Computing Service Providers Research Articles

The Challenges of Institutional Distance: Data Privacy Issues in Cloud Computing

Data protection and data privacy are significant challenges in cloud computing for multinational corporations. There are no standard laws to protect data across borders. The institutional and regulatory constraints and governance differ across countries. This article explores the challenges of institutional constraints faced by cloud computing service providers in regard to data privacy issues across borders. Through a qualitative case study methodology, this research compares the institutional structure of a few host countries, with regard to data privacy in cloud computing and delineates a relative case study. This article will also review the cloud computing legal frameworks and the history of cloud computing to make the concept more comprehensible to a layman.

Resource Sharing of a Computing Access Point for Multi-User Mobile Cloud Offloading with Delay Constraints

We consider a mobile cloud computing system with multiple users, a remote cloud server, and a computing access point (CAP). The CAP serves both as the network access gateway and a computation service provider to the mobile users. It can either process the received tasks from mobile users or offload them to the cloud. We jointly optimize the offloading decisions of all users, together with the allocation of computation and communication resources, to minimize the overall cost of energy consumption, computation, and maximum delay among users. The joint optimization problem is formulated as a mixed-integer program. We show that the problem can be reformulated and transformed into a non-convex quadratically constrained quadratic program, which is NP-hard in general. We then propose an efficient solution to this problem by semidefinite relaxation and a novel randomization mapping method. Furthermore, when there is a strict delay constraint for processing each user's task, we further propose a three-step algorithm to guarantee the feasibility and local optimality of the obtained solution. Our simulation results show that the proposed solutions give nearly optimal performance under a wide range of parameter settings, and the addition of a CAP can significantly reduce the cost of multi-user task offloading compared with conventional mobile cloud computing where only the remote cloud server is available.

Resource allocation and routing in parallel multi-server queues with abandonments for cloud profit maximization

This paper considers a Markov decision model for profit maximization of a cloud computing service provider catering to customers submitting jobs with firm real-time random deadlines. Customers are charged on a per-job basis, receiving a full refund if deadlines are missed. The service provider leases computing resources from an infrastructure provider in a two-tier scheme: long-term leasing of basic infrastructure, consisting of heterogeneous parallel service nodes, each modeled as a multi-server queue, and short-term leasing of external servers. Given the intractability of computing an optimal dynamic resource allocation and job routing policy, maximizing the long-run average profit rate, the paper addresses the design, implementation and testing of low-complexity heuristics. The policies considered are a static policy given by an optimal Bernoulli splitting, and three dynamic index policies based on different index definitions: individually optimal (IO), policy improvement (PI) and restless bandit (RB) indices. The paper shows how to implement efficiently each such policy, and presents a comprehensive empirical comparison, drawing qualitative insights on their strengths and weaknesses, and benchmarking their performance in an extensive study.

Analysis Of Maturity Level Cloud Computing Service Provider Using COBIT 4.1

This research is focused on the analysis of cloud computing service provision by both division IT Project and IT Support Division at PT. Eikon Technology in Surabaya to improve business process in this company, by examining the extent of cloud services provided by the company to customers through the two divisions by applying information technology. The total detailed control objective used was 38 detail controls performed by the IT Project division and 40 control details performed by the IT Support division. The result of this research is analysis of current and expected maturity level from sub domain PO4, PO7, DS1, DS5, and DS7, got the average total maturity level is 2.7 and the expected maturity level is 3.76. Recommendations and conclusions are expected to develop the process of information technology governance in the form of providing cloud computing services to better and efficient in supporting the business in PT Eikon Technology, Surabaya

Designing Software as a Service in Cloud Computing Using Quality Function Deployment

Cloud computing is an approach to access the virtualized resources based on an integrated system. Flexibility, scalability, high accessibility, and cost-effectiveness are some features of this system. These advantages have caused a favorable reception of different cloud computing services, such as software as a service (SAAS), platform as a service (PAAS), and infrastructure as a service (IAAS) on the part of businesses. In this article, a model for SAAS services has been proposed as one of the cloud computing layers with the maximum adjustment between the dimensions and components of QFD-based customer requirements. QFD is a method that seeks to translate the customer's voice into the technical design requirement. For this purpose, the dimensions and components of customer requirements and the dimensions and components of designing were determined through the review of literature and consulting with the experts. Finally, the dimensions and components of final desirable outcome were determined for SAAS by stages to achieve a modified QFD. After the examination of dimensions and components, a comparison was made between the companies and finally the most effective customer needs and the target values were determined. Thus, an SAAS service was designed. The telecommunications and cloud computing service provider companies can satisfy the customers and achieve a competitive advantage in designing SAAS services using the results of this research.

