Faculty Publications
Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736
Publications by NITK Faculty
Browse
9 results
Search Results
Item A review on mobile cloud computing interoperability issues and challenges(Springer, 2020) Debbarma, T.; Chandrasekaran, K.Mobile cloud computing (MCC) is the convergence of two recent technologies namely “Cloud Computing” and “Mobile Computing” with wireless networks as a communication backbone. There are mainly three paradigms that use the concepts of MCC, viz. edge computing, fog computing and cloudlets. Due to the presence of various heterogeneous hardware and software platforms in MCC, there are many interoperability issues which create vendor/services lock-in problems, it also makes data and application portability difficult. This paper studies the different paradigms of MCC and the challenges in making them interoperable in heterogeneous hardware and software platforms. We have summarized some of the MCC-based research papers and their findings. Contribution of this paper is the summary of challenges and research scopes in the field of MCC where it needs to be addressed to mitigate the interoperability issues. © Springer Nature Singapore Pte Ltd. 2020.Item Interoperability based resource management in cloud computing by adaptive dimensional search(Institute of Electrical and Electronics Engineers Inc., 2017) Anithakumari, S.; Chandrasekaran, K.The concept of cloud computing is introduced as a new computing technology based on different computing techniques such as virtualization, which implements applications on virtual machines procreated on physical machines. The deployment of cloud computing can be of different types based on the implementation of service model and the availability of cloud services to the end users. One of the challenges need to be faced by cloud computing is related to the data interoperability and portability. Here we have established a mechanism for flexible resource allocation between the cloud service providers based on SLA mapping and clustering techniques to propose an interoperable cloud computing environment. This interoperabilityis made possible with the use of multiple techniques such as Adaptive Dimensional Search Algorithm (ADS), Clustering and SLA mapping. © 2017 IEEE.Item An effective analysis on intrusion detection systems in wireless mesh networks(Institute of Electrical and Electronics Engineers Inc., 2017) Karri, K.G.; Raju, V.P.; Santhi Thilagam, P.S.Intrusion Detection Systems(IDSs) are widely used to detect both known attacks and unknown attacks performed by internal and external attackers in wireless networks. However, challenging issues for developing IDSs inWireless Mesh Networks (WMNs) are 1) supporting interoperability and 2) handling volatile parameters. In addition, security standards for WMN are still in draft stage, and to protect the WMN, IDSs of similar wireless networks such as wireless sensor, Ad-Hoc, MANET can be adopted, but the best performance is not guaranteed. In this paper, we have classified the existing IDSs for wireless networks into four categories namely single layer IDS, cross-layer IDS, reputation-based IDS, reputation based cross-layer IDS, and analyzed the performance of these IDSs with core-layer attacks and detection methodology. Based on our analysis, we address the loopholes in existing IDSs and specify research directions for strengthening the existing IDSs and for developing new efficient IDSs with respect to backbone mesh and client mesh networks. © 2017 IEEE.Item Adaptive resource allocation in interoperable cloud services(Springer Verlag, 2019) Anithakumari, S.; Chandrasekaran, K.Interoperable cloud computing is the one in which the services or resources of one cloud can be accessed by another cloud. The implementation of interoperable cloud architecture is a challenging one because various characteristics of the cloud computing environment need to be considered for its achievement. The aim of this work is to implement interoperable cloud computing with the awareness of service-level agreements and to provide adequate resources when shortage of resources occurs at one cloud while providing the agreed services to the user. To achieve this, we proposed a methodology of interoperability-based flexible resource management. Initially, the SLA templates of private and public cloud are mapped using the Soft TF-IDF metric with case-based reasoning (CBR) approach. Then, based on the mapped SLAs, different clusters of cloud providers are formed with the help of K-means clustering technique. And finally, if one of the cloud in a cluster faces the problem of resource shortage, the flexible resource allocation is provided through the adaptive dimensional search algorithm. © Springer Nature Singapore Pte Ltd. 2019.Item Middleware