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International Journal of Cloud Computing

International Journal of Cloud Computing (IJCC)

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International Journal of Cloud Computing (18 papers in press)

Regular Issues

    by Meena Settu, Gayathri V 
    Abstract: Data security and privacy are staying one of the most significant concerns for cloud computing. The secrecy of the Personal Health Records (PHI) and Personally Identifiable Information (PII) is the main issue when financial cloud servers are utilized by healthcare associations to preserve the patients' health records since patient's information could be handled by numerous foundations for example, government and private emergency clinics and hospitals, general professionals and examination labs. Recent years, numerous intrusions on healthcare information intensified the requirement for tight security for healthcare data. Additionally, the security specialists state that such a large number of vulnerabilities are there at the Health and Humanities Service Systems Data (HHSSD). If it isn't alleviated, it could make an immense risk and potential threats to the HHSSD. So the security solutions must be expedient and simple to supplying and aiding high-level safety without compromising network performance and it is more essential to regulate critical layer of security to maintain the patients sensitive information. This paper proposes novel data encryption in healthcare cloud by applying C-R3D (Combined RSA and Triple DES) algorithm to encrypt every patient's personal health record file before moving into the cloud which ensures data confidentiality. In addition, Multimodal Biometric authentication has been connected, for example, integrated unique finger impression and iris authentication along with username and password which ensures the privacy of patients sensitive information stored in the healthcare cloud. Thus, the experimental outcomes demonstrate the effectiveness of the proposed framework
    Keywords: Data Security; Personal Health Records; Health and Humanities Service Systems Data (HHSSD); Combined RSA and Triple DES; Multimodal Biometric Authentication.

  • Intrusion Detection and Prevention of DDoS attacks in Cloud Computing Environment: A Review on Issues and Current Methods   Order a copy of this article
    by Kiruthika Devi, Subbulakshmi T 
    Abstract: Cloud computing has emerged as the most successful service model for the IT/ITES community due to the various long-term incentives offered in terms of reduced cost, availability, reliability and improved QoS to the cloud users. Most of the applications already migrated to centralized data centres in the cloud. Due to the growing needs of the business model, more small and medium enterprises rely on the cloud because little investment would suffice on the infrastructure and hardware/software. The most alarming cyber-attack in the cloud that interrupts the availability of the cloud services is Distributed Denial of Service (DDoS) attack. In this paper, various existing Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS) and their positioning in the cloud are investigated and the essence of the current techniques in the literature is briefed in detail. The comprehensive review on the latest IDS/IPS solutions and their capabilities to detect and prevent intrusions in the cloud are explored and the comparisons of the methodology provides the researchers with the security issues/challenges exposed in the cloud computing environment. The significance of the design of a secure framework for cloud is also being emphasized for achieving improved security in the cloud.
    Keywords: Cloud computing; DDoS; IDS; IPS; security.

  • A Novel redundancy Technique to enhance the security of Cloud Computing   Order a copy of this article
    by Syed Ismail 
    Abstract: Cloud Computing is an emerging technology that offers computing, storage, and software as a service to ITorganizations and individuals. The users of the cloud can access the applications provided by it from anywhere, anytime, and anyplace in the world. Security is considered as a critical issue in the cloud environment. To prevent cloud resources from external threats, data leakage, and various attacks, security controls, and technological safeguards should be offered to the datacenters of the cloud. Additionally to integrity and availability cloud should also possess reliability. Reliability enables the users to completely forget about the availability and security of the data stored in the cloud without jeopardizing data loss.This paper proposes a novel approach known as the Multi-Cloud Database(MCDB) which uses multiple Cloud Service Providers (CSP) instead of a single CSP. For this purpose, a Shamir's secret sharing algorithm and a sequential Triple Modular Redundancy(TMR) technique are implemented toimprove the reliability and offer enhanced security to the MCDB. The proposed model is compared with one single cloud(SPORC) and four multi-cloud models(DepSky, HAIL, RACS,MCDB without TMR) in terms of Reliability, Integrity, Confidentiality, Availability, and Security. The maximum Reliability, Integrity, Confidentiality, Availability, and Security values obtained for the proposed model were 100%, 99%, 99%, 97%, and 99%.
    Keywords: Cloud Computing; Reliability; Security; Multi-cloud Database; Shamir's secret sharing algorithm; and Triple Modular Redundancy.

