Power efficient virtual machine placement in cloud data centers with a discrete and chaotic hybrid optimization algorithm

Cluster Computing - Cloud computing is a new computation technology that provides services to consumers and businesses. The main idea of Cloud computing is to present software and hardware services...     

Classified power capping by network distribution trees for green computing

Power management is becoming very important in data centers. To apply power management in cloud computing, Green Computing has been proposed and considered. Cloud computing is one of the new promising techniques, that are appealing to many big companies. In fact, due to its dynamic structure and property in online services, cloud computing differs from current data centers in terms of power management. To better manage the power consumption of web services in cloud computing with dynamic user locations and behaviors, we propose a power budgeting design based on the logical level, using distribution trees. By setting multiple trees or forest, we can differentiate and analyze the effect of workload types and Service Level Agreements (SLAs, e.g. response time) in terms of power characteristics. Based on these, we introduce classified power capping for different services as the control reference to maximize power saving when there are mixed workloads.     

Ontology as a Service (OaaS): extracting and replacing sub-ontologies on the cloud

Cloud computing is founded by the concept of service computing, where everything is a service—computing services are now utilities. There are various known services in cloud computing. At the moment, there are Software as a Service (SaaS), Platform as a Service (PaaS), Hardware/Infrastructure as a Service (HaaS/IaaS), and Database as a Service (DaaS). In this paper, we propose Ontology as a Service (OaaS), which is an ontology tailoring process service in the cloud. In particular, we focus on sub-ontology extraction and replacement on the cloud. We use the Maximum Extraction method to facilitate this. UMLS meta-thesaurus ontology is used as a walk-through case study to illustrate our proposed method.     

A Service Brokering and Recommendation Mechanism for Better Selecting Cloud Services

Cloud computing is becoming the new generation computing infrastructure, and many cloud vendors provide different types of cloud services. How to choose the best cloud services for specific applications is very challenging. Addressing this challenge requires balancing multiple factors, such as business demands, technologies, policies and preferences in addition to the computing requirements. This paper recommends a mechanism for selecting the best public cloud service at the levels of Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). A systematic framework and associated workflow include cloud service filtration, solution generation, evaluation, and selection of public cloud services. Specifically, we propose the following: a hierarchical information model for integrating heterogeneous cloud information from different providers and a corresponding cloud information collecting mechanism; a cloud service classification model for categorizing and filtering cloud services and an application requirement schema for providing rules for creating application-specific configuration solutions; and a preference-aware solution evaluation mode for evaluating and recommending solutions according to the preferences of application providers. To test the proposed framework and methodologies, a cloud service advisory tool prototype was developed after which relevant experiments were conducted. The results show that the proposed system collects/updates/records the cloud information from multiple mainstream public cloud services in real-time, generates feasible cloud configuration solutions according to user specifications and acceptable cost predication, assesses solutions from multiple aspects (e.g., computing capability, potential cost and Service Level Agreement, SLA) and offers rational recommendations based on user preferences and practical cloud provisioning; and visually presents and compares solutions through an interactive web Graphical User Interface (GUI).     

CryptoGA: a cryptosystem based on genetic algorithm for cloud data security

Cluster Computing - Cloud Computing is referred to as a set of hardware and software that are being combined to deliver various services of computing. The cloud keeps the services for delivery of...     

The UK Human Genome Mapping Project online computing service

This paper presents an overview of computing and networkingfacilities developed by the Medical Research Council to provideonline computing support to the Human Genome Mapping Project(HGMP) in the UK. The facility is connected to a number of othercomputing facilities in various centres of genetics and molecularbiology research excellence, either directly via high-speedlinks or through national and international wide–areanetworks. The paper describes the design and implementationof the current system, a ‘client/server’ networkof Sun, IBM, DEC and Apple servers, gateways and workstations.A short outline of online computing services currently deliveredby this system to the UK human genetics research community isalso provided. More information about the services and theiravailability could be obtained by a direct approach to the UKHGMP-RC.     

