Agent-based Cloud service composition

Service composition in multi-Cloud environments must coordinate self-interested participants, automate service selection, (re)configure distributed services, and deal with incomplete information about Cloud providers and their services. This work proposes an agent-based approach to compose services in multi-Cloud environments for different types of Cloud services: one-time virtualized services, e.g., processing a rendering job, persistent virtualized services, e.g., infrastructure-as-a-service scenarios, vertical services, e.g., integrating homogenous services, and horizontal services, e.g., integrating heterogeneous services. Agents are endowed with a semi-recursive contract net protocol and service capability tables (information catalogs about Cloud participants) to compose services based on consumer requirements. Empirical results obtained from an agent-based testbed show that agents in this work can: successfully compose services to satisfy service requirements, autonomously select services based on dynamic fees, effectively cope with constantly changing consumers’ service needs that trigger updates, and compose services in multiple Clouds even with incomplete information about Cloud participants.     

Hybrid Clouds brokering: Business opportunities,QoS and energy-saving issues

Hybrid Clouds couple the scalability offered by public Clouds with the greater control supplied by private ones. A (hybrid) Cloud broker acting as an intermediary between users and providers of public Cloud services, may support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality.The paper presents a Cloud brokering algorithm delivering services with different level of non-functional requirements, to the private or public resources, on the basis of different scheduling criteria. With the objective of maximize user satisfaction and broker’s revenues, the algorithm pursues profit increases by reducing energy costs, through the adoption of energy saving mechanisms. A simulation model is used to evaluate performance in terms of broker’s revenue, user satisfaction and energy behavior of various allocation policies. Simulation results show that differences among policies depend on system loads and that the use of turn on and off techniques greatly improves energy savings at low and medium load rates.     

MetaCDN: Harnessing ‘Storage Clouds’ for high performance content delivery

Content delivery networks (CDNs) such as Akamai and Mirror Image place web server clusters in numerous geographical locations to improve the responsiveness and locality of the content it hosts for end-users. However, their services are priced out of reach for all but the largest enterprise customers. An alternative approach to content delivery could be achieved by leveraging existing infrastructure provided by ‘Storage Cloud’ providers, who offer internet accessible data storage and delivery at a fraction of the cost. In this paper, we introduce MetaCDN, a system that exploits ‘Storage Cloud’ resources, creating an integrated overlay network that provides a low cost, high performance CDN for content creators. MetaCDN removes the complexity of dealing with multiple storage providers, by intelligently matching and placing users’ content onto one or many storage providers based on their quality of service, coverage and budget preferences. MetaCDN makes it trivial for content creators and consumers to harness the performance and coverage of numerous ‘Storage Clouds’ by providing a single unified namespace that makes it easy to integrate into origin websites, and is transparent for end-users. We then demonstrate the utility of this new approach to content delivery by showing that the participating ‘Storage Clouds’ used by MetaCDN provide high performance (in terms of throughput and response time) and reliable content delivery for content consumers, whilst the MetaCDN system itself introduces minimal overhead compared to using these ‘Storage Clouds’ directly.     

4CaaSt marketplace: An advanced business environment for trading cloud services

As Clouds mature and become ubiquitous, marketplace environments are developed facilitating the provision of services in a manner that emphasizes on the modular composition of individual services across different providers that crosscut the cloud service stack layers (i.e. composition of XaaS) to fulfil customers’ requirements. Besides acting as intermediaries for the search, selection and trading of services, such marketplaces should also support the complete service lifecycle and the consolidation of offerings from different providers with varying and often contradicting business goals. In this paper we present a one-stop cloud marketplace solution that addresses the aforementioned challenges while enabling the simulation of different business cases to optimize service offerings according to a wide and dynamic set of parameters. Moreover, the proposed solution introduces advanced aggregated price models and integrates a new resolution approach that incorporates business intelligence into the search and selection processes. We also demonstrate the operation of the implemented approach and evaluate its effectiveness using a real-world scenario, based on a taxi fleet management application.     

Dynamic,behavioral-based estimation of resource provisioning based on high-level application terms in Cloud platforms

Delivering Internet-scale services and IT-enabled capabilities as computing utilities has been made feasible through the emergence of Cloud environments. While current approaches address a number of challenges such as quality of service, live migration and fault tolerance, which is of increasing importance, refers to the embedding of users’ and applications’ behaviour in the management processes of Clouds. The latter will allow for accurate estimation of the resource provision (for certain levels of service quality) with respect to the anticipated users’ and applications’ requirements. In this paper we present a two-level generic black-box approach for behavioral-based management across the Cloud layers (i.e., Software, Platform, Infrastructure): it provides estimates for resource attributes at a low level by analyzing information at a high level related to application terms (Translation level) while it predicts the anticipated user behaviour (Behavioral level). Patterns in high-level information are identified through a time series analysis, and are afterwards translated to low-level resource attributes with the use of Artificial Neural Networks. We demonstrate the added value and effectiveness of the Translation level through different application scenarios: namely FFMPEG encoding, real-time interactive e-Learning and a Wikipedia-type server. For the latter, we also validate the combined level model through a trace-driven simulation for identifying the overall error of the two-level approach.     