  • EARA- PSOCA: An Energy-Aware Resource Allocation and Particle Swarm Optimization (Pso) Based Cryptographic Algorithm In E-Health Care Cloud Environment   Order a copy of this article
    by Palani Subramanian, Rameshbabu K 
    Abstract: In cloud platforms, large amount of energy is consumed by execution of scientific workflow. So, VMs has to be deployed in energy efficient manner. Throughout the world, wide attention is attracted by cloud platforms energy consumption. Cooling systems, light systems, network peripherals, monitors, console, processors cooling fan, server running consumes large amount of power in a cloud data centre. In order to face these issues, Energy-aware Resource Allocation method is proposed in this work, which is termed as EnReal. For execution of scientific workflow, virtual machines are deployed dynamically which focus Current e-health standards and solutions. In general e-health systems, client platform security is not addressed by this method which is an important factor to be considered. In e-health domain infrastructures, for privacy establishment, new Particle Swarm Optimization (PSO) with cryptography-based security algorithm (PSOCA) is proposed in this work. Controlled environment can be created by this for datas privacy easy management as well as for security. For experimentation, CloudSim framework is adapted in cloud simulation environment. Hence the Proposed method are evaluated using various parameters like energy consumption and resource utilization
    Keywords: Cloud security; cloud computing; resource allocation; cryptography; Energy-aware method.

  • An Application of Taguchi L16 Method for optimization of Load balancing Process Parameters in Cloud Computing   Order a copy of this article
    by Shahbaz Afzal, G. Kavitha, Amir Ahmad Dar 
    Abstract: Cloud computing has emerged as a large scale distributed computing platform to maintain and deliver data, information, applications, web services, IT infrastructure and other cloud services on a global scale of users over internet. With a feature of global concurrent access to users on its finite resources, scheduling of tasks is an essential process in cloud computing to assign cloud user tasks on cloud resources. Under the circumstances of varying nature of user tasks, task scheduling and resource allocation mappings are not self sufficient to keep the overall cloud system functional in a balanced state. So, task scheduling in absence of proper load balancing techniques result in workload imbalanced machines with overloaded, under-loaded or idle resources. This has negative consequences on deliverable Quality of Service and profit. Hence, prior to designing a load balancing algorithm, it is essential to determine the input parameters that have much impact on the output / response variable to prevent load imbalances among cloud computing machines. The study investigates the impact of input parameters namely growth rate, magnitude of cloud task with respect to CPU or memory, initial population of tasks, and sampling interval, on the population of tasks N(t) with the help of Taguchi Design of Experiment. Taguchi L16 method is used for experimental setup and two statistical techniques - Analysis of Mean (ANOM) and Analysis of Variance (ANOVA) are used for performance analysis. ANOM is used to identify which input parameter has a significant effect on N(t) and it also provides the best optimal combination of input variables for which the virtual machine is stable. ANOVA is used to measure the percentage contribution of each input parameter on the response variable. From the experimental results, it is concluded that N0 has the most significant impact on N(t) with a percentage contribution of 37%. The whole setup was executed on the Minitab18 statistical software toolbox.
    Keywords: Cloud computing; load balancing; scheduling; virtual machines; control parameters; Taguchi method; ANOM; ANOVA; optimal combination.

  • FSACE: Finite State Automata based client-side Encryption for Secure data Deduplication in Cloud Computing   Order a copy of this article
    by Basappa Kodada, Demian Antony D'Mello 
    Abstract: Now a day, digital data are growing vastly that are generated from different source of media in unstructured manner. The maintenance and management of this high volume of data is very critical that guides the clients to make use of cloud storage service. In reality, the communication and computation overhead will be increased to manage these data by security expectations at cloud with duplicate entries. The data deduplication technique is widely used that reduces overhead on cloud service provider. The several approaches have been proposed by researcher to address the issues of data deduplication. The convergent encryption(CE) and its flavors are widely used in secure data deduplication to reduce network bandwidth usage, storage usage and storage cost and improves storage efficiency, but CE algorithm faces dictionary based brute-force attack and threats from inner and outer adversaries. In this paper, we propose FSA based client side encryption to accomplish secure data deduplication that provides data confidentiality and integrity for users data. The FSACE protocol achieves data access control by using Proof of ownership (PoW) challenge given to data owner. The security analysis indicates that, FSACE protocol is secure enough to protect data from inner and outer adversaries.We also demonstrates performance evaluation on obtain results that shows considerably decrease in communication and computation overhead and increase in storage efficiency.
    Keywords: Security;Encryption;Cryptography;Deduplication;Secure Deduplication;Proof of ownership;Data Security;Cloud Data Security.