Frameworks for Mobile Cloud Computing, Internet of Things and Cloud of Things: A Review(Springer, 2020) Debbarma, T.; Chandrasekaran, K.Mobile cloud computing (MCC) is an extension of cloud computing (CC) technologies. It provides seamless access of different cloud services to smart mobile devices (SMDs). There is no denying that CC can be scaled to a great extent in terms of computing, storage and other services, but the SMDs used for accessing those services are limited on battery capacity, storage and computing power due to their small form factors. The limitations of SMDs can be minimised/resolved by using MCC platforms. Though MCC is advantageous in many ways, it has its own inherent challenges and issues due to the heterogeneous hardware and software platforms used by SMDs and CC platforms, which makes it difficult to have interoperable services and the development of applications for those devices. This paper studied recently (from 2012 onwards) proposed/developed middlewares for the Internet of things (IoT), cloud of things (CoT), context-aware middlewares (CaMs) and mobile cloud middlewares (MCMs). Different middleware architectures are chosen, as in many cases, these technologies converge in terms of features, functions and services they provide. The study finds that the present middlewares lack in providing an integrated solution that complies with interoperability, portability, adaptability, context awareness, security and privacy, service discovery, fault tolerance requirements. At the end of the paper, the challenges pertaining to achieve portability, interoperability, context awareness, security are discussed and identify the gaps in the existing approaches in MCC interoperability and context adaptability. © 2020, Springer Nature Singapore Pte Ltd.Item Media Independent Handover and Mobile IPv6-Based UDP Performance Evaluation Suite for Heterogeneous Wireless Networks(Springer, 2023) Chandavarkar, B.R.Simulation is a cost-effective, simple, and straightforward approach to implementing a system for exhaustive analysis. Many commercial and open-source simulators, such as NS2, NS3, OMNET++, OPNET, QualNet, etc., exist in the literature to simulate wired and wireless networks. However, the major challenge in dealing with open-source simulators is analysing the results and presenting their performance metrics. Further, the ever-increasing demands of the users in terms of higher data rates with uninterrupted connections resulted in a heterogeneous wireless network (HWN) that supports the integration of WiFi, WiMAX, LTE, etc. Amongst all network simulators available in the literature, NS2 and NS3 are the most popularly used by the research community because of their immense support for implementing and verifying innovative networking algorithms. Furthermore, with the contribution of the National Institute of Science and Technology (NIST), NS2 supports the simulation of WiFi and WiMAX heterogeneous wireless networks with Media Independent Handover and Mobile-IPv6 which is yet to be supported entirely by NS3. However, the major shortcoming of NIST’s contribution is the ease of developing a simulation script followed by result analysis. In continuation with the NIST’s contribution, this paper proposes a Graphical User Interface-based evaluation suite (ES) for the simulation of User Datagram Protocol applications’ in HWN, referred to as ES-HWN. With the support of this suite, the research community can quickly develop the heterogeneous wireless network simulation script followed by the textual and graphical results of handover, packets sent and received, throughput, packet delay, and jitter. The proposed ES-HWN supports the configuration of 10 WiFi and WiMAX interface mobile nodes with two WiFi-Access Points and a WiMAX-Base Station. Besides, it supports the configuration of UDP-based applications’ packet size and transmission rate. Finally, over many experiments, ES-HWN exhibited 100% reliable results. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.Item Integration of Synergetic IoT Applications with Heterogeneous Format Data for Interoperability Using IBM ACE(Springer, 2024) Sandeep, M.; Chandavarkar, B.R.Data interoperability is a crucial requirement in IoT to improve services and enhance business opportunities and innovation. Integrating synergetic applications with heterogeneous data formats is a critical issue that needs to be addressed to achieve interoperability. The use cases indicate IBM ACE is promising in resolving integration issues among on-premises and cloud applications. Further, many efforts are observed to address the interoperability issue apart from the IBM ACE approach. However, they are complex, restricted to few data formats, and use proprietary solutions. To address these above-mentioned issues, this paper proposes the Integration of Synergetic IoT applications with Heterogeneous format data for Interoperability using IBM ACE (ISHII). Further, an intelligence-based data recognition module in the proposed ISHII is trained with standard features defined in RFC 7111, 8259, 8996, JSON-LD of W3C, and Google’s Protobuf. Subsequently, recognized heterogeneous format data are integrated and translated to interoperable format using Data Format Description Language (DFDL) with Extended SQL codes on IBM ACE. Finally, the performance of ISHII has been evaluated with synthetically generated patient monitoring and room ambiance datasets with reference to accuracy, time required for integration, and translation efficiency. