Cloud Federation Research Articles

A Cost-Aware Management Framework for Placement of Data-Intensive Applications on Federated Cloud

Modern big data analysis and business intelligence applications come with high resource demands, along with a requirement for large data transfer between storage and compute nodes. Since the available resources of a single data center might not be sufficient to host these applications, federated cloud systems present a promising solution. The objective of each cloud service provider in a federation is to maximize its own profit and to minimize its total operating cost. To achieve these objectives, spatial variation in the energy cost and bandwidth cost could be leveraged while allocating the workload. We propose a hierarchical approach for resource management in a federated cloud, catering to the requirements of each provider in the federation. We formulate the placement of a data-intensive applications as an optimization problem to minimize the total operating cost, including the energy and communication costs. We propose an algorithm to allocate the virtual components of a data-intensive application, in two phases; partitioning and mapping. While partitioning creates clusters of correlated nodes, mapping allocates the created clusters to data centers that minimize the total cost. Through extensive experiments in different scenarios, we demonstrate that the proposed algorithm achieves a significant reduction in the total operating cost.

A Secret data sharing Model for Agriculture Experts in Federated Cloud based on Polynomial based Encrypted Scheme

A shift in computation from PC’s to Cloud allows more number of users to involve in cooperative computation on various categories of data wish to merge their expertise and thereby gain more useful information without leaking their own sensitive information. In the case of data collected from various sensors in an agricultural farm IoT device, the cloud and customers can cooperate to provide adequate services; benefits to experts, research stations related to agriculture. Enormous Agriculture Data generated is related to Soil, weather, Research, crop, farmers, Agriculture marketing, Agri-IOT, fertilizers and pesticide makes cloud as a centralized resource. The exchange of information and research will inculcate a healthy competitive atmosphere in the country in agriculture. Sharing of data, computation, services across cloud boundaries with different clients at different places will enhance expertise suggestions and results to farming field which benefit to improve countries economy. Federation of cloud will allow resource and data sharing, but the security threats severely limit the application development as the usage of data processing or sharing mechanisms will leak private information. So in this research paper, a Polynomial Based Encryption Secret Sharing Scheme (PBESSS)is proposed as Federated cloud data exchange system with multiple cloud instances of the same cloud host or separate computing hosts.

Cooperative Service Placement and Scheduling in Edge Clouds: A Deadline-Driven Approach

Mobile edge computing enables resource-limited edge clouds (ECs) in federation to help each other with resource-hungry yet delay-sensitive service requests. Contrary to common practice, we acknowledge that mobile services are heterogeneous and the limited storage resources of ECs allow only a subset of services to be placed at the same time. This paper presents a jointly optimized design of cooperative placement and scheduling framework, named JCPS, that pursues <i>social cost minimization</i> over time while ensuring diverse user demands. Our main contribution is a novel perspective on cost reduction by exploiting the <i>spatial-temporal diversities</i> in <i>workload and resource cost</i> among federated ECs. To build a practical edge cloud federation system, we have to consider two major challenges: <i>user deadline preference</i> and <i>ECs’ strategic behaviors</i> . We first formulate and solve the problem of spatially strategic optimization without deadline awareness, which is proved <inline-formula><tex-math notation="LaTeX">$\mathcal {NP}$</tex-math></inline-formula> -hard. By leveraging user deadline tolerance, we develop a Lyapunov-based <i>deadline-driven</i> joint cooperative mechanism under the scenario where the workload and resource information of ECs are known for one-shot global cost minimization. The <i>service priority</i> imposed by deadline urgency drives time-critical placement and scheduling, which, combined with cooperative control, enables workloads migrated across different times and ECs. Given selfishness of individual ECs, we further design an auction-based cooperative mechanism to elicit <i>truthful bids</i> on workload and resource cost. Rigorous theoretical analysis and extensive simulations are performed, validating the efficiency of JCPS in realizing cost reduction and user satisfaction.

