; IoT-based cloud; big data; e-health; electronic health; m-health; ML approach on osmosis; fog service provider; FSP; latency; usage of energy.
    DOI: 10.1504/IJSGGC.2020.10032101