  • Predictive Data Center Selection Scheme for Response Time Optimization in Cloud Computing   Order a copy of this article
    by Deepak Kapgate 
    Abstract: The quality of cloud computing services is evaluated based on various performance metrics out of which response time is most important. Nearly all cloud users demands its applications response time as minimum as possible, so to minimize overall system response time we have proposed Request Response Time prediction based data center (DC) selection algorithm in this work. Proposed DC selection algorithm uses results of optimization function for DC selection formulated based on M/M/m queuing theory, as present cloud scenario roughly obeys M/M/m queuing model. In cloud environment DC selection algorithms assessed based on their performance in practice, rather than how they are supposed to be used. Hence explained DC selection algorithm with various forecasting models is evaluated for minimum user application response time and response time prediction accuracy on various job arrival rates, real parallel workload types and forecasting model training set length. Finally performance of proposed DC selection algorithm with optimal forecasting model is compared with other DC selection algorithms on various cloud configurations, considering generic cloud environment.
    Keywords: Cloud Computing; Response Time Optimization; Time Series Forecasting; M/M/m Queuing Model.

  • PSO optimized Workflow Scheduling and VM Replacement algorithm using Gaming concept in Cloud Datacenter   Order a copy of this article
    by Narayani Raman, Aisha Banu Wahab 
    Abstract: The principal features of Cloud Computing are dynamic resource allocation and its pricing nature. This paper implies an algorithm that provides resources based on the demand to users in the Cloud Infrastructure as a service (IaaS) environment. This paper proposes an algorithm that optimizes workflow scheduling and VM replacement algorithm using Particle Swarm Optimization with the gaming theory concept (GTPSO-WSP). It enhances system performance with metrics such as cost and makespan. The proposed algorithm in the Cloud Computing environment has two phases. In the first phase, resources are allocated to the physical server based on a static scheduling algorithm. During the second phase, the proposed system applies the dynamic reconfiguration based on the GTPSO-WSP algorithm for reducing the cost and makespan of the workflow. In GTPSO-WSP, the multi-start method gives a solution to particle premature convergence. However, the experimental analysis in the WorkflowSim environment improves the makespan and monitory cost. The observed results indicate performance improvement of 4% in terms of makespan and 9% in terms of cost while comparing GTPSO-WSP with the traditional Particle Swarm Optimization (PSO) and Cuckoo Search algorithm.
    Keywords: Algorithm; Cloud Computing; Game Theory; Makespan; Optimization; Placement; physical server; Resource Allocation; Scheduling; Workflow.

  • A Novel Hybrid Algorithm for Workflow Scheduling in Cloud   Order a copy of this article
    by Isha Agarwal, Swati Gupta, Ravi S. Singh 
    Abstract: Cloud Computing is a service that provides its users all the computing facilities which can be accessed anywhere, at any time through the internet on a pay-per-use basis. There is a huge number of Cloud service providers receiving a large number of requests from multiple users around the world, scheduling plays a vital role in assigning those requests to it's requested resources. Task Scheduling is an NP-Hard problem in Cloud Environment due to which many heuristics and meta heuristics algorithms have been used for obtaining an optimised mapping. In this paper, we designed a Hybrid Jaya-Particle Swarm Optimization(PSO) algorithm. The proposed algorithm combines both the Jaya and PSO to provide us better quality results. Our algorithm is evaluated in terms of execution cost and execution time and achieved better results in comparison with Genetic Algorithm(GA), PSO, Honey Bee, Cat Swarm Optimization(CSO), Ant Colony Optimization(ACO) and Jaya.
    Keywords: Task Scheduling; cloud computing; workflow scheduling; Jaya; PSO; execution cost; running time.
    DOI: 10.1504/IJCC.2023.10038837
  • Automation of Franchise Based Data Storage, Management and Analysis Using Amazon Web Services(AWS)   Order a copy of this article
    by Shreya Oswal 
    Abstract: The wave of computer automation in business has revolutionized the way companies and employees interact with their customers and each other. Robotic Process Automation (RPA) not only mimics human actions involving complex, high volume, and routine tasks but has also extended the creative problem-solving capabilities and productivity of human beings and deliver superior business results. Amazon Web Services (AWS) has created a dramatic cultural shift in Infrastructure Provisioning from a fairly manual process of physical machines and software configuration. This paper proposes to use Amazon AWS to automate the task of scheduled uploading of data from different franchises, managing the database, analyzing the data and storing the data on the supervisors machine. This reduces the redundant tasks of daily uploading data to company servers, analyzing the data and then downloading the data. The Analysed data can be used by the company to improve the basic functioning and acknowledge various issues and problems. Thus it aims to offer Infrastructure as a Service (IaaS) by providing virtualized computing resources over the internet.
    Keywords: Amazon Web Services(AWS); AWS S3; AWS Lambda; DynamoDB; Robotic Process Automation (RPA).