Optimize the Cost of Resources in Federated Cloud by Collaborated Resource Provisioning and Most Cost-effective Collated Providers Resource First Algorithm

Cloud Computing works as the best solution for providing many of its services for cloud consumer agents with different requests for huge computational VM's with large storage capacity. The instance requests of cloud consumers will dynamically change as per their usage of application requirements with the demand for business growth, and single-vendor cloud becomes a constraint to satisfy these needs of the cloud consumers. Federated Cloud can contribute its solution approaches to meet these dynamic needs of cloud consumer requests of resource instances. The interoperability of clouds was made realistic with cloud federation. This paper provides an optimized solution approach where a set of collaborated cloud providers will provide services to satisfy consumer agents' multiple requests. It presents the two-phase collaborated resource provisioning (CCRP) approach and Most Cost-Effective Collated Providers Resources First (MCECPRF) algorithm. The algorithm’s efficiency has been tested with specific data set for optimizing the cost for cloud consumer agents and analyzes the cancellation of requests, decision time for provisioning for different VM configurations within specific time slots.

End-to-end SLA management in federated clouds

Cloud federation is a concept that collectively combines segregated cloud services to create an extended pool of resources for clouds to competently deliver their promised level of services. This p...

An improved pricing algorithm for infrastructure as a service cloud

Marketing in cloud systems enables users to trade and share resources. For the sales of services, client applications and service providers negotiate to make a service level agreement. Offering prices in the negotiation of services become one that is challenging. A federal cloud is an efficient approach of recent interest to better balance risk sharing between services provider and customer. This work presents a new algorithm to increase service provider revenue and reducing user costs simultaneously. The auction of remaining time spent on resources and interactions between federal clouds increases the profits of clouds, the number of successful requests, and reduces users' costs. The simulation results confirm the expectations of the proposed approach.

An agent-based mechanism to form cloud federations and manage their requirements changes

An agent-based mechanism to form cloud federations and manage their requirements changes

An agent-based mechanism to form cloud federations and manage their requirements changes

Cloud computing is a business paradigm, where Cloud providers offer computing resources (software and hardware) and Cloud consumers use them. Forming Cloud federations and managing them is a big pr...

Making the digital economy “fit for Europe”

AbstractOver the past three decades, cyberspace has gradually become an engine of unsustainable outcomes from an economic, social and environmental perspective. The European Commission has launched several new initiatives, in the attempt to restore public control over cyberspace, remedy the distributional imbalances generated by the rise of large‐scale digital platforms, and promote Europe's digital sovereignty. The paper argues that only by embedding rules and values in “code” and preserving openness towards the rest of the world will the EU manage to achieve its desired goals. Current initiatives such as the data strategy, the AI regulation, the Digital Services Act and the European Cloud Federation appear still too sparse and uncoordinated to really deliver on Europe's ambition to lead the world in the sustainable use of technology.

Federation-Level Agreement and Integrity-Based Managed Cloud Federation Architecture

One of the biggest challenges in cloud federations is how to express the federation level agreement (FLA) and voluntary aspect of the federation members and maintain the integrity of the organization. However, existing works are not able to present the cloud federation management aspect or implement these properties that distinguish cloud federation from other inter-cloud organizations. This paper bridges this gap by proposing a managed cloud federation architecture based on this subset of properties. The key component of this architecture is the federation manager that controls, tracks, evaluates, and predicts the behavior of the federation. In order to ensure the effectiveness of the approach, the authors developed the Managed Federation Simulator to implement the proposed federation architecture on the SmartFed simulator and evaluate it through a set of scenarios on a real case study.

Mobile Medical Applications and Cloud Federation Challenges

Abstract Issue Given the importance, of cloud environments for mobile telemedicine information systems, focus is given in this paper on the challenges rising. We discuss the pros of the access to computing services and resources on demand without having own infrastructures, and the need of advanced interoperability data formats and application program interfaces (APIs) to facilitate the usage of the infrastructure. Description of the problem Cloud-Oriented Architecture (COA) describes the architecture, where applications act as services and serve other applications in the cloud environment. The aim is IT infrastructure and software applications to be optimized for their use in cloud computing environments. But what happens in the specific field of health as data interoperability for mobile telemedicine information systems? Results Two architectures were presented using a patient's compliance and engagement solution. A simple Representational State Transfer (REST) based architectural style was implemented in a three-layered architecture first and then compared to a cloud federation model. In the second the interaction goes through the federation via a middleware layer. Internal operations of cloud providers in the federation are still transparent to the cloud users. The middleware layer aims to coordinate the interaction with cloud users and providers in the federation. But, to avoid delays in those interactions interoperability of data formats and APIs. Lessons A Fast Healthcare Interoperability Resources (FHIR) based application was developed. Mobile telemedicine information systems are a strong instrument in patients' compliance. Many systems have proved that the used resources combined can solve clinical and administrative problems in a secure environment. Key messages The use of cloud is wide spread in the health sector. The challenge is to combine this infrastructure into one federated platform and maximize the added value by using advanced interoperability data formats and APIs.