Cloud federation in a layered service model

We show how a layered Cloud service model of software (SaaS), platform (PaaS), and infrastructure (IaaS) leverages multiple independent Clouds by creating a federation among the providers. The layered architecture leads naturally to a design in which inter-Cloud federation takes place at each service layer, mediated by a broker specific to the concerns of the parties at that layer. Federation increases consumer value for and facilitates providing IT services as a commodity. This business model for the Cloud is consistent with broker mediated supply and service delivery chains in other commodity sectors such as finance and manufacturing. Concreteness is added to the federated Cloud model by considering how it works in delivering the Weather Research and Forecasting service (WRF) as SaaS using PaaS and IaaS support. WRF is used to illustrate the concepts of delegation and federation, the translation of service requirements between service layers, and inter-Cloud broker functions needed to achieve federation.     

Design of emerging digital services: a taxonomy

There has been a gigantic shift from a product based economy to one based on services, specifically digital services. From every indication it is likely to be more than a passing fad and the changes these emerging digital services represent will continue to transform commerce and have yet to reach market saturation. Digital services are being designed for and offered to users, yet very little is known about the design process that goes behind these developments. Is there a science behind designing digital services? By examining 12 leading digital services, we have developed a design taxonomy to be able to classify and contrast digital services. What emerged in the taxonomy were two broad dimensions; a set of fundamental design objectives and a set of fundamental service provider objectives. This paper concludes with an application of the proposed taxonomy to three leading digital services. We hope that the proposed taxonomy will be useful in understanding the science behind the design of digital services.     

Balancing throughput and response time in online scientific Clouds via Ant Colony Optimization (SP2013/2013/00006)

The Cloud Computing paradigm focuses on the provisioning of reliable and scalable infrastructures (Clouds) delivering execution and storage services. The paradigm, with its promise of virtually infinite resources, seems to suit well in solving resource greedy scientific computing problems. The goal of this work is to study private Clouds to execute scientific experiments coming from multiple users, i.e., our work focuses on the Infrastructure as a Service (IaaS) model where custom Virtual Machines (VM) are launched in appropriate hosts available in a Cloud. Then, correctly scheduling Cloud hosts is very important and it is necessary to develop efficient scheduling strategies to appropriately allocate VMs to physical resources. The job scheduling problem is however NP-complete, and therefore many heuristics have been developed. In this work, we describe and evaluate a Cloud scheduler based on Ant Colony Optimization (ACO). The main performance metrics to study are the number of serviced users by the Cloud and the total number of created VMs in online (non-batch) scheduling scenarios. Besides, the number of intra-Cloud network messages sent are evaluated. Simulated experiments performed using CloudSim and job data from real scientific problems show that our scheduler succeeds in balancing the studied metrics compared to schedulers based on Random assignment and Genetic Algorithms.     

Mobile guides: Taxonomy of architectures,context awareness,technologies and applications

Portable devices are increasingly employed in a wide range of mobile guidance applications. Typical examples are guides in urban areas, museum guides, and exhibition space aids. The demand is for the delivery of context-specific services, wherein the context is typically identified by a combination of data related to location, time, user profile, device profile, network conditions and usage scenario. A context-aware mobile guide is intended to provide guidance services adjusted to the context of the received request. The adjustment may refer to tailoring the user interface to the perceived context, as well as delivering the right type of information to the right person at the right time and the right location. It may also refer to intermediary adaptation, as in the case of mobile multimedia transmission. This paper offers a taxonomy of mobile guides considering multiple criteria. The taxonomy considers several aspects of the mobile applications space, including context awareness, client architectures, mobile user interfaces, as well as offered functionalities, highlighting functional, architectural, technological, and implementation issues. Existing implementations are classified accordingly and a discussion of research issues and emerging trends is offered.     

A taxonomy of multicast protocols for Internet applications

The continuous growth in applications that require communications among a group of hosts or simultaneous dissemination of data to multiple sites on the Internet has led to considerable interest in multicast communication. These applications have different quality of service requirements such as deadlines to response time and tolerance to data loss. Internet multicast protocols provide a spectrum of services to cater for the needs of a wide array of multicast applications. The design alternatives of a multicast protocol for a particular application may lead to different performance characteristics, for example higher utilization of network bandwidth vs lower protocol processing requirements. Therefore a framework is required to various design choices available to design multicast protocols and evaluate the performance tradeoffs associated with these alternatives. Motivated by such a need and by the evolution of multicast applications over the Internet, this article presents a taxonomy of multicast protocols and a common framework to evaluate their performance.     

