The Ohio State University

Other

John Tadrous

Hesham El Gamal

Nayer Wanas

Kareem Youssef

Ahmed Abou-Elkheir

Hakem Zaid

Atilla Eryilmaz

Methods and systems are provided for optimizing the use of network bandwidth by a mobile device. In one embodiment, a system is provided that includes a mobile application client. The mobile application client may log information regarding content requests to a content log and may log network connection statuses for the mobile device. The system may analyze content consumption of a user of the mobile device based on the content log and may create a user profile. The system may also compile a prefetching schedule based on the user profile and the prefetching schedule may be provided to the mobile device. The mobile device may prefetch content at least partially in accordance with the prefetching schedule.

System and method for efficient use of network bandwidth

A system for optimizing the use of network bandwidth by a mobile device including a mobile application client, which resides on the mobile device, and is connected to a cloud server, wherein the system analyzes user content consumption, provides a prefetching schedule to the mobile device, and the mobile device prefetches content partially in accordance with the schedule. A method of optimizing the use of network bandwidth using the system is also provided.

System and method for efficient use of network bandwidth based on user profiles and other data

A system and method for allocating resources in a network is disclosed. The system and method comprises a proactive resource allocation framework in which the predictability of user behavior is exploited to balance the network traffic over time and to reduce the bandwidth required to achieve a given blocking/outage probability. The disclosed proactive resource allocation framework avoids limitations associated with off-peak demand and achieves a significant reduction in the peak to average demand ratio without relying on out of network users. It is based on a model in which smart devices are assumed to predict the arrival of new requests and submit them to the network T time slots in advance. Using tools from large deviation theory, the resulting prediction diversity gain is quantified to establish that the decay rate of the outage event probabilities increases linearly with the prediction duration T.

System and method for proactive resource allocation

Growing community of inventors

Columbus, OH, United States of America

John Tadrous