Resource management in the federated cloud environment using Cournot and Bertrand competitions

Cloud federation helps cloud providers to scale up by renting resources from other providers when the workload increased. Moreover, cloud providers with idle or underutilized resources can sell their resources to others and earn revenue inside a cloud federation. One of the most critical problems in the federated cloud environment is the management of resources and cloud providers. The game theory seems to be an excellent way to model cloud federation. This paper introduces a new model for resource management between cloud providers in a centralized federated cloud environment, based on the well known Cournot and Bertrand games. To resolve the problem of heterogeneous resources, a physical resource unit which has specific computational features and can be shared between cloud providers is introduced in this paper. Besides, by introducing a new revenue-sharing approach between providers, this paper increased the collaboration of different providers. This model is implemented by the federated Cloudsim tool, and experiments show that the Cournot model outperforms others in terms of overall benefit and responsiveness. In other words, Cournot model can respond to an acceptable number of requests while making more profit. Besides, the reviews show that the proposed model works better than other methods in terms of time.

Resource Provisioning Analysis in Virtual Machines Using Statistical Performance of Workloads for Business Applications

Cloud Federation is the interconnection of two or more cloud computing settings in order to share configurable processing components such as networks, servers, apps that can be dynamically delivered to customers. Virtualization has been an integral part of cloud computing which provides manageability and utilization of resources. This paper analyses on how jobs of business applications demand and efficiently use the capacity of the resources that are provisioned by the VMs, thereby managing the performance of the applications. The in-depth assessment is based on two large-scale and constant performance traces gathered in a cloud datacenter that host company tools for running distinct apps with regard to requested and used resources.

A Survey on the Security Issues of Software Defined Networking Tool in Cloud Computing

The Advent of the digital age has led to a rise in different types of data with every passing day. In fact, it is expected that half of the total data used around the world will be on the cloud nowadays. This complex data needs to be stored, processed and analyzed for information gaining that can be used for several organizations. Cloud computing provides an appropriate platform for Software Defined Networking (SDN) in communicating and computing requirements of the latter. It makes cloud-based networking a viable research field in the current scenario. However, several issues addressed and risk needs to be mitigated in the L2 cloud server. Virtual networks and cloud federation being considered in the network virtualization over L3 cloud router. This research work explores the existing research challenges and discusses open issues for the security in cloud computing and its uses in the relevant field by means of a comparative analysis of L2 server L3 router based on SDN tools. Also, an analysis of such issues are discussed and summarized. Finally, the best tool identified for the use cloud security.

Effective Data Storage and Dynamic Data Auditing Scheme for Providing Distributed Services in Federated Cloud

Recently, many organizations and industries are using the cloud computing technologies for exchanging the resources and their confidential data. For this purpose, many cloud services are available and also provide the facility to categorize their users as private and public users for accessing their own data from private cloud and public cloud. The combination of these two clouds is called federated cloud which facilitates to allow both kinds of cloud users for accessing their own data on same cloud database. In this scenario, the authorization and authentication process is becoming complex task on cloud. For providing the facility to access their own data only from federated cloud, a new secured data storage and retrieval algorithm called AES and Triple-DES-based Secured Storage and Retrieval Algorithm (ATDSRA) are proposed for storing the private and public cloud user’s data securely on cloud database. Here, the TDES is used for encrypting the input data, data merging and aggregation methods were used for grouping the encrypted input data. Moreover, a new dynamic data auditing scheme called CRT-based Dynamic Data Auditing Algorithm (CRTDDA) is proposed for conducting the cloud data auditing over the federated cloud and also restricting the data access. The proposed new auditing mechanism that is able to protect the stored data from access violence. In addition, the standard Table64 is used for encryption and decryption processes. The experimental results of this work proves the efficiency of the proposed model in terms of security level.

