A Network Aware Resource Discovery Service

International audienceInternet in recent years has become a huge set of channels for content distribution highlighting limits and inefficiencies of the current protocol suite originally designed for host-to-host communication. In this paper we exploit recent advances in Information Centric Networks in the attempt to reshape the actual Internet infrastructure from a host-centric to a name-centric paradigm where the focus is on named data instead of machine name hosting those data. In particular, we pro- pose a Content Name System Service that provides a new network aware Content Discovery Service. The CNS behavior and architecture uses the BGP inter-domain routing information. In particular, the service registers and discovers resource names in each Autonomous System: contents are discovered by searching through the augmented AS graph represen- tation classifying ASes into customer, provider, and peering, as the BGP protocol does.Performance of CNS can be characterized by the fraction of Autonomous Systems that successfully locate a requested content and by the average number of CNS Servers explored during the search phase. A C-based simulator of CNS is developed and is run over real ASes topologies provided by the Center for Applied Internet Data Analysis to provide estimates of both performance indexes. Preliminary performance and sensitivity results show the CNS approach is promising and can be efficiently implemented by incrementally deploying CNS Servers

A network aware resource discovery service (a performance evaluation study)

International audienceInternet in recent years has become a huge set of channels for content distribution highlighting limits and inefficiencies of the current protocol suite originally designed for host-to-host communication. In this paper we exploit recent advances in Information Centric Networks in the attempt to reshape the actual Internet infrastructure from a host-centric to a name-centric paradigm where the focus is on named data instead of machine name hosting those data. In particular, we pro- pose a Content Name System Service that provides a new network aware Content Discovery Service. The CNS behavior and architecture uses the BGP inter-domain routing information. In particular, the service registers and discovers resource names in each Autonomous System: contents are discovered by searching through the augmented AS graph represen- tation classifying ASes into customer, provider, and peering, as the BGP protocol does.Performance of CNS can be characterized by the fraction of Autonomous Systems that successfully locate a requested content and by the average number of CNS Servers explored during the search phase. A C-based simulator of CNS is developed and is run over real ASes topologies provided by the Center for Applied Internet Data Analysis to provide estimates of both performance indexes. Preliminary performance and sensitivity results show the CNS approach is promising and can be efficiently implemented by incrementally deploying CNS Servers

ETSI SmartM2M Technical Report 103714: Study for oneM2M Discovery and Query use cases and requirements

The oneM2M system has implemented basic native discovery capabilities. In order to enhance the semantic capabilities of the oneM2M architecture by providing solid contributions to the oneM2M standards, four Technical Reports have been developed. Each of them is the outcome of a special study phase: requirements, study, simulation and standardization phase. The present document covers the first phase and provides the basis for the other documents.The use cases specified in the present document lead to potential requirements, which extend the existing requirements of the use case documented in oneM2M TR-0001 [i.19], clause 12.9 with a focus on the discovery and query capabilities, introducing a direct relation with the semantic aspects and enabling more sophisticated semantic queries as e.g. a capability in the CSE, that takes routing decisions for forwarding a received Advanced Semantic Discovery Query.oneM2M has currently native discovery capabilities that work properly only if the search is related to specific known sources of information (e.g. searching for the values of a known set of containers) or if the discovery is well scoped and designed (e.g. the lights in a house). When oneM2M is used to discover wide sets of data or unknown sets of data, the functionality is typically integrated by ad hoc applications that are expanding the oneM2M functionality. This means that this core function may be implemented with different flavours and this is not optimal for interworking and interoperability.The objective of the present document [i.1] in conjunction with three other ones [i.2], [i.3] and [i.4] is the study and development of semantic Discovery and Query capabilities for oneM2M and its contribution to the oneM2M standard.The goal is to enable an easy and efficient discovery of information and a proper interworking with external source/consumers of information (e.g. a distributed data base in a smart city or in a firm), or to directly search information in the oneM2M system for big data purposes

ETSI SmartM2M Technical Report 103716; oneM2M Discovery and Query solution(s) simulation and performance evaluation

oneM2M has currently native discovery capabilities that work properly only if the search is related to specific known sources of information (e.g. searching for the values of a known set of containers) or if the discovery is well scoped and designed (e.g. the lights in a house). When oneM2M is used to discover wide sets of data or unknown sets of data, the functionality is typically integrated by ad hoc applications that are expanding the oneM2M functionality. This means that this core function may be implemented with different flavours and this is not optimal for interworking and interoperability.The objective of the present document [i.3] in conjunction with three other ones ETSI TR 103 714 [i.1], ETSITR 103 715 [i.2] and ETSI TR 103 717 [i.4] is the study and development of semantic Discovery and Query capabilities for oneM2M and its contribution to the oneM2M standard.The goal is to enable an easy and efficient discovery of information and a proper interworking with external source/consumers of information (e.g. a distributed data base in a smart city or in a firm), or to directly search information in the oneM2M system for big data purposes.A simulation phase is conducted in parallel and "circular" feedback with respect to the study phase, with the goal to provide a proof of concept, run suitable scenarios provided by previous phases and a performance evaluation to support the selection/development of the Discovery and Query solution. The simulator and the simulation results are documented in ETSI TR 103 716 [i.3] (the present document). An extract of the simulation results is included ETSI TR 103 715 [i.2] and ETSI TR 103 717 [i.4]. A selection of the use cases includes a set of oneM2M relevant configurations scenarios to be considered for the simulation activity described below