Faculty Publications

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Subject: search.filters.subject.Analytic hierarchy process

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    Dynamic partner selection in Cloud Federation for ensuring the quality of service for cloud consumers
    (World Scientific Publishing Co. Pte Ltd wspc@wspc.com.sg, 2017) Thomas, M.V.; Chandrasekaran, K.
    Cloud Computing has become the popular paradigm for accessing the various scalable and on-demand computing services over the internet. Nowadays, individual Cloud Service Providers (CSPs) offering specialized services to the customers collaborate to form the Cloud Federation, in order to reap the real benefits of Cloud Computing. By collaboration, the member CSPs of the federation achieve better resource utilization and Quality of Service (QoS), thereby increasing their business prospects. When a CSP runs out of resources in the Cloud Federation, in order to offload the customer requests for resources to other CSP(s), identifying a suitable partner is a challenging task due to the lack of global coordination among them. In this paper, we propose the design and implementation of an efficient partner selection mechanism in the Cloud Federation, using the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods, and also considering the trust values of various CSPs in the federation. The AHP method is used to calculate the weights of the QoS parameters used in the TOPSIS method which is used to rank the various CSPs in the Cloud Federation according to the user requirements. Simulation results show the effectiveness of this approach in order to efficiently select the trustworthy partners in large scale federations to ensure the required QoS to the cloud consumers. © 2017 World Scientific Publishing Company.
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    Dynamic analysis and optimization of SiC reinforced Al6082 and Al7075 MMCs
    (Institute of Physics Publishing helen.craven@iop.org, 2019) Allien, V.J.; Kumar, H.; Desai, V.
    Composites play a vital role in engineering applications. The main aim of this study was to analyse how addition of SiC will improve the damping properties of metal matrix composites (MMCs). The strengthening of composites depends on physical, mechanical and dynamic factors. In the present study, Al6082 and Al7075 aluminum alloy reinforced with (0, 1, 2, 3, 4, 5, 7.5, 10, 15 and 20) different weight percentages of silicon carbide particles (SiCp) MMCs have been fabricated through stir casting method. The microstructure, density, hardness, tensile strength, impact strength, natural frequencies and damping ratio of the MMCs were determined. The mechanical tests and free vibration analysis results revealed that the addition of SiCp reinforcement enhanced the strength and stiffness of the aluminum alloy MMCs. Multi-attribute decision making (MADM) techniques like analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) methods were applied for determining the best fabricated MMCs. Based on MADM techniques, 15% SiC/Al7075 composite was selected as the best material and using response surface methodology (RSM) 13.66% SiC/Al7075 composite was found as the optimal composite material. © 2019 IOP Publishing Ltd.
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    Assessing forest health using remote sensing-based indicators and fuzzy analytic hierarchy process in Valmiki Tiger Reserve, India
    (Institute for Ionics, 2023) Roshani; Sajjad, H.; Rahaman, M.H.; Rehman, S.; Masroor, M.; Ahmed, R.
    Anthropogenic activities, climate variability and environmental stresses have greatly affected forest ecosystems globally. Thus, monitoring of forest health is essential for proper planning and effective management. The present study employed an integrated approach of remote sensing and fuzzy analytic hierarchy process to assess the forest health in the Valmiki Tiger Reserve in India. Advanced vegetation index, normalized difference vegetation index, normalized difference moisture index, forest fragmentation, rainfall and soil types were derived from remote sensing data. Multiple buffer zones of villages, roads, railways and canals were also determined for analyzing the forest health status. These layers were prepared in the geographical information system. These layers were given weightage using fuzzy analytic hierarchy process. These layers were integrated to prepare forest health map using weighted overlay method. The results revealed that the largest forest area was found under moderately healthy forest (37%) followed by healthy forest (31%) and unhealthy forest (13%). Of the total area of the Reserve, 19% area was under non-forest category. Human-induced disturbances such as encroachment, illegal sand mining, livestock grazing and forest conversion to agriculture have been attributed to the unhealthy forest in the Reserve. The receiver operating characteristic curve value and area under curve (0.792) show reliability of forest health map. The findings of this study may be helpful for forest managers, conservationists and local communities in devising sustainable strategies for effective management of the forest. The methodological framework adopted in this study may be utilized in other geographical regions interested in assessing forest health. © 2022, The Author(s) under exclusive licence to Iranian Society of Environmentalists (IRSEN) and Science and Research Branch, Islamic Azad University.
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    An approach to quantify the contamination potential of hazardous waste landfill leachate using the leachate pollution index
    (Institute for Ionics, 2024) Ambujan, A.; Thalla, A.K.
    A significant portion of the hazardous wastes generated by rapid industrialisation and urbanisation end up in landfills. The wastes disposed of in hazardous waste landfills are less biodegradable; thus, the leachate generated due to the physical and chemical changes in the landfill renders high toxicity. If not monitored and handled appropriately, this leachate could lead to contamination affecting human and livestock health and adversely affect the soil and agriculture in the vicinity of the landfill site. A tool to quantify the contamination caused by improper handling of hazardous waste landfill leachate is essential to understand which landfill site would need immediate attention. In the present study, the leachate pollution index is developed based on the predominantly available pollutants in hazardous waste landfill leachate and their toxicity limits. Fuzzy Delphi-Analytic Hierarchy Process has been used to develop the index. These techniques have been used for screening and assigning weights to the pollutants. Further, sub-index curves have been developed considering the available concentration, the toxicity, and the standard concentration limits for each pollutant. The weighted linear sum function has been used to aggregate the weights and sub-index scores. The hazardous waste landfill leachate pollution index developed in this study can serve as a potential tool for quantifying the leachate contamination potential. Furthermore, it can be used as a comparison tool for ranking landfill sites based on the contamination potential. © 2023, The Author(s) under exclusive licence to Iranian Society of Environmentalists (IRSEN) and Science and Research Branch, Islamic Azad University.
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    Identification of challenges to Industry 5.0 adoption in Indian manufacturing firms: an emerging economy perspective
    (Taylor and Francis Ltd., 2025) Sahoo, P.; Saraf, P.K.; Uchil, R.
    This study aims to identify a comprehensive list of challenges and empirically evaluate their impact on Industry 5.0 adoption, particularly in developing countries in Indian manufacturing firms. Challenges were classified into four significant categories: human, environmental, legal and ethical, and financial through an extensive literature review conducted and experts’ inputs. Multi-criteria decision-making (MCDM) is a method for analyzing complex issues by assessing multiple alternatives based on specific criteria. The analytic hierarchy Process (AHP) aids in selecting suitable options, while the analytical network processes (ANP) technique determines relevant criteria. A sensitivity analysis was carried out to validate the research findings. The most preeminent challenges were identified as human critical thinking, human-machine teams, incorporation of ethics, investment in Industry 5.0 technologies, human well-being perspective, over-dependency on technology, and personalization and hyper-customization 5.0, respectively, in the adoption of Industry 5.0. The comprehensive challenges proposed in the study will assist decision-makers, practitioners, and managers in determining fair benchmarking strategies to precipitate Industry 5.0. This research helps to gauge manufacturing firms’ readiness index to adopt Industry 5.0, provides a distinct perspective, and foregrounds the significance of research to assist the industry in its long-term to anticipate Production 6.0. © 2024 Informa UK Limited, trading as Taylor & Francis Group.