Abstract: An optimum configuration of resources in a network function virtualisation data network is identified by assembling candidate configurations of resources (243), each configuration being an arrangement of the resources into clusters selected such that each cluster provides one or more required services, (212, 213) and assessing the candidate configurations (step 400) to identify an optimum configuration, the assessment of each configuration including measurement of latency (195) in physical links between the resources and, for each candidate configuration, determination of the total latency between the resources within each cluster of the configuration, for a predicted level and pattern of traffic associated with the required service to be operated by each cluster.

Abstract: This invention relates to methods and systems for monitoring mobile service quality in a mobile network and also for determining parts of a mobile network which need expansion or upgrade. Embodiments of the invention monitor the market impact and/or service quality, and determine an expansion ranking. The market impact, service quality and/or expansion ranking may view the network from a plurality of perspectives, including a location perspective, an historical time perspective, a future time perspective and/or a network element type perspective. The results of the monitoring and determining can be acted on by predetermined rules and/or actions to derive a list of prioritized expansion tasks for the network.

Abstract: The present invention provides a method which can be used to optimise the delivery of series over communications networks. Tasks which need to executed within a short timescale and those which are not due to be executed for a long time are excluded from the optimisation process. A score is determined, using fuzzy logic, for each task and its related resources and for each resource and its related tasks. This score is then used to determined which tasks should be optimised.

Abstract: An optimum configuration of resources in a network function virtualisation data network is identified by assembling candidate configurations of resources (243), each configuration being an arrangement of the resources into clusters selected such that each cluster provides one or more required services, (212, 213) and assessing the candidate configurations (step 400) to identify an optimum configuration, the assessment of each configuration including measurement of latency (195) in physical links between the resources and, for each candidate configuration, determination of the total latency between the resources within each cluster of the configuration, for a predicted level and pattern of traffic associated with the required service to be operated by each cluster.

Abstract: This invention relates to methods and systems for monitoring mobile service quality in a mobile network and also for determining parts of a mobile network which need expansion or upgrade. Embodiments of the invention monitor the market impact and/or service quality, and determine an expansion ranking. The market impact, service quality and/or expansion ranking may view the network from a plurality of perspectives, including a location perspective, an historical time perspective, a future time perspective and/or a network element type perspective. The results of the monitoring and determining can be acted on by predetermined rules and/or actions to derive a list of prioritized expansion tasks for the network.

Abstract: The present invention provides a method which can be used to optimise the delivery of series over communications networks. Tasks which need to executed within a short timescale and those which are not due to be executed for a long time are excluded from the optimisation process. A score is determined, using fuzzy logic, for each task and its related resources and for each resource and its related tasks. This score is then used to determined which tasks should be optimised.

Abstract: In response to requests for their use of the resources by the applications, resources are first allocated to “inelastic” requests specified for performance at a specific time slot. A baseline allocation of resources is then determined which is the minimum amount of capacity that has to be used for efficient operation of the resources required to meet the requests. This baseline will include some additional capacity as the minimum efficient capacity is less than the maximum capacity. “Elastic” requests, specified for performance within a predetermined time range comprising two or more of the set of time slots, are then allocated so as to prioritize the use of this spare capacity, bringing actual usage up to at least the baseline allocation of resources. If further capacity is required to meet all the inelastic requests, further capacity is allocated and the baseline redefined to include it.

Abstract: In response to requests for their use of the resources by the applications, resources are first allocated to “inelastic” requests specified for performance at a specific time slot. A baseline allocation of resources is then determined which is the minimum amount of capacity that has to be used for efficient operation of the resources required to meet the requests. This baseline will include some additional capacity as the minimum efficient capacity is less than the maximum capacity. “Elastic” requests, specified for performance within a predetermined time range comprising two or more of the set of time slots, are then allocated so as to prioritise the use of this spare capacity, bringing actual usage up to at least the baseline allocation of resources. If further capacity is required to meet all the inelastic requests, further capacity is allocated and the baseline redefined to include it.