Ramana V. Polavarapu

CAESAR: A Context-Aware, Social Recommender System for Low-End Mobile Devices

Mobile-enabled social networks applications are becoming increasingly popular. Most of the current social network applications have been designed for high-end mobile devices, and they rely upon features such as GPS, capabilities of the world wide web, and rich media support. However, a significant fraction of mobile user base, especially in the developing world, own low-end devices that are only capable of voice and short text messages (SMS). In this context, a natural question is whether one can design meaningful social network-based applications that can work well with these simple devices, and if so, what the real challenges are. Towards answering these questions, this paper presents a social network-based recommender system that has been explicitly designed to work even with devices that just support phone calls and SMS. Our design of the social network based recommender system incorporates three features that complement each other to derive highly targeted ads. First, we analyze information such as customers address books to estimate the level of social affinity among various users. This social affinity information is used to identify the recommendations to be sent to an individual user. Second, we combine the social affinity information with the spatio-temporal context of users and historical responses of the user to further refine the set of recommendations and to decide when a recommendation would be sent. Third, social affinity computation and spatio-temporal contextual association are continuously tuned through user feedback. We outline the challenges in building such a system, and outline approaches to deal with such challenges.

On the partial caching of streaming video

Video objects are much larger in size than traditional web objects and tend not to be viewed in entirety. Hence, caching them partially is a promising approach. Also, the projected growth in video traffic over wireless cellular networks calls for resource-efficient caching mechanisms in the wireless edge to lower traffic over the cellular backhaul and peering links and their associated costs. An evaluation of traditional partial caching solutions proposed in the literature shows that known solutions are not robust to video viewing patterns, increasing object pool size, changing object popularity, or limitation in the resources available for caching at the wireless network elements. In this paper, to overcome the limitations, we propose a novel approach that adopts a flexible segmentation policy and generalizes both LRU and LFU when applied to segmented accesses, and in our simulations, is shown to significantly lower wireless backhaul traffic (by around 20-30% and in some cases even higher).

Organizing for Delivery of IT Services Having Moderate Task Novelty

The grouping of IT Services by degrees of novelty and the appropriate organizational structures are explained. For IT Services having moderate levels of novelty, the cellular model of delivery may be appropriate, and the considerations involved in designing the appropriate organizational structure for cellular delivery is explained. A simulation framework is proposed for determining the appropriate organizational structure. This simulation framework includes a model for determining the optimal way to allocate tasks to cells, and also a procedure for determining a optimal design of cells.