Multi-User Multi-Task Offloading and Resource Allocation in Mobile Cloud Systems

We consider a general multi-user Mobile Cloud Computing (MCC) system where each mobile user has multiple independent tasks. These mobile users share the computation and communication resources while offloading tasks to the cloud. We study both the conventional MCC where tasks are offloaded to the cloud through a wireless access point, and MCC with a computing access point (CAP), where the CAP serves both as the network access gateway and a computation service provider to the mobile users. We aim to jointly optimize the offloading decisions of all users as well as the allocation of computation and communication resources, to minimize the overall cost of energy, computation, and delay for all users. The optimization problem is formulated as a non-convex quadratically constrained quadratic program, which is NP-hard in general. For the case without a CAP, an efficient approximate solution named MUMTO is proposed by using separable semidefinite relaxation (SDR), followed by recovery of the binary offloading decision and optimal allocation of the communication resource. To solve the more complicated problem with a CAP, we further propose an efficient three-step algorithm named MUMTO-C comprising of generalized MUMTO SDR with CAP, alternating optimization, and sequential tuning, which always computes a locally optimal solution. For performance benchmarking, we further present numerical lower bounds of the minimum system cost with and without the CAP. By comparison with this lower bound, our simulation results show that the proposed solutions for both scenarios give nearly optimal performance under various parameter settings, and the resultant efficient utilization of a CAP can bring substantial cost benefit.

Edge-of-things computing framework for cost-effective provisioning of healthcare data

Edge-of-Things (EoT)-based healthcare services are forthcoming patient-care amenities related to autonomic and persuasive healthcare, where an EoT broker usually works as a middleman between the Healthcare Service Consumers (HSC) and Computing Service Providers (CSP). The computing service providers are the edge computing service providers (ECSP) and cloud computing service provider (CCSP). Sensor observations from a patient’s body area networks (BAN) and patients’ medical and genetic historical data are very sensitive and have a high degree of interdependency. It follows that EoT based patient monitoring systems or applications are tightly coupled and require obstinate synchronization. Therefore, this paper proposes a portfolio optimization solution for the selection of virtual machines (VMs) of edge and/or cloud computing service providers. The dynamic pricing for an EoT computation service is considered by the EoT broker for optimal VM provisioning in an EoT environment. The proposed portfolio optimization solution is compared with the traditional certainty equivalent approach. As the portfolio optimization is a centralized solution approach, this paper also proposes an alternating direction method of multipliers (ADMM) based distributed provisioning method for the healthcare data in the EoT computing environment. A comparative study shows the cost-effective provisioning for the healthcare data through portfolio optimization and ADMM methods over the traditional certainty equivalent and greedy approach, respectively.

Cloud Service Providers Under the NIS Directive The UK's Implementation (With GDPR Comparisons)

This article analyses how the UK implemented the EU Network and Information Systems Security Directive, focusing on its impact on cloud computing service providers. It highlights some UK divergences, whether through policy choice or error, noting issues with the consultation process. It also compares security and notification obligations on cloud providers under the Directive and the EU General Data Protection Regulation.