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.Item Heterogeneous data format integration and conversion (HDFIC) using machine learning and IBM-DFDL for IoT(Springer Nature, 2024) Sandeep, S.; Chandavarkar, B.R.; Khatri, S.The future of the Internet of Things (IoT) demands the integration of synergetic applications to cater to societal needs. Examples of IoT-based confederated applications include Ambient Assisted Living with Active Healthy Ageing, CasAware with Smart Energy, Smart Gas Distribution Networks with GIS systems, and more. However, the data heterogeneity hinders integration, as these systems follow different standards, data formats, semantic models, and representations. Further, this leads to data interoperability issues in IoT. The major concern of academia and industry in the smooth integration of heterogeneous applications is interpreting different data formats and representing them in a common schema for further analysis. Existing solutions, such as message payload translation, middleware/cloud format, and Inter-IoT, are complex, time-consuming, and ineffective. Hence, this paper proposes the heterogeneous data format integration and conversion (HDFIC), a machine learning-based system to identify data formats using a Random Forest classifier and integrate them using the Data Format Description Language (DFDL). The content-based data format identification in the proposed HDFIC is trained with the standard features defined in RFC 7111, 8259, and 8996. Subsequently, the data is integrated into a single XML Schema Definition and converted into the required data format using the IBM App Connect Enterprise tool and DFDL. Finally, the performance of HDFIC is evaluated with the synergetic patient body vitals and room ambiance dataset for accuracy, data integration time, and conversion efficiency. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.Item AN ONTOLOGY-DRIVEN BI-DIRECTIONAL WORKFLOW FOR INTEGRATING PROJECT MANAGEMENT DATA INTO THE IFC STANDARD(International Council for Research and Innovation in Building and Construction, 2025) Kone, V.; Mahesh, G.The evolution of Building Information Modelling (BIM) towards a data-centric paradigm is often hindered by challenges in semantic interoperability, particularly when integrating project management data with the Industry Foundation Classes (IFC) standard. While IFC enables syntactic data exchange, a persistent gap exists dynamically linking building geometry with the complex, relational information of project schedules, resources, and costs in a semantically consistent, interoperable manner. This paper presents a novel, bi-directional methodology that leverages Semantic Web technologies (RDF, OWL, SPARQL) to address this challenge. The core of the methodology is an ontology-driven workflow that uses two purpose-built ontologies: BIMOnto, a lightweight representation of the building asset derived from if cOWL, and IproK (Integrated Project Knowledge Ontology), which formally structures project management information across schedule, resource, and cost domains. The workflow enables both directions: (1) transforming IFC models into queryable knowledge graphs, and (2) programmatically generating new, enriched IFC models from unified knowledge graphs. This reverse transformation creates native, standards-compliant IFC entities for tasks (IfcTask), resources (IfcResource), costs (IfcCostItem), and their standard relationships (IfcRelAssignsToProduct, etc.), moving beyond custom property sets. The feasibility and effectiveness of this approach are validated through a case study using a multi-story residential building model, demonstrating the successful generation of a verifiable, integrated BIM artifact. The findings show that this ontology-driven framework significantly enhances data integration, creating truly interoperable models where process data becomes a first-class citizen within the BIM environment, advancing the potential for more intelligent, data-centric BIM practices throughout the project lifecycle. © © 2025 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.