8 research outputs found

    Architecture for the heterogeneous federation of future internet experimentation facilities

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    International audienceInternet systems are currently too complex to be entirely designed in advance and therefore must be thoroughly evaluated in realistic environments. Experimentally driven research is at the heart of Future Internet Research and Experiment (FIRE) facilities, which target various experimenter profiles, ranging from core Internet communities and sensor networks to clouds and web services. Such facilities exist in relative isolation to the detriment of innovative research ideas that could arise from the mixture of their diverse technologies and resources, and their combined power. Internet research communities can benefit from gaining access to a larger number and variety of resources through a federation of these facilities. To this end, we present an architecture to support such a federation of Future Internet experimentation facilities, based on use cases and requirements from infrastructure owners, as well as services and first line support communities

    An architecture for mobile computation offloading on cloud-enabled LTE small cells

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    Small cell networks are currently seen as a new way to satisfy the increasing wireless traffic demand. The proximity of base stations to subscribers brings many possibilities for the development of new applications, including new offerings based on cloud computing. Smartphones can directly offload applications to close base stations, provided that these are equipped with additional computational and storage resources. The cloud concept applied in the framework of small cells can also combine radio and computation aspects in order to optimise the service delivery. This paper introduces a new element called the Small Cell Manager (SCM), which optimises the overall operation of a cluster of cloud-enabled small cells. The SCM, aware of the cluster situation in terms of both radio and cloud aspects, interacts not only with the cloud-enabled base stations, but also with LTE core network components. To that end, different possibilities for the general architecture of a small-cell-cloud are analysed. Furthermore, the paper describes different evaluation criteria an LTE operator has to consider before adopting this approach in order to optimise the required investment and maximise benefits.Peer Reviewe

    TROPIC-D22 Design of network architecture for femto-cloud computing

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    This deliverable intends to provide an analysis of the network architecture required for small-cell-cloud computing. The architectural framework considered in this document refers to LTE small cell architecture options outlined in the 3GPP standard.The individual elements for radio, cloud and backhaul are described and various possibilities are considered and compared in order to bring them all together for the operation of a small cell cluster to take place in an LTE environment, taking into account the differences between residential and corporate environments. The inter-cluster scenario, for greater computing capabilities, is also analysed. Finally, several solutions are provided for different problems encountered during the analysis, such as Over the Air Communication and distributed cluster management, among others. This document can be used as a recommendation for operators adopting the small-cell-cloud paradigm. The architectural choices are recommendations that telecom operators may study and evaluate according to their requirements and preferencesPreprin

    TROPIC-D22 Design of network architecture for femto-cloud computing

    No full text
    This deliverable intends to provide an analysis of the network architecture required for small-cell-cloud computing. The architectural framework considered in this document refers to LTE small cell architecture options outlined in the 3GPP standard.The individual elements for radio, cloud and backhaul are described and various possibilities are considered and compared in order to bring them all together for the operation of a small cell cluster to take place in an LTE environment, taking into account the differences between residential and corporate environments. The inter-cluster scenario, for greater computing capabilities, is also analysed. Finally, several solutions are provided for different problems encountered during the analysis, such as Over the Air Communication and distributed cluster management, among others. This document can be used as a recommendation for operators adopting the small-cell-cloud paradigm. The architectural choices are recommendations that telecom operators may study and evaluate according to their requirements and preference

    TROPIC-D22 Design of network architecture for femto-cloud computing

    No full text
    This deliverable intends to provide an analysis of the network architecture required for small-cell-cloud computing. The architectural framework considered in this document refers to LTE small cell architecture options outlined in the 3GPP standard.The individual elements for radio, cloud and backhaul are described and various possibilities are considered and compared in order to bring them all together for the operation of a small cell cluster to take place in an LTE environment, taking into account the differences between residential and corporate environments. The inter-cluster scenario, for greater computing capabilities, is also analysed. Finally, several solutions are provided for different problems encountered during the analysis, such as Over the Air Communication and distributed cluster management, among others. This document can be used as a recommendation for operators adopting the small-cell-cloud paradigm. The architectural choices are recommendations that telecom operators may study and evaluate according to their requirements and preference

    TROPIC-D21 Scenario and Requirements

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    This deliverable defines general framework for consequent technical workpackages in TROPIC. First, scenarios from the business point of view are defined and further transformed to more technical representation. Then, abstraction models are introduced for both communication and computation parts of femto-cloud concept. Furthermore, requirements need to be met to ensure efficient and feasible utilization of the femto-cloud are presented. To enable prove of the femto-cloud concept and to compare the developed techniques and algorithms a set of performance indicators to be considered in all technical workpackages are listed and defined. To that end, the models and simulation settings are defied in the last section of the documen

    TROPIC-D21 Scenario and Requirements

    No full text
    This deliverable defines general framework for consequent technical workpackages in TROPIC. First, scenarios from the business point of view are defined and further transformed to more technical representation. Then, abstraction models are introduced for both communication and computation parts of femto-cloud concept. Furthermore, requirements need to be met to ensure efficient and feasible utilization of the femto-cloud are presented. To enable prove of the femto-cloud concept and to compare the developed techniques and algorithms a set of performance indicators to be considered in all technical workpackages are listed and defined. To that end, the models and simulation settings are defied in the last section of the documentPreprin

    TROPIC-D21 Scenario and Requirements

    No full text
    This deliverable defines general framework for consequent technical workpackages in TROPIC. First, scenarios from the business point of view are defined and further transformed to more technical representation. Then, abstraction models are introduced for both communication and computation parts of femto-cloud concept. Furthermore, requirements need to be met to ensure efficient and feasible utilization of the femto-cloud are presented. To enable prove of the femto-cloud concept and to compare the developed techniques and algorithms a set of performance indicators to be considered in all technical workpackages are listed and defined. To that end, the models and simulation settings are defied in the last section of the documen
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