Opportunistic Task Scheduling over Co-Located Clouds in Mobile Environment

With the growing popularity of mobile devices, a new type of peer-to-peer communication mode for mobile cloud computing has been introduced. By applying a variety of short-range wireless communication technologies to establish connections with nearby mobile devices, we can construct a mobile cloudlet in which each mobile device can either works as a computing service provider or a service requester. Although the paradigm of mobile cloudlet is cost-efficient in handling computation-intensive tasks, the understanding of its corresponding service mode from a theoretic perspective is still in its infancy. In this paper, we first propose a new mobile cloudlet-assisted service mode named Opportunistic task Scheduling over Co-located Clouds (OSCC), which achieves flexible cost-delay tradeoffs between conventional remote cloud service mode and mobile cloudlets service mode. Then, we perform detailed analytic studies for OSCC mode, and solve the energy minimization problem by compromising among remote cloud mode, mobile cloudlets mode and OSCC mode. We also conduct extensive simulations to verify the effectiveness of the proposed OSCC mode, and analyze its applicability. Moreover, experimental results show that when the ratio of data size after task execution over original data size associated with the task is smaller than 1 ( i.e., $r ) and the average meeting rate of two mobile devices $\lambda$ is larger than $0.00014$ , our proposed OSCC mode outperforms existing service modes.

CypherDB: A Novel Architecture for Outsourcing Secure Database Processing

CypherDB addresses the problem of protecting the confidentiality of database stored externally in a cloud and enabling efficient computation over it to thwart any curious-but-honest cloud computing service provider. It works by encrypting the entire outsourced database and executing queries over the encrypted data using our novel CypherDB secure processor architecture. To optimize computational efficiency, our proposed processor architecture provides tightly-coupled datapaths that avoid information leakage during database access and query execution. Our simulation using a well-known database benchmark TPC-H over a commercial grade Database Management System (SQLite) demonstrates that our proposed architecture incurs an average of about 10 percent overhead when compared with the same set of operations without secure database processing.

Thoughts on human-computer interaction in the age of artificial intelligence

With the rapid development of information technology, the extensive development of artificial intelligence and its successful applications in several industries have given rise to great imaginations of providing computer services to human beings once again. However, as the interface of information communication between humans and computers-human-computer interaction-has not been properly developed, the resulting bottleneck effect has become increasingly evident. The reasons for this can be summarized as follows: (1) lack of learning history of the development experience; and (2) changes in the application scenarios in the age of artificial intelligence result in new demands, which presents a huge challenge to human-computer interaction. This paper presents a review of the history of the development of human-computer interaction, focuses on the core issues of human-computer interaction, and summarizes the important theory of thoughts. Lastly, we present some necessary discussions and reflections on the future development of human-computer interaction.

An exploration of growth in computer software micro firms

This paper investigates the drivers of growth in Swedish micro firms providing computer services. Analysis is based on linked data from several sources: registers on business, value added tax (VAT) and education as well as from production statistics. ordinary least squares (OLS) estimations, including approximately 7000 computer service micro firms, show that initial relative labor productivity of micro firms (compared to that of large firms) is significantly positively related to subsequent employment growth in the two following years. Furthermore, exporting micro firms grow faster than those that only sell on the domestic market. The link between exporting and firm growth is higher for export starters. Separate estimations for young micro firms confirm the positive relationships for both exporting and initial productivity. However, share of workers with a tertiary degree is not significantly related to the employment growth of micro firms. Quantile regressions reveal that both exporting and the initial productivity level are particularly important for high-growth micro firms.

Cloud Storage for Electronic Health Records Based on Secret Sharing With Verifiable Reconstruction Outsourcing

Deploying electronic health records (EHRs) is now an undisputable trend in healthcare systems. Through affording benefits like flexibility and low cost, the cutting-cloud cloud storage is becoming a popular solution to store a massive amount of EHRs to depress the local storage. Nevertheless, storing sensitive information such as health records on the cloud incurs severe security and privacy risks. In this paper, we propose a novel cloud storage system for EHRs which fully ensures the data privacy by employing the Shamir’s secret sharing. In this system, an EHR is divided into multiple segments by a healthcare center, and the segments are distributed to numerous cloud servers. When retrieving the EHR, the healthcare center captures segments from partial cloud servers and reconstructs the EHRs. Meanwhile, in reality, the reconstruction of a shared EHR could be much burdensome for a healthcare center or a patient, we thus propose a practical cloud storage scheme which outsources the reconstruction of a shared EHR to a cloud computing service provider. Such a solution can drastically boost the efficiency of the proposed scheme. As far as we know, our scheme is the first to define reconstruction outsourcing concept in all cloud storage schemes for EHRs based on secret sharing, and the results of outsourcing reconstruction can be verified by healthcare centers or patients in our scheme. The theoretical analysis and experimental results also support that our proposed scheme is secure and efficient.

