Method and system for detecting common attributes of network upgrades

A system and method identify a set of rules for determining a commonality of attributes across different behavior changes for a network. The system performs the method by receiving a set of data correlating network triggers to performance changes of one or more network devices. The set of data further includes an indication of a sign of the performance change for each of the network devices based on the triggers. The method further includes extracting a set of rules relating to a set of relationships between the triggers and the performance changes. The rules identify a commonality of the performance changes for multiple network devices based on the triggers.Board of Regents, University of Texas Syste

Method and apparatus for managing quality of service

A system that incorporates teachings of the present disclosure may include, for example, obtaining regression coefficients that quantify a relationship between premises feedback and first network and premises performance indicators, obtaining second network performance indicators for the network elements, obtaining second premises performance indicators for the customer premises equipment, and predicting customer complaints by applying the obtained regression coefficients to at least the second network performance indicators and the second premises performance indicators. Other embodiments are disclosed.Board of Regents, University of Texas Syste

Genetic Regulation of N6-Methyladenosine-RNA in Mammalian Gametogenesis and Embryonic Development

Emerging evidence shows that m(6)A is the most abundant modification in eukaryotic RNA molecules. It has only recently been found that this epigenetic modification plays an important role in many physiological and pathological processes, such as cell fate commitment, immune response, obesity, tumorigenesis, and relevant for the present review, gametogenesis. Notably the RNA metabolism process mediated by m(6)A is controlled and regulated by a series of proteins termed writers, readers and erasers that are highly expressed in germ cells and somatic cells of gonads. Here, we review and discuss the expression and the functional emerging roles of m(6)A in gametogenesis and early embryogenesis of mammals. Besides updated references about such new topics, readers might find in the present work inspiration and clues to elucidate epigenetic molecular mechanisms of reproductive dysfunction and perspectives for future research

Interest-based content retrieval and dissemination in distributed environments

In many networked applications, ranging from information dissemination services to distributed simulations and virtual worlds to file-sharing applications, a vast amount of information can potentially be accessed by a large number of widely distributed network users. In most cases, each user is interested in only a small subset of all information available. This stimulates tremendous demand for interest-based content retrieval and content dissemination. In this thesis, we first investigate interest-based content retrieval where information consumers actively seek content of interest and then initiate content transmission. We examine such a pull mechanism by analyzing various types of peer-peer file-sharing systems, in which peers first locate their files of interest and then issue requests to download matched files. We next investigate interest-based content dissemination mechanisms in which information providers publish (push) their content through a so-called publish/subscribe (pub/sub) system, and information consumers receive content of interest to them from this system. In particular, we study a method of utilizing multiple multicast groups to scope content dissemination. We also consider an alternative approach that provides content filtering along the content-delivery paths based on the requests of receivers to perform interest-based content dissemination

Finding Critical Traffic Matrices

traffic matrix represents the amount of traffic between origin and destination in a network. It has tremendous potential utility for many IP network engineering applications, such as network survivability analysis, traffic engineering, and capacity planning. Recent advances in traffic matrix estimation have enabled ISPs to measure traffic matrices continuously. Yet a major challenge remains towards achieving the full potential of traffic matrices. In practical networking applications, it is often inconvenient (if not infeasible) to deal with hundreds or thousands of measured traffic matrices. So it is highly desirable to be able to extract a small number of "critical" traffic matrices. Unfortunately, we are not aware of any good existing solutions to this problem (other than a few ad hoc heuristics). This seriously limits the applicability of traffic matrices. To bridge the gap between the measurement and the actual application of traffic matrices, we study the critical traffic matrices selection (CritMat) problem in this paper. We developed a mathematical problem formalization after identifying the key requirements and properties of CritMat in the context of network design and analysis. Our complexity analysis showed that CritMat is NP-hard. We then developed several clustering-based approximation algorithms to CritMat. We evaluated these algorithms using a large collection of real traffic matrices collected in AT&T's North American backbone network. Our results demonstrated that these algorithms are very effective and that a small number (e.g., 12) of critical traffic matrices suffice to yield satisfactory performance

A demand adaptive and locality aware (dala) streaming media server cluster architecture

The wide availability of broadband networking technologies such as cable modems and DSL coupled with the growing popularity of the Internet has led to a dramatic increase in the availability and the use of online streaming media. With the “last mile ” network bandwidth no longer a constraint, the bottleneck for video streaming has been pushed closer to the server. Streaming high quality audio and video to a myriad of clients imposes significant resource demands on the server. In this work, we propose a demand adaptive and locality aware (DALA) clustered media server architecture that can dynamically allocate resources to adapt to changing demand and also maximize the number of clients serviced by the server cluster. Moreover, our design exploits temporal locality among requests by dispatching newly arriving requests to servers that are already servicing prior requests for those objects, thereby extracting the benefits of locality. We explore the efficacy of the DALA clustered architecture using simulations. Our simulation results show that DALA is highly adaptive, exhibits significant performance gains when compared to static schemes, and has a low system overhead. Our results demonstrate that DALA is a simple, yet effective approach for designing clustered media servers.

Joint Traffic Blocking and Routing Under Network Failures and Maintenances

Under device failures and maintenance activities, network resources reduce and congestion may arise inside networks. In this paper, we study a dual approach that combines traffic blocking (rate-limiting) at the edge of a network and traffic rerouting inside the network. We formulate a joint ingress blocking and routing optimization problem and develop mechanisms to introduce blocking differentiations among users with different service priorities and with different level of impact to network congestions. Our evaluation result shows that by blocking only a small fraction of traffic, one can greatly reduce network congestion under severe failures and maintenance activities. Our solution efficiently identifies the optimal blocking among heterogeneous users and achieves much better performance in comparison with proportional traffic blocking. The proposed algorithms can be easily adopted by network service providers in their traffic engineering practices