Fault tolerance and QoS scheduling using CAN in mobile social cloud computing

The performance of mobile devices including smart phones and laptops is steadily rising as prices plummet sharply. So, mobile devices are changing from being a mere interface for requesting services to becoming computing resources for providing and sharing services due to immeasurably improved performance. With the increasing number of mobile device users, the utilization rate of SNS (Social Networking Service) is also soaring. Applying SNS to the existing computing environment enables members of social network to share computing services without further authentication. To use mobile device as a computing resource, temporary network disconnection caused by user mobility and various HW/SW faults causing service disruption should be considered. Also these issues must be resolved to support mobile users and to provide user requirements for services. Accordingly, we propose fault tolerance and QoS (Quality of Services) scheduling using CAN (Content Addressable Network) in Mobile Social Cloud Computing (MSCC). MSCC is a computing environment that integrates social network-based cloud computing and mobile devices. In the computing environment, a mobile user can, through mobile devices, become a member of a social network through real world relationships. Essentially, members of a social network share cloud service or data with other members without further authentication by using their mobile device. We use CAN as the underlying MSCC to logically manage the locations of mobile devices. Fault tolerance and QoS scheduling consists of four sub-scheduling algorithms: malicious-user filtering, cloud service delivery, QoS provisioning, and replication and load-balancing. Under the proposed scheduling, a mobile device is used as a resource for providing cloud services, faults caused from user mobility or other reasons are tolerated and user requirements for QoS are considered. We simulate scheduling both with and without CAN. The simulation results show that our proposed scheduling algorithm enhances cloud service execution time, finish time and reliability and reduces the cloud service error rate.     

Secure outsourcing of modular exponentiations in cloud and cluster computing

Cloud computing and cluster computing are user-centric computing services. The shared software and hardware resources and information can be provided to the computers and other equipments according to the demands of users. A majority of services are deployed through outsourcing. Outsourcing computation allows resource-constrained clients to outsource their complex computation workloads to a powerful server which is rich of computation resources. Modular exponentiation is one of the most complex computations in public key based cryptographic schemes. It is useful to reduce the computation cost of the clients by using outsourcing computation. In this paper, we propose a novel outsourcing algorithm for modular exponentiation based on the new mathematical division under the setting of two non-colluding cloud servers. The base and the power of the outsourced data can be kept private and the efficiency is improved compared with former works.     

Service-oriented execution model supporting data sharing and adaptive query processing

To deal with the environment’s heterogeneity, information providers usually offer access to their data by publishing Web services in the domain of pervasive computing. Therefore, to support applications that need to combine data from a diverse range of sources, pervasive computing requires a middleware to query multiple Web services. There exist works that have been investigating on generating optimal query plans. We however in this paper propose a query execution model, called PQModel, to optimize the process of query execution over Web Services. In other words, we attempt to improve query efficiency from the aspect of optimizing the execution processing of query plans.     

A limited-trust capacity model for mitigating threats of internal malicious services in cloud computing

Hidden persistent malware in guest virtual machine instances are among the most common internal threats in cloud computing, affecting the security of both cloud customers and providers. With the growing sophistication of modern malware, traditional methods are becoming increasingly ineffective for tackling cloud security problems. Moreover, given the pay-per-use model of clouds, consumption of resources by these malwares and malicious services can cause huge losses to both the cloud provider and customer. Thus, it is important to develop mechanisms that can limit the scale of malicious attacks in order to minimize their resources consumption. Trust management is a fundamental technique for assessing and increasing the reliability and security of cloud services. Unfortunately, majority of existing mechanisms for trust management in clouds have limitations that prevent them from being fully effective. In this paper, we propose a novel limited-trust capacity model to mitigate the threats of internal malicious software and services in cloud computing using concepts from flow networks to reduce the scale of malicious software or services. Our limited-trust capacity model can be utilized in the following two ways: (1) to manage the trust relationship among the guest services and to evaluate the threats of unknown malicious services, and (2) to minimize risk associated with renting cloud services and limiting the resource drain caused by malicious guest services. Finally, experimental results show that our limited-trust capacity model can effectively restrict the scale of malicious services and significantly mitigate the threats of internal attacks.     

RHAS: robust hybrid auto-scaling for web applications in cloud computing

Cluster Computing - The elasticity characteristic of cloud services attracts application providers to deploy applications in a cloud environment. The scalability feature of cloud computing gives...     

OPSA: an optimized prediction based scheduling approach for scientific applications in cloud environment

Cluster Computing - Cloud computing has attracted scientists to deploy scientific applications by offering services such as Infrastructure-as-a-service (IaaS), Software-as-a-service (SaaS), and...     

An in-depth and systematic literature review on the blockchain-based approaches for cloud computing

Cluster Computing - Cloud computing enables businesses to decrease the total costs by outsourcing their required services. Therefore, it provides a new challenge of data protection regarding...     