A Circular Business Model for Cloud Computing Services Providers

NOTE: THIS ARTICLE WAS PUBLISHED WITH THE INFORMING SCIENCE INSTITUTE. Aim/Purpose................................................................................................................................................................................................. The main objective of the current study is to develop a business model for service providers of cloud computing which is designed based on circular economy principles and can ensure the sustainable consumption. Background Even though the demand for cloud computing technology is increasing day by day in all over the world, the current the linear economy principles are incapable to ensure society development needs. To consider the benefit of the society and the vendors at the same time, the principles of circular economy can address this issue. Methodology................................................................................................................................................................................................. An extensive literature review on consumption, sustainable consumption, circular economic, business model, and cloud computing were conducted. the proposed model of Osterwalder, Pigneur and Tucci (2005) is admitted designing the circular business model. Contribution................................................................................................................................................................................................. The proposed model of the study is the contribution of this study where provides the guidelines for the cloud computing service providers to achieve both their economic profits and the society’ needs. Findings Finding reveals that if the cloud computing service providers design their business model based on the “access” principle of circular economy, they can meet their economic profits and the society’ needs at a same time. Recommendations for Practitioners.............................................................................................................................................................. It is recommended to the startup and the existing businesses to utilize the proposed model of this study to reach a sustainable development. Recommendation for Researchers................................................................................................................................................................ It proposes a new circular business model and its linkages with community building. Impact on Society............................................................................................................................................................................................ The proposed model of the study provides guidelines to the cloud computing service providers to design a business model which is able not only to meet their economic profit, but also to meet the society’s and customers’ benefits. Future Research............................................................................................................................................................................................... Future researches can build on this research model which proposed in this study to examine the limitations of this model by using empirical researches.

Cost Aware Resource Selection in IaaS Clouds

One of the main challenges in cloud computing is to cope up with the selection of efficient resources in terms of cost. There are various cloud computing service providers which dynamically provide resources to the customers through different pricing policies. Based on the different APIs and pricing policies of the service providers, it becomes difficult for the customers to select the best service provider in terms of cost. In some cases, if the usage of the resources provided by a datacenter exceeds certain limit, then the providers cannot offer more resources to the customers as new VMs cannot be created. Hence, even if the customer chooses the best provider based on the least cost parameter, still there is no guarantee that the provider allocates complete resources to the customer. For this reason, I present system architecture that selects the best service provider based on the customer requirements mainly the cost. The proposed architecture also performs resource management by automatically providing new VMs from the available service providers in the inter cloud. The proposed system is based on five clouds i.e. Amazon EC2, Cloudsigma, Google, GoGrid, and Windows Azure. An interface is designed for obtaining the user requirements. These user requirements are matched with the design database of five cloud providers and based on the matched values; the catalog of optimal costs for each particular cloud is shown to the user. Then Cost Aware Resource Selection algorithm is run for determining the lowest optimal cost for Instance based approach and Quantity based approach. The algorithm tackles two domains of clouds for the algorithm i.e. Single Cloud and Multi Cloud.

AVE: Autonomous Vehicular Edge Computing Framework with ACO-Based Scheduling

With the emergence of in-vehicle applications, providing the required computational capabilities is becoming a crucial problem. This paper proposes a framework named autonomous vehicular edge (AVE) for edge computing on the road, with the aim of increasing the computational capabilities of vehicles in a decentralized manner. By managing the idle computational resources on vehicles and using them efficiently, the proposed AVE framework can provide computation services in dynamic vehicular environments without requiring particular infrastructures to be deployed. Specifically, this paper introduces a workflow to support the autonomous organization of vehicular edges. Efficient job caching is proposed to better schedule jobs based on the information collected on neighboring vehicles, including GPS information. A scheduling algorithm based on ant colony optimization is designed to solve this job assignment problem. Extensive simulations are conducted, and the simulation results demonstrate the superiority of this approach over competing schemes in typical urban and highway scenarios.