  • KBSS: An Efficient Approach of Extracting Text Contents from Lecture Videos - Computational Intelligence Techniques   Order a copy of this article
    by Sreerama Murthy Velaga 
    Abstract: For the last few decades, there is a lot of research going on in the areas of image processing and text mining, and they became an emerging research area because an image or a video with cloud is a major source of data, whereas text is a prominent and direct source of information in a video lecture. The challenges that usually faced are converting the lecture video frames into binary conversion matrix, extracting image to text matrix, Defining the threshold value and classification. Here, in this paper an efficient approach for extracting text contents from Meta data lecture videos with cloud is proposed. We built a frame work KBSS in which the frames are converted into binary matrix, then extracting key factors with text matrix, then apply clustering with proposed similarity measures in-order to reduce the matrix and classification of text matrix using neural networks and checking proposed similarity measure with properties of each case wise. The objective is to extract text from Meta lecture videos with cloud and improving algorithm performance.
    Keywords: Lecture meta video; computational intelligence techniques; binary matrix; key factors; text and image mining.

    by Sawsan Alshattnawi, Anas Alsobeh 
    Abstract: Jordan is one of the poorest countries in water resources, estimated to be below the poverty line. Due to high population growth and development, water supply and demand needs a novel distribution water regime in Jordan. This paper presents a design-based Smart Water Distribution Model (SWDM), which integrates various technology solutions, such as Behavior-Interaction-Priority (BIP) components, Cloud computing, and the Internet of Things (IoT). BIP is a component model of design that includes - three aspects: behavior, interaction, and priority. IoT is a design for connected system components that collect data from physical devices to deliver executable insights. This paper proposes a BIP-IoT model to introduce the SWDM, which provides a dynamic smart-design scalable model that is implemented over cloud components to cope with the increasing challenges of the water distribution regime in Jordan. The paper analyzes the viability of this model and investigates an advantage in the reusable automation dynamic of SWDMs architecture. A composition component is integrated into the architecture that employs intelligence domain-independent planning to control execution. It also presents a high-level prototype cloud-based implementation of our proposed architectural model using smart artificial data analysis algorithms.
    Keywords: BIP Component Model; Cloud Computing; Internet of Things (IoT); Water Distribution Network; Wireless Sensor Network (WSN); Smart Water Distribution Management Model.

  • Data consistency protocol for multicloud systems   Order a copy of this article
    by Olga Kozina, Volodymyr Panchenko, Oleksii Kolomiitsev, Nataliia Stratiienko, Viktoriya Usik, Lyudmila Safoshkina, Yurii Kucherenko 
    Abstract: Using the resources of several cloud service providers (CSPs) to store, serve, and access users data can improve availability and reduce latency. However, the management of multicloud systems also poses an important challenge of how to guarantee that requests from any region to geo-distributed replicas of the database will content equivalent actual data, which is considered in this paper. The existing taxonomy of data consistency models allows to choose the required level of data consistency in cloud systems, however, the implementation of consistency protocols for multicloud systems requires a reasonable choice of middleware architecture and compromise decisions between response time and other constraints required by clients requirements. We propose consistency protocol based on the geo-distributed architecture of multicloud middleware to assign the ordering of numbers in a global sequence for incoming writing.
    Keywords: Data consistency; consistency protocol; consistency model; multi clouds; cloud service providers; multicloud systems; latency; geo-distributed database; response time; middleware architecture.