Optima: a domain-specific model for prioritization and conflicts management in requirements engineering for services intermediaries

New business models are set up, thanks to Web technologies. In this work, we focus on services intermediary companies. They generate value through the (automatic) selection of third-party services and the (automatic) delivery of the combinations of these services to consumers. Such companies face the problem of deciding which services to select and deliver in order to maximize their profit. The two main paper objectives are (i) to design the generic business model of services intermediaries and (ii) to propose an optimization model. The latter enables to choose the consumer requirements that will be satisfied in order to maximize profit. This model ranks implementable solutions based on various financial aspects. They are related to cost and revenue information that is associated with the requirements. It can support the decision-making process that aims at selecting a profit-maximizing set of requirements for services intermediaries’ system-to-be. Indeed, the proposed model solves the conflicts between requirements and prioritizes the optional requirements. We argue for the relevance of the optimization model via an example and simulations.     

Delivering cloud services with QoS requirements: Business opportunities,architectural solutions and energy-saving aspects

The flexible and pay-as-you-go computing capabilities offered by Cloud infrastructures are nowadays very attractive, and widely adopted by many organizations and enterprises. In particular this is true for those having periodical or variable tasks to execute, and, choose to not or cannot afford the expenses of buying and managing computing facilities or software packages, that should remain underutilized for most of the time. For their ability to couple the scalability offered by public service providers, with the wider Quality of Service (QoS) provisions and ad-hoc customizations provided by private Clouds, Hybrid Clouds (HC) seem a particularly appealing solution for customers requiring something more than the mere availability of the service.The paper firstly introduces a Cloud brokering system leveraging on a promising architectural approach, based on the use of a gateway toolkit. This approach provides noticeably advantages, both to customers and to Cloud Brokers (CB), for its ability to hide all the intricacies related to the management of powerful, but often complex and heterogeneous infrastructures like the Cloud. Moreover such approach, through customized interfaces, facilitates customers in accessing Cloud resources thus easing the tailored deployment and execution of their applications and workflows.The major contribution of this work is given by the analysis of a set of brokering strategies for Hybrid Clouds, implemented by a brokering algorithm, aimed at the execution of various applications subject to different user requirements and computational conditions. With the objective of firstly maximize both user satisfaction and CB’s revenues the algorithm also pursues profit increases through the reduction of energy costs by adopting energy saving mechanisms. A simulation model is used to evaluate performance, and the results show that differences among strategies depend on type and size of system loads and that the use of turn on and off techniques greatly improves energy savings at low and medium load rates thus indirectly increasing CB revenues without diminishing customers’ satisfaction.     

TaxoPublish: Towards a solution to automatically personalize taxonomies in e-catalogs

Taxonomies are utilized in e-catalogs to facilitate customers navigating through a marketplace with the help of hierarchically structured concepts. However, when entering the e-catalog, each customer is shown the identical taxonomy regardless their individual requirements. Customers are distracted when navigating to preferred concepts as those are siblings of not required concepts. Provided progress in dynamic taxonomies, catalog segmentation, and personalized directories lacks in a fully automatic support for modifying the taxonomy according to the user’s requirements. The existing works need an explicit user-query, are missing information about the domain, or require the modification through the provider. In this paper, TaxoPublish expert system based on logic programming is presented. The proposed system predicts the customers requirements for automatically modifying the taxonomy in B2B context. With TaxoPublish, retailers can now provide personalization in the form of personalized e-catalogs without any human effort, and without missing any information about the domain. TaxoPublish is using knowledge provided through a Customer Relationship Management system for predicting customers preferences, and knowledge of a Product Information Management system for performing taxonomic operations based on two novel types of taxonomic concepts. Through the usage of logic programming and the cross-platform database model, TaxoPublish can be applied as expert system over distributed and heterogeneous data warehouse architectures across various domains. The comprehensive experiments on two public and one private database show that TaxoPublish expert system is capable of fully-automatic taxonomy modification with an accuracy similar to the expert manual modifications.     

Multi-tenant intrusion detection system for public cloud (MTIDS)

Cloud computing is an innovative paradigm technology that is known for its versatility. It provides many creative services as requested, and it is both cost efficient and reliable. More specifically, cloud computing provides an opportunity for tenants to reduce cost and raise effectiveness by offering an alternative method of service utilization. Although these services are easily provided to tenants on demand with minor infrastructure investment, they are significantly exposed to intrusion attempts since the services are offered under the administration of diverse supervision over the Internet. Moreover, the security mechanisms offered by cloud providers do not take into consideration the variation of tenants’ needs as they provide the same security mechanism for all tenants. So, meeting tenants’ security requirements are still a major challenge for cloud providers. In this paper, we concentrate on the security service offered to cloud tenants and service providers and their infrastructure to restrain intruders. We intend to provide a flexible, on-demand, scalable, and pay-as-you-go multi-tenant intrusion detection system as a service that targets the security of the public cloud. Further, it is designed to deliver appropriate and optimized security taking into consideration the tenants’ needs in terms of security service requirements and budget.     