Verifiable and Exculpable Outsourced Attribute-Based Encryption for Access Control in Cloud Computing

We propose two ciphertext-policy attribute-based key encapsulation mechanism (CP-AB-KEM) schemes that for the first time achieve both outsourced encryption and outsourced decryption in two system storage models and give corresponding security analysis. In our schemes, heavy computations are outsourced to Encryption Service Providers (ESPs) or Decryption Service Providers (DSPs), leaving only one modular exponentiation computation for the sender or the receiver. Moreover, we propose a general verification mechanism for a wide class of ciphertext-policy (cf. key-policy) AB-KEM schemes, which can check the correctness of the outsourced encryption and decryption efficiently. Concretely, we introduce a stronger version of verifiability (cf. [1] ) and a new security notion for outsourced decryption called exculpability, which guarantees that a user cannot accuse DSP of returning incorrect results while it is not the case. With all these mechanisms, any dispute between a user and an outsource computation service provider can be easily resolved, furthermore, a service provider will be less motivated to give out wrong results. Finally, we implement our schemes in Charm [2] , and the results indicate that the proposed schemes/mechanisms are efficient and practical.

Energy Efficient Resource Allocation for Virtual Services Based on Heterogeneous Shared Hosting Platforms in Cloud Computing

Abstract This paper is an extended and updated version, presented at the INDIA 2017 conference. Optimal resource provisioning for virtual services in the Cloud computing is one of the concerns nowadays. For cloud computing service providers, reducing the number of physical machines providing resources for virtual services in cloud computing is one of the efficient ways to reduce the amount of energy consumption, which in turn enhances the performance of data centers. Multi-dimensional resource provisioning on a Heterogeneous Shared Hosting Platforms for virtual services is known as a NP-hard problem. Therefore, it is necessary to apply the metaheuristic algorithms for estimating the outcome of the problem. In this study, we propose the resource allocation problem for reducing the energy consumption. ECRA-SA algorithms were designed to solve it and were evaluated through CloudSim simulation tool compared with FFD algorithm. The experimental results show that the proposed ECRA-SA algorithm yields a better performance than FFD algorithm.

Applying Ant Colony System algorithm in multi-objective resource allocation for virtual services

ABSTRACTOver the past few years, using cloud computing technology has become popular. With the cloud computing service providers, reducing the number of physical machines providing resources for virtual services in cloud computing is one of the efficient ways to reduce the amount of energy consumption which in turn enhance the performance of data centres. However, using a minimum of physical machines to allocate resources for virtual services can result in system overload and break the SLA of service. Consequently, providing resources for virtual services which do not only satisfy the constraint of reducing the energy consumption but also ensure the load balancing of the whole system is necessary. In this study, we present the multi-objective resource allocation problem for virtual services. This problem aims at both reducing the energy consumption and balancing the load of physical machines. The MORA-ACS algorithm is proposed to resolve the problem by the Ant Colony System method. The experimental results show that in the CloudSim environment, the MORA-ACS algorithm could balance the load as well as reduce the energy consumption better than the Round Robin algorithm.

Logistics and cloud computing service providers’ cooperation: a resilience perspective

Cloud computing (CC) services can offer substantial cost-effective global operational and relationship benefits if the cooperation between logistics and CC services are resilient. Potential vulnerabilities to cooperation of CC and logistics service providers can occur with respect to vital factors such as security and trust. Extant studies have demonstrated CC benefits as well as few challenges associated with CC services application. However, no extant study has examined the inter-organisational benefits based on cooperative resilience between CC and logistics service providers in terms of both capability and trust vulnerability factors. This study examines the cooperative resilience of logistics and CC service providers based on innovation diffusion theory within a supply chain risk assessment framework. Using structural equation modelling techniques, we investigate the relationship between the vulnerability factor (trust), capability factor (security) and collaboration benefits (relationship and operational) offered by CC service providers based on 236 Chinese logistics service firms’ perceptions of CC adoption. The results indicate Chinese logistics companies perceive security impediments as a major factor affecting cooperative resilience between logistics service and CC service providers.