Dynamic large branching hash tree based secure and efficient dynamic auditing protocol for cloud environment

Cluster Computing - Cloud computing model offers various platforms services and provides a scalable, on-demand service at any time-anywhere manner. However, in the outsourcing strategy, users no...     

A resource-sharing model based on a repeated game in fog computing

With the rapid development of cloud computing techniques, the number of users is undergoing exponential growth. It is difficult for traditional data centers to perform many tasks in real time because of the limited bandwidth of resources. The concept of fog computing is proposed to support traditional cloud computing and to provide cloud services. In fog computing, the resource pool is composed of sporadic distributed resources that are more flexible and movable than a traditional data center. In this paper, we propose a fog computing structure and present a crowd-funding algorithm to integrate spare resources in the network. Furthermore, to encourage more resource owners to share their resources with the resource pool and to supervise the resource supporters as they actively perform their tasks, we propose an incentive mechanism in our algorithm. Simulation results show that our proposed incentive mechanism can effectively reduce the SLA violation rate and accelerate the completion of tasks.     

Design a cloud storage platform for pervasive computing environments

An increasing number of personal electronic handheld devices (e.g., SmartPhone, netbook, MID and etc.), which make up the personal pervasive computing environments, are playing an important role in our daily lives. Data storage and sharing is difficult for these devices due to the data inflation and the natural limitations of mobile devices, such as the limited storage space and the limited computing capability. Since the emerging cloud storage solutions can provide reliable and unlimited storage, they satisfy to the requirement of pervasive computing very well. Thus we designed a new cloud storage platform which includes a series of shadow storage services to address these new data management challenges in pervasive computing environments, which called as “SmartBox”. In SmartBox, each device is associated its shadow storage with a unique account, and the shadow storage acts as backup center as well as personal repository when the device is connected. To facilitate file navigation, all datasets in shadow storage are organized based on file attributes which support the users to seek files by semantic queries. We implemented a prototype of SmartBox focusing on pervasive environments being made up of Internet accessible devices. Experimental results with the deployments confirm the efficacy of shadow storage services in SmartBox.     

Software quality in the clouds: a cloud-based solution

Cloud computing, an on-demand computation model that consists of large data-centers (Clouds) managed by cloud providers, offers storage and computation needs for cloud users based on service level agreements (SLAs). Services in cloud computing are offered at relatively low cost. The model, therefore, forms a great target for many applications, such as startup businesses and e-commerce applications. The area of cloud computing has grown rapidly in the last few years; yet, it still faces some obstacles. For example, there is a lack of mechanisms that guarantee for cloud users the quality that they are actually getting, compared to the quality of service that is specified in SLAs. Another example is the concern of security, privacy and trust, since users lose control over their data and programs once they are sent to cloud providers. In this paper, we introduce a new architecture that aids the design and implementation of attestation services. The services monitor cloud-based applications to ensure software quality, such as security, privacy, trust and usability of cloud-based applications. Our approach is a user-centric approach through which users have more control on their own data/applications. Further, the proposed approach is a cloud-based approach where the powers of the clouds are utilized. Simulation results show that many services can be designed based on our architecture, with limited performance overhead.     

Interconnecting Federated Clouds by Using Publish-Subscribe Service

Cloud Federation is an emerging computing model where multiple resources from independent Cloud providers are leveraged to create large-scale distributed virtual computing clusters, operating as into a single Cloud organization. This model enables the implementation of environmental diversity for Cloud applications, and overcomes the provisioning and scalability limits of a single Cloud, by introducing minimal additional cost for the Cloud consumer. In such a scenario, it is necessary to leverage on specific networking technologies that enable the effective support of inter-Cloud communication services between Cloud providers. This paper proposes an interconnection solution for Cloud federations based on publish/subscribe services. Moreover, we discuss some fundamental concerns needed to satisfy the inter-Cloud communication requirements in terms of reliability and availability. Finally, we present some experimental results that highlight some key reliability and denial of service vulnerability concerns in this domain.     

Master–Worker: An Enabling Framework for Applications on the Computational Grid

The goal of this work is to create a tool that allows users to easily distribute large scientific computations on computational grids. Our tool MW relies on the simple master–worker paradigm. MW provides both a top Level interface to application software and a bottom Level interface to existing Grid computing toolkits. Both interfaces are briefly described. We conclude with a case study, where the necessary Grid services are provided by the Condor high-throughput computing system, and the MW-enabled application code is used to solve a combinatorial optimization problem of unprecedented complexity.