We introduce FlowComb, a network management framework that helps Big Data processing applications, such as Hadoop, achieve high utilization and low data processing times. FlowComb predicts application network transfers, sometimes before they start, by using software agents installed on application servers and while remaining completely transparent to the application. A centralized decision engi...

An algorithm that can tackle time dependent vehicle routing problems with hard or soft time windows without any alteration in its structure is presented. Analytical and experimental results indicate that average computational time increases proportionally to the number of customers squared. New replicable test problems that capture the typical speed variations of congested urban settings are pr...

In this paper we provide low-congested Interval Routing Schemes (IRS) for some common interconnection networks such as butterflies, wrapped butterflies and cube connected cycles. In particular, by exploiting their hypercube-like structure, we show that 1-IRS and 2-IRS are already sufficient to get schemes with a congestion which is at most c times the optimal one, for low constant values of c. ...

Observation of a 4-mile long, inhomogeneous, congested traffic stream revealed that vehicle accumulations between detectors vary with flow in a predictable way, and that a macroscopic kinematic wave with a reproducible speed exists in queues despite unusual traffic behavior. As a result, time-dependent vehicle trip times and accumulations inside long queues (and the queue length itself) can be ...