Pablo Chacin

In this article, the authors dissect the technical challenges that cities face when implementing smart city plans and outlines the design principles and lessons learned after they carried out a flagship initiative on fog computing in Barcelona. In particular, they analyze what they call the Quadruple Silo (QS) problem -- that is, four categories of silos that cities confront after deploying commercially available solutions. Those silo categories are: physical (hardware) silos, data silos, and… Show more

In this article, the authors dissect the technical challenges that cities face when implementing smart city plans and outlines the design principles and lessons learned after they carried out a flagship initiative on fog computing in Barcelona. In particular, they analyze what they call the Quadruple Silo (QS) problem -- that is, four categories of silos that cities confront after deploying commercially available solutions. Those silo categories are: physical (hardware) silos, data silos, and service management silos, and the implications of the three silos in administrative silos. The authors show how their converged cloud/fog paradigm not only helps solve the QS problem, but also meets the requirements of a growing number of decentralized services -- an area in which traditional cloud models fall short. The article exposes cases in which fog computing is a must, and shows that the reasons for deploying fog are centered much more on operational requirements than on performance issues related to the cloud. Show less

Today we witness the converge of two tidal forces: an increasing demand for new mobility related services and the extension of traditional ITS infrastructures to include a myriad of in vehicle and in-road sensors, mobile devices, and powerful road-side components backed by massive cloud services. The prevalent ITS architectures seams not be be sufficient to address many usage scenarios that require local, near real-time interactions and cooperation among multiple parties. In this paper we… Show more

Today we witness the converge of two tidal forces: an increasing demand for new mobility related services and the extension of traditional ITS infrastructures to include a myriad of in vehicle and in-road sensors, mobile devices, and powerful road-side components backed by massive cloud services. The prevalent ITS architectures seams not be be sufficient to address many usage scenarios that require local, near real-time interactions and cooperation among multiple parties. In this paper we explore the requirements for an open platform that supports the development and deployment of ITS services that run on the edges of the infrastructure and interact with a diversity of sensors and devices. We then explore some promising emerging trends that could contribute to address these challenges. We finally propose a research roadmap for the development of the future ITS architectures. Show less

This deliverable introduces IoT Standards Developing Organisation (SDO), Alliance and Open Source Software (OSS) landscapes to be used as input for the recommendations for Large Scale Pilots (LSPs) standard framework and gap analysis. The LSPs can play an important role in investigating and solving specific challenges for the IoT industry and promoting innovation that is related to specific activities such as 1) the applied standards framework, 2) deployments, 3) technological and business… Show more

This deliverable introduces IoT Standards Developing Organisation (SDO), Alliance and Open Source Software (OSS) landscapes to be used as input for the recommendations for Large Scale Pilots (LSPs) standard framework and gap analysis. The LSPs can play an important role in investigating and solving specific challenges for the IoT industry and promoting innovation that is related to specific activities such as 1) the applied standards framework, 2) deployments, 3) technological and business model validation and 4) acceptability.
The main objective of this deliverable is to briefly present the global dynamics and landscapes of IoT SDO, Alliance and OSS initiatives, which can be used: 1) to leverage on existing IoT standardization, industry promotion and implementation of standards and protocols, 2) as input for LSP standards framework and gap analysis and 3) to provide a guideline for the proponents of future project proposals associated with future IoT related calls financed by the EC on the positioning of these initiatives within these landscapes. Show less

Modern service-oriented applications demand the ability to adapt to changing conditions and unexpected situations while maintaining a required QoS. Existing self-adaptation approaches seem inadequate to address this challenge because many of their assumptions are not met on the large-scale, highly dynamic infrastructures where these applications are generally deployed on.

The main motivation of our research is to devise principles that guide the construction of large scale self-adaptive… Show more

Modern service-oriented applications demand the ability to adapt to changing conditions and unexpected situations while maintaining a required QoS. Existing self-adaptation approaches seem inadequate to address this challenge because many of their assumptions are not met on the large-scale, highly dynamic infrastructures where these applications are generally deployed on.

The main motivation of our research is to devise principles that guide the construction of large scale self-adaptive distributed services. We aim to provide sound modeling abstractions based on a clear conceptual background, and their realization as a middleware framework that supports the development of such services.