  • A distributed auction-based algorithm for virtual machine placement in multiplayer cloud gaming infrastructures   Order a copy of this article
    by Yassine Boujelben, Hasna Fourati 
    Abstract: Cloud gaming is an emerging service model that basically mimics the cloud computing model. Indeed, intensive computing tasks incurred by the graphical processing of the fairly complex game scenes are exported to remote cloud servers. While this would alleviate the hardware and software requirements on the gaming terminals, it poses serious problems of quality of service and experience. Furthermore, as the massive multiplayer gaming model becomes increasingly popular, computing resources are likely spread across multiple data centers and the need for a distributed assignment algorithm becomes paramount. In this paper, we are interested in the assignment of virtual machines hosted on rendering servers in a distributed cloud gaming infrastructure to requests sent by online gamers. We use the auction algorithm along with several efficient extensions to solve the virtual machine placement problem. We propose a completely distributed implementation technique without any shared memory for our algorithm called DVMP.
    Keywords: multiplayer cloud gaming; MCG; virtual machine placement; VMP; matchmaking; distributed auction algorithm; distributed VMP; gaming experience.
    DOI: 10.1504/IJCC.2024.10048138
  • Hybrelastic: A Hybrid Elasticity Strategy with Dynamic Thresholds for Microservice-based Cloud Applications   Order a copy of this article
    by Jose Augusto Accorsi, Rodrigo Da Rosa Righi, Vinicius F. Rodrigues, Cristiano André Costa, Dhananjay Singh 
    Abstract: Microservices-based architectures aim to divide the application’s functionality into small services so that each one of them can be scaled, managed, implemented, and updated individually. Currently, more and more microservices are used in application modelling, making them compatible with resource elasticity. In the literature, solutions employ elasticity to improve application performance; however, most of them are based on CPU utilisation metrics and only on reactive elasticity. In this context, this article proposes the hybrelastic model, which combines reactive and proactive elasticity with dynamically calculated thresholds for CPU and network metrics. The article presents three contributions in the context of microservices: 1) combination of two elasticity policies; 2) use of more than one elasticity evaluation metric; 3) use of dynamic thresholds to trigger elasticity. Experiments with hybrelastic demonstrate 10.31% higher performance and 20.28% lower cost compared to other executions without hybrelastic.
    Keywords: elasticity; reactive elasticity; proactive elasticity; scalability; dynamic thresholds; microservices.
    DOI: 10.1504/IJCC.2024.10048365
  • Amazon EC2 Spot Price Prediction Using LSTM Time Series Prediction Model   Order a copy of this article
    by Veena Khandelwal, Shantanu Khandelwal 
    Abstract: Amazon EC2 spot instances provide access to unused Amazon EC2 capacity at high discounts relative to on-demand and reserved prices. Spot prices fluctuate based on the demand and supply of available unused capacity of EC2. When users request spot instances, they specify the maximum spot price they are willing to pay. Optimum maximum spot price estimation is crucial to control costs and have uninterrupted access to spot instances. We analyse spot price fluctuations for any seasonal or residual component and present a stacked LSTM-based prediction model based on the deep learning RNN model. In order to analyse Amazon spot pricing, we use time-smoothed spot prices at frequency of one hour. Our experiments with the new Amazon EC2 spot pricing model show that the LSTM model predicts future spot prices with different lead times with very low RMSE values.
    Keywords: Amazon EC2; compute instances; new spot pricing model; spot price prediction; long short-term memory; LSTM.
    DOI: 10.1504/IJCC.2024.10049932
  • Integration of Cloud Based Scheme with Industrial Wireless Sensor Network for Data Publishing in Privacy of Point Source   Order a copy of this article
    Abstract: Wireless sensor networks (WSNs) are normally conveyed in arbitrary regions with no security. The source area uncovers significant data about targets. In this paper, a plan dependent on the cloud utilising data publishing in privacy of point source is proposed to resolve the issue of source area security. Then, at that point, a cloud-moulded phony area of interest is made to add counterfeit parcels into the WSN to confound the enemy and give a far-reaching protection area. Every important parcel is steered through a way that is very hard for the area of interest finding enemy to discover straightforwardly. Recreation results represent that the plan can forestall antagonistic catch and keep a significant degree of security insurance simultaneously. The energy utilisation in this plan applies restricted impact on the organisation lifetime contrasted and a cloud-based plan and an all-course irregular steering calculation conspire.
    Keywords: wireless sensor networks; WSNs; privacy of point source; security; technology; research; cloud computing.
    DOI: 10.1504/IJCC.2024.10051526
  • A Comparative Study of Collision Avoidance Medium Access Control Protocols in Internet-of-Things   Order a copy of this article
    by Sachin Kumar, Pawan Kumar Verma 
    Abstract: In wireless communications, different collision avoidance medium access control (MAC) protocols are available to avoid contention, but none of them are accepted as standard protocols to fulfil the requirements of the internet of things (IoT). So there is a need for well-defined MAC protocols to optimise the channel access mechanism. Therefore, this paper presents the fundamentals of IoT, types of collisions, features of IoT-based communication technologies, and a comparative study of collision avoidance MAC protocols in IoT. This paper first outlines the system model of IoT networks based on a comprehensive study of the reported literature. Following that, types of collisions are discussed. Further, we have provided a comprehensive study of ALOHA, CSMA, CSMA/CA, and hybrid MAC protocols, issues in MAC protocols, and their state-of-the-art solutions to avoid collisions and to provide higher throughput. Finally, future research direction for IoT has been highlighted to underline potential real-time IoT applications.
    Keywords: internet of things; IoT; machine to machine; M2M; MAC protocols; ALOHA; CSMA/CA; quality-of-service; QoS.
    DOI: 10.1504/IJCC.2024.10051835