Abstract
Bugs in multithreaded application can be elusive. They are often hard to trace and replicate, given the usual non-determinism and irreproducibility of scheduling decisions at runtime. We present Cooperari, a tool for deterministic testing of multithreaded Java code based on cooperative execution. In a cooperative execution, threads voluntarily suspend (yield) at interference points (e.g., lock acquisition), and code between two consecutive yield points of each thread always executes serially as a transaction. A cooperative scheduler takes over control at yield points and deterministically selects the next thread to run. An application test runs multiple times, until it either fails or the state-space of schedules is deemed as covered by a configurable policy that is responsible for the scheduling decisions. Beyond failed assertions in software tests, deadlocks and races are also detected as soon as they are exposed in the cooperative execution. Cooperari effectively finds, characterizes, and deterministically reproduces bugs that are not detected under unconstrained preemptive semantics, as illustrated by standard benchmark examples.

Abstract
Real-time monitoring applications deployed in Low-power and Lossy Networks may generate flows sensitive to delay, where the information is useful for the destination only if it is received within a strict delay boundary. Data packets that will likely miss the application deadline could be discarded during their routing through the network or even be not transmitted at all, thus contributing for a better usage of the network resources. This paper presents RA-EEDEM, a set of modifications made to RPL that improve the End-to-End Delay (EED) estimation accuracy. The RA-EEDEM modifications include changes to the RPL metrics and to its Objective Function (OF). The results show that RA-EEDEM improves the accuracy of EED estimation while minimizing its impact on the average EED and Packet Reception Ratio (PRR).

Abstract
The need for better adaptation of networks to transported flows has led to research on new approaches such as content aware networks and network aware applications. In parallel, recent developments of multimedia and content oriented services and applications such as IPTV, video streaming, video on demand, and Internet TV reinforced interest in multicast technologies. IP multicast has not been widely deployed due to interdomain and QoS support problems; therefore, alternative solutions have been investigated. This article proposes a management driven hybrid multicast solution that is multi-domain and media oriented, and combines overlay multicast, IP multicast, and P2P. The architecture is developed in a content aware network and network aware application environment, based on light network virtualization. The multicast trees can be seen as parallel virtual content aware networks, spanning a single or multiple IP domains, customized to the type of content to be transported while fulfilling the quality of service requirements of the service provider.

Abstract
The reduction of carbon emission is imperative towards the Green Internet. Hence, this paper proposes and validates green routing metrics focused on improving energy efficiency of multi-hop approaches in heterogeneous wireless peoplecentric environments. The validation is carried out through discrete event simulations based on real data set traces and controlled random topologies for the specific case of AODV. Results show improvements to network lifetime without penalizing other performance metrics.

Abstract
Traffic prediction is a fundamental tool that captures the inherent behavior of a network and can be used for monitoring and managing network traffic. Online traffic prediction is usually performed based on large historical data used in training algorithms. This may not be suitable to highly volatile environments, such as cloud computing, where the coupling between observations decreases quickly with time. We propose a dynamic window size approach for traffic prediction that can be incorporated with different traffic predictions mechanisms, making them suitable to online traffic prediction by adapting the amount of traffic that must be analyzed in accordance to the variability of data traffic. The evaluation of the proposed solution is performed for several prediction mechanisms by assessing the Normalized Mean