Taking the inspiration from the concepts of decentralized markets in economics, we propose a solution based on three principles: emergent self-organization, utility driven behavior and model-less adaptation. Based on these principles, we designed Collectives, a middleware framework which provides a comprehensive solution for the diverse adaptation concerns that rise in the development of distributed systems. We tested the soundness and comprehensiveness of the Collectives framework by implementing eUDON, a middleware for self-adaptive web services, which we then evaluated extensively by means of a simulation model to analyze its adaptation capabilities in diverse settings.

We found that eUDON adapts to diverse conditions like peaks in the workload and massive failures, maintaining its QoS and using efficiently the available resources; it is highly scalable and robust; can be implemented on existing services in a non-intrusive way; and do not require any performance model of the services, their workload or the resources they use.

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The main contribution of this paper is the proposal of an Elastic Utility Driven Overlay Network (eUDON) for dynamically scaling the number of instances of a service to ensure a target QoS objective in highly dynamic large-scale infrastructures of non-dedicated servers. This overlay combines an application provided utility function to express the service’s QoS, with an epidemic protocol for state information dissemination, and simple local decisions on each instance to adapt to changes in the… Show more

The main contribution of this paper is the proposal of an Elastic Utility Driven Overlay Network (eUDON) for dynamically scaling the number of instances of a service to ensure a target QoS objective in highly dynamic large-scale infrastructures of non-dedicated servers. This overlay combines an application provided utility function to express the service’s QoS, with an epidemic protocol for state information dissemination, and simple local decisions on each instance to adapt to changes in the execution conditions. These elements give the overlay robustness, flexibility, scalability and a low overhead.

We show, by means of simulation experiments, that the proposed mechanisms can adapt to a diverse range of situations like flash crowds and massive failures, while maintaining the QoS objectives of the service Show less

Recent years have witnessed the emergence of service-oriented applications formed by a large number of service instances deployed on shared infrastructures. This paradigm introduces significant challenges for the load balancing of requests in terms of how to adapt to non-dedicated servers whose capacities can vary over time; how to scale up to a very large number of service instances; how to handle the churn of instances as they are activated/deactivated or fail; and how to handle variations in… Show more

Recent years have witnessed the emergence of service-oriented applications formed by a large number of service instances deployed on shared infrastructures. This paradigm introduces significant challenges for the load balancing of requests in terms of how to adapt to non-dedicated servers whose capacities can vary over time; how to scale up to a very large number of service instances; how to handle the churn of instances as they are activated/deactivated or fail; and how to handle variations in the demand, including flash crowds.

To address these challenges, we propose UDON, a Utility-Driven Overlay Network that combines a simple routing heuristic with an adaptive admission control function, using state information about service instances disseminated by an epidemic algorithm.

Our results indicate that the mechanism we propose can effectively maintain a target QoS objective despite the variations in the capacity of servers due to background loads; is robust and
scalable; has low overhead; makes an efficient usage of resources; and adapts to different operational conditions. Show less

Service Oriented Computing has a deep impact on how IT infrastructures are conceived both in academia (e-science) and in industry (Service Oriented Architecture and commercial Web Services). Increasingly, economic models are being considered as suitable coordination mechanism for the management of service allocations to clients. However, few complete infrastructures have demonstrated the enabling of economics-based Service Oriented Grids (SOGs). The authors propose a complete infrastructure for… Show more

Service Oriented Computing has a deep impact on how IT infrastructures are conceived both in academia (e-science) and in industry (Service Oriented Architecture and commercial Web Services). Increasingly, economic models are being considered as suitable coordination mechanism for the management of service allocations to clients. However, few complete infrastructures have demonstrated the enabling of economics-based Service Oriented Grids (SOGs). The authors propose a complete infrastructure for economics-based SOGs and demonstrate its application in a prototype. They conduct experiments showing that practical agent-based automatic and fair trading of services at stable prices can be achieved using the proposed infrastructure. Show less

Markets are a powerful model for the coordination of distributed systems and,
in particular, in the face of incomplete information and changing environments.
The application of markets for the resource allocation in grid systems has re-
cently been researched as an alternative to traditional approaches. However,
the proper implementation of sophisticated markets capable of handling diverse
trading models (various auctions types, bargaining) and structures (direct… Show more