MultiCloud Tournament: A cloud federation approach to prevent Free-Riders by encouraging resource sharing

Organized in associations, Cloud Computing Providers became able to negotiate the acquisition of resources from other providers at more attractive prices, while allowing the marketing of their own idle resources to the other members of the respective Inter-Cloud. However, Inter-Cloud associations are characterized as resource-sharing environments, which allow for the presence of malicious providers called Free-Riders. Free-Riders have predatory behavior, seeking to serve only their own interests and consequently harming other providers within the environment. Mechanisms to avoid Free-Riders, as well as to keep resources supply × demand balanced, are needed in Inter-cloud environments such as Cloud Federations. For example, the absence of a resource consumption control mechanism can cause a Free-Rider to consume resources in a way that is disproportionate to that offered to Inter-Cloud, referring to the problem described previously. In view of the above, this paper presents a new Inter-Cloud called MultiClouds Tournament (MCT) focused on addressing the standalone cloud providers limitations. This Inter-Cloud is inspired by the format of a soccer tournament and based on the main features of Cloud Federations. We assessed the MCT using a real workload, showing it offers an architecture that adds to the characteristics of the federations, being effective in the management of CSPs and robust in relation to Free-Riders prevention and the main strategies CSPs.

On Coordination of Smart Grid and Cooperative Cloud Providers

Cooperative cloud providers in the form of cloud federations can potentially reduce their energy costs by exploiting electricity price fluctuations across different locations. In this environment, on the one hand, the electricity price has a significant influence on the federations formed, and, thus, on the profit earned by the cloud providers, and on the other hand, the cloud cooperation has an inevitable impact on the performance of the smart grid. In this regard, the interaction between independent cloud providers and the smart grid is modeled as a two-stage Stackelberg game interleaved with a coalitional game in this article. In this game, in the first stage the smart grid, as a leader chooses a proper electricity pricing mechanism to maximize its own profit. In the second stage, cloud providers cooperatively manage their workload to minimize their electricity costs. Given the dynamic of cloud providers in the federation formation process, an optimization model based on a constrained Markov decision process (CMDP) has been used by the smart grid to achieve the optimal policy. Numerical results show that the proposed solution yields around 28% and 29% profit improvement on average for the smart grid, and the cloud providers, respectively, compared to the noncooperative scheme.

A green, energy, and trust-aware multi-objective cloud coalition formation approach

The workload of cloud providers is often uncertain due to the dynamic and varied client demands, thus presenting a significant challenge. If cloud providers fail to meet changing demands during peak hours, they may experience service requests’ delays and rejections, damaging both their reputation and their profit margin. The idea of cloud federations is contemplated as a solution to this challenge by allowing a group of cloud providers to combine their resources, as and when required, to satisfy client requests dynamically. Despite the merits of the existing cloud federation approaches, they suffer from several limitations, such as performance issues, the inability to converge to a solution in complex scenarios, the lack of consideration of SLA requirements during the federation formation phase, and the lack of flexibility offered to clients to prioritize specific objectives during the formation of the cloud federation. This work addresses these deficiencies by presenting a green, practical, and customizable SLA-based approach to cloud federation formation. Inspired by social gaming, the proposed approach can rapidly form a stable coalition of cloud providers able to fulfill client requests, while ensuring the satisfaction of SLA requirements in terms of performance, energy consumption, CO2 emissions, and providers’ trustfulness. At the heart of this approach lies a new coalition formation algorithm, dubbed the “multi-criterion coalition formation algorithm (MCCF).” Unlike existing collation formation algorithms, the MCCF algorithm offers clients the flexibility to prioritize the objectives used for cloud federation formation. Based on those preferences, the MCCF algorithm generates stable SLA-aware groups of cloud providers that dynamically adapt to network changes using a self-healing process. The MCCF algorithm has been implemented and extensively tested using a wide range of scenarios, and its performance was compared with that of two state of the art approaches: The optimal approach and the split-and-merge approach. The results show that the MCCF algorithm outperforms the optimal and the split-and-merge approaches in terms of coalition size, individual providers’ payoff, and mistrust cost. Moreover, the proposed approach yields a zero % request rejection rate and an execution time that is 8 to 16 times faster than the split-and-merge and optimal approaches, while enabling a reduction of the Carbon footprint of the cloud coalition operations. Owing to these advantages and its ability to offer a flexible and customizable solution to clients, the MCCF algorithm represents a promising and environmentally conscious cloud collation formation approach that is ideal for real-time applications and practical cloud deployments.

