Abstract:
A system (1000) is disclosed including a resource allocation optimization (RAO) platform (1002) for optimizing the allocation of resources in network (1004) for delivery of assets to user equipment devices (UEDs) (1012). The RAO platform (1002) determines probabilities that certain asset delivery opportunities (ADOs) will occur within a selected time window and uses these probabilities together with information concerning values of asset delivery to determine an optimal use of asset deliveries. In this regard, the RAO platform (1004) received historical data from repository (1014) that facilitates calculation of probabilities that ADOs will occur. Such information may be compiled based on asset delivery records for similar network environments in the recent past or over time.
Abstract:
A system (1000) is disclosed including a resource allocation optimization (RAO) platform (1002) for optimizing the allocation of resources in network (1004) for delivery of assets to user equipment devices (UEDs) (1012). The RAO platform (1002) determines probabilities that certain asset delivery opportunities (ADOs) will occur within a selected time window and uses these probabilities together with information concerning values of asset delivery to determine an optimal use of asset deliveries. In this regard, the RAO platform (1004) received historical data from repository (1014) that facilitates calculation of probabilities that ADOs will occur. Such information may be compiled based on asset delivery records for similar network environments in the recent past or over time.
Abstract:
A system (1000) is disclosed including a resource allocation optimization (RAO) platform (1002) for optimizing the allocation of resources in network (1004) for delivery of assets to user equipment devices (UEDs) (1012). The RAO platform (1002) determines probabilities that certain asset delivery opportunities (ADOs) will occur within a selected time window and uses these probabilities together with information concerning values of asset delivery to determine an optimal use of asset deliveries. In this regard, the RAO platform (1004) received historical data from repository (1014) that facilitates calculation of probabilities that ADOs will occur. Such information may be compiled based on asset delivery records for similar network environments in the recent past or over time.
Abstract:
A system (1000) is disclosed including a resource allocation optimization (RAO) platform (1002) for optimizing the allocation of resources in network (1004) for delivery of assets to user equipment devices (UEDs) (1012). The RAO platform (1002) determines probabilities that certain asset delivery opportunities (ADOs) will occur within a selected time window and uses these probabilities together with information concerning values of asset delivery to determine an optimal use of asset deliveries. In this regard, the RAO platform (1004) received historical data from repository (1014) that facilitates calculation of probabilities that ADOs will occur. Such information may be compiled based on asset delivery records for similar network environments in the recent past or over time.
Abstract:
A system (1000) is disclosed including a resource allocation optimization (RAO) platform (1002) for optimizing the allocation of resources in network (1004) for delivery of assets to user equipment devices (UEDs) (1012). The RAO platform (1002) determines probabilities that certain asset delivery opportunities (ADOs) will occur within a selected time window and uses these probabilities together with information concerning values of asset delivery to determine an optimal use of asset deliveries. In this regard, the RAO platform (1004) received historical data from repository (1014) that facilitates calculation of probabilities that ADOs will occur. Such information may be compiled based on asset delivery records for similar network environments in the recent past or over time.
Abstract:
Embodiments of the invention provide systems and methods for constructing a schedule well before the time of an asset delivery opportunity that associates a collection of one or more assets, potentially from multiple advertisers or asset providers, that are planned to play in each asset delivery opportunity. Specific rules for each device also determine which asset each will play, thereby ensuring that campaigns of total asset delivery and asset delivery pacing are approximately fulfilled. This scheduling can be accomplished using marketing data associated with each user device and can be prepared in a practicable period of time using reasonable processing resources.
Abstract:
A system (1000) is disclosed including a resource allocation optimization (RAO) platform (1002) for optimizing the allocation of resources in network (1004) for delivery of assets to user equipment devices (UEDs) (1012). The RAO platform (1002) determines probabilities that certain asset delivery opportunities (ADOs) will occur within a selected time window and uses these probabilities together with information concerning values of asset delivery to determine an optimal use of asset deliveries. In this regard, the RAO platform (1004) received historical data from repository (1014) that facilitates calculation of probabilities that ADOs will occur. Such information may be compiled based on asset delivery records for similar network environments in the recent past or over time.
Abstract:
A system (1000) is disclosed including a resource allocation optimization (RAO) platform (1002) for optimizing the allocation of resources in network (1004) for delivery of assets to user equipment devices (UEDs) (1012). The RAO platform (1002) determines probabilities that certain asset delivery opportunities (ADOs) will occur within a selected time window and uses these probabilities together with information concerning values of asset delivery to determine an optimal use of asset deliveries. In this regard, the RAO platform (1004) received historical data from repository (1014) that facilitates calculation of probabilities that ADOs will occur. Such information may be compiled based on asset delivery records for similar network environments in the recent past or over time.
Abstract:
A system (1000) is disclosed including a resource allocation optimization (RAO) platform (1002) for optimizing the allocation of resources in network (1004) for delivery of assets to user equipment devices (UEDs) (1012). The RAO platform (1002) determines probabilities that certain asset delivery opportunities (ADOs) will occur within a selected time window and uses these probabilities together with information concerning values of asset delivery to determine an optimal use of asset deliveries. In this regard, the RAO platform (1004) received historical data from repository (1014) that facilitates calculation of probabilities that ADOs will occur. Such information may be compiled based on asset delivery records for similar network environments in the recent past or over time.
Abstract:
Embodiments of the invention provide systems and methods for constructing a schedule well before the time of an asset delivery opportunity that associates a collection of one or more assets, potentially from multiple advertisers or asset providers, that are planned to play in each asset delivery opportunity. Specific rules for each device also determine which asset each will play, thereby ensuring that campaigns of total asset delivery and asset delivery pacing are approximately fulfilled. This scheduling can be accomplished using marketing data associated with each user device and can be prepared in a practicable period of time using reasonable processing resources.