Markets are a powerful model for the coordination of distributed systems and,
in particular, in the face of incomplete information and changing environments.
The application of markets for the resource allocation in grid systems has re-
cently been researched as an alternative to traditional approaches. However,
the proper implementation of sophisticated markets capable of handling diverse
trading models (various auctions types, bargaining) and structures (direct nego-
tiation, brokering, etc.) requires a set of supporting services to provide partici-
pants a proper environment to engage in negotiations. Grid Market Middleware
(GMM) is a framework that aims to ease the development of market based grid
systems. In this paper we present its architecture, the services it provides and
describe how they can be used to implement diverse market models. We also
discuss our experience with the implementation of prototypes for various core
services.
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The development of a self-adaptive P2P applications faces many challenges ranging from the proper modeling of the application's behavior to the definition of the distributed algorithms required to support its functionalities and finally to its implementation in a particular platform. Collectives is a framework that addresses this issues by providing the modeling concepts and the implementation architecture required to separate the diverse adaptation concerns at the proper level of abstraction.

Efficient resource discovery and allocation is one of the challenges of any large scale Application Layer Network (ALN) such as computational Grids, Content Distribution Networks and P2P applications. In centralized approaches, the user requests can easily be matched to the most convenient resource. These approaches, however, present scalability limits in the highly dynamic and complex ALN environments. This paper, explores an architecture for incorporating fully decentralized economic… Show more

Efficient resource discovery and allocation is one of the challenges of any large scale Application Layer Network (ALN) such as computational Grids, Content Distribution Networks and P2P applications. In centralized approaches, the user requests can easily be matched to the most convenient resource. These approaches, however, present scalability limits in the highly dynamic and complex ALN environments. This paper, explores an architecture for incorporating fully decentralized economic mechanisms for resource allocation. These mechanisms are implemented by a set of trading agents that operate on behalf of the clients and service providers, interacting over an overlay network and interfacing with the underlying resources of the platform. A prototype of the proposed architecture is presented and the practical implications of its implementation in a grid scenario are discussed. Show less

Resource allocation is one of the challenges for self-management of
large scale distributed applications running in a dynamic and heterogeneous
environment. Considering Application Layer Networks (ALN) as a general
term for such applications including computational Grids, Content Distribution
Networks and P2P applications, the characteristics of the ALNs and the
environment preclude an efficient resource allocation by a central instance. The
approach we propose integrates… Show more

Resource allocation is one of the challenges for self-management of
large scale distributed applications running in a dynamic and heterogeneous
environment. Considering Application Layer Networks (ALN) as a general
term for such applications including computational Grids, Content Distribution
Networks and P2P applications, the characteristics of the ALNs and the
environment preclude an efficient resource allocation by a central instance. The
approach we propose integrates ideas from decentralized economic models into
the architecture of a resource allocation middleware, which allows the
scalability towards the participant number and the robustness in very dynamic
environments. At the same time, the pursuit of the participants for their
individual goals should benefit the global optimization of the application. In
this work, we describe the components of this middleware architecture and
introduce an ongoing prototype. Show less

Grid computing has recently become an important paradigm for managing computationally demanding applications, composed of a collection of services. The dynamic discovery of services, and the selection of a particular service instance providing the best value out of the discovered alternatives, poses a complex multi-attribute n:m allocation decision problem, which is often solved using a centralized resource broker. To manage complexity, this article proposes a two-layer architecture for service… Show more

Grid computing has recently become an important paradigm for managing computationally demanding applications, composed of a collection of services. The dynamic discovery of services, and the selection of a particular service instance providing the best value out of the discovered alternatives, poses a complex multi-attribute n:m allocation decision problem, which is often solved using a centralized resource broker. To manage complexity, this article proposes a two-layer architecture for service discovery in such Application Layer Networks (ALN). The first layer consists of a service market in which complex services are translated to a set of basic services, which are distinguished by price and availability. The second layer provides an allocation of services to appropriate resources in order to enact the specified services. This framework comprises the foundations for a later comparison of centralized and decentralized market mechanisms for allocation of services and resources in ALNs and Grids. Show less