An SLA-Aware Cloud Coalition Formation Approach for Virtualized Networks

One of the main challenges faced by cloud providers is the uncertainty in their workload, resulting from the high variability and the dynamic nature of clients' demands. The inability to meet those demands during peak times can lead to high service rejection rates, experienced delays, and consequently profit and reputation losses. The concept of cloud federation has been proposed as a way to address this challenge, by enabling a group of cloud providers to collaborate by dynamically combining their resources as needed, to satisfy received requests. Existing cloud federation approaches fail to consider clients' SLA requirements during the coalition formation process or provide a self-healing mechanism to deal with unexpected resources' shortage during operation. Furthermore, the state of the art approaches suffer from performance issues, such as high execution times, unstable performance, and lack of convergence to a solution in complex scenarios (e.g., requests with mixed, independent types of VMs). This paper proposes a novel social gaming based approach for coalition formation in the cloud that finds the best coalition of cloud providers to answer requests, while satisfying the clients' SLA requirements. The proposed algorithm, dubbed SLA Aware Cloud Coalition Formation algorithm (S-ACCF), leverages Irving's roommate algorithm to form a stable coalition of cloud providers, with a rapid execution time. The S-ACCF algorithm is designed to maximize the coalition's profit, while minimizing the number of participants in the coalition as well as the penalty incurred by providers who fail to offer all or some of the promised resources using a self-healing process. The S-ACCF algorithm was extensively tested using a variety of scenarios, and its performance was compared to two state of the art approaches: 1) the Optimal Cloud Federation Mechanism (OCFM) that relies on an exhaustive search of all possible solutions to find the best coalition; and 2) the Cloud Federation Formation Mechanism (CFFM) that relies on an iterative split-and-merge approach to find the best coalition. While the optimal approach (OCFM) always finds the best coalition leading to the highest collective profit, it has an exponential time complexity, thus leading to very large execution times. On the other hand, the split-and-merge approach (CFFM), which relies on random selection of sub-groups for coalition formation, suffers from instability (different results in repeated runs), high and variable execution time, and a noticeable requests' rejection rate that changes between runs. The test results show that the S-ACCF algorithm addresses the limitations of the OCFM and the CFFM algorithms, and outperforms the optimal and split-and-merge approaches in terms of execution time, individual provider payoff, and the number of providers per coalition. Furthermore, it yields higher stability and zero rejection rate, when compared to the split-and-merge approach. Indeed, our proposed approach yields an execution time that is 12 to 25 times faster than the optimal and split-and-merge approaches, which is a major advantage for real-time applications. Moreover, when compared to the two other approaches, our S-ACCF algorithm always finds the smallest coalition possible satisfying the client requirements, thus leading to the highest individual payoff for providers and lower administration overhead. Finally, unlike the split-and-merge approach, our algorithm shows a stable performance, and converges towards the optimal solution in simple and complex scenarios, thus making it suitable for production environments.

Data encoding and cost optimised distribution for efficient and secure storage in cloud federation

Cloud federation is the future paradigm of computing which can reduce cost and avoid vendor lock-in problem. Cloud providers are now collaborating for increasing revenue and building trust among customers and indirectly help in better resource utilisation of every service provider in the federation. In the proposed framework all collaborating service providers share their storage resources and use single sign-on federated identity management model which will reduce the overhead of maintaining multiple credentials and strengthen the authentication process. Initially, files are encrypted with the secret key created with client id, session token and a random number which will improve the data security and based on the service level selected for files erasure codes are applied, which will reduce storage overhead as compared to the traditional replication techniques. Hence overall reliability, availability and security of data stored in the cloud federation is improved.