VMMP: a practical tool for the development of portable andefficient programs for multiprocessors

The VMMP (virtual machine for multiprocessors) software package is presented. It provides a coherent set of services for parallel application programs running on diverse multiple input multiple data (MIMD) multiprocessors, including shared memory and message passing multiprocessors. The communication, synchronization, and data distribution requirements of parallel algorithms are analyzed. Related languages and tools are described. VMMP services are identified. VMMP implementation, coding and portability are discussed. Some measurements of the performance of VROMP application programs and VMMP overhead are given. Several hints for improving the performance of application programs are described     

An intrusion detection and prevention system in cloud computing: A systematic review

The distributed and open structure of cloud computing and services becomes an attractive target for potential cyber-attacks by intruders. The traditional Intrusion Detection and Prevention Systems (IDPS) are largely inefficient to be deployed in cloud computing environments due to their openness and specific essence. This paper surveys, explores and informs researchers about the latest developed IDPSs and alarm management techniques by providing a comprehensive taxonomy and investigating possible solutions to detect and prevent intrusions in cloud computing systems. Considering the desired characteristics of IDPS and cloud computing systems, a list of germane requirements is identified and four concepts of autonomic computing self-management, ontology, risk management, and fuzzy theory are leveraged to satisfy these requirements.     

Groups of services delivered by Brazilian branchless banking and respective network integration models

Over the last decade, Brazil has pioneered an innovative model of branchless banking, known as correspondent banking, involving distribution partnership between banks, several kinds of retailers and a variety of other participants, which have allowed an unprecedented growth in bank outreach and became a reference worldwide. However, despite the extensive number of studies recently developed focusing on Brazilian branchless banking, there exists a clear research gap in the literature. It is still necessary to identify the different business configurations involving network integration through which the branchless banking channel can be structured, as well as the way they relate to the range of bank services delivered. Given this gap, our objective is to investigate the relationship between network integration models and services delivered through the branchless banking channel. Based on twenty interviews with managers involved with the correspondent banking business and data collected on almost 300 correspondent locations, our research is developed in two steps. First, we created a qualitative taxonomy through which we identified three classes of network integration models. Second, we performed a cluster analysis to explain the groups of financial services that fit each model. By contextualizing correspondents’ network integration processes through the lens of transaction costs economics, our results suggest that the more suited to deliver social-oriented, “pro-poor” services the channel is, the more it is controlled by banks. This research offers contributions to managers and policy makers interested in understanding better how different correspondent banking configurations are related with specific portfolios of services. Researchers interested in the subject of branchless banking can also benefit from the taxonomy presented and the transaction costs analysis of this kind of banking channel, which has been adopted in a number of developing countries all over the world now.     

A sharing-oriented service selection and scheduling approach for the optimization of resource utilization

We present a sharing-oriented service selection and scheduling approach capable of finding a trade-off between requirement satisfaction degree, service utilization rate and service sharing cost for limited quantities and capacities of available services. In traditional service selection approaches, each customer requirement is independently satisfied by optimally selecting a set of candidate service resources. However, in real-life service scenarios, it is usual for multiple customers to raise their requirements simultaneously, and available services need to be allocated between them. Especially, when available services are limited in both quantity and capacity, a traditional “first-come-first-serve” strategy would lead to a low service utilization rate, and some requirements cannot be satisfied at all (i.e., a low requirement satisfaction degree). Our approach makes use of the feature that some services can be shared by several customer requirements. Specifically, a virtualized service resource consisting of multiple candidate services is constructed and scheduled to satisfy multiple customer requirements simultaneously. Our approach searches for the global optimization on requirement satisfaction degree, service utilization rate, and service sharing cost. We build a mathematical model for this multi-objective optimization problem and propose a nested genetic algorithm mixed with a greedy strategy. Experiments in an ocean transportation service setting are conducted and our approach is compared with traditional approaches to validate its effectiveness.     

Robustness Comparison of 15 Real Telecommunication Networks: Structural and Centrality Measurements

Multiple failures can have catastrophic consequences on the normal operation of telecommunication networks. In this sense, guaranteeing network robustness to avoid users and services being disconnected is essential. A wide range of metrics have been proposed for measuring network robustness. In this paper the taxonomy of robustness metrics in telecommunication networks has been extended and a classification of multiple failures scenarios has been made. Moreover, a structural and centrality robustness comparison of 15 real telecommunication networks experiencing multiple failures was carried out. Through this analysis the topological properties which are common for grouping networks with similar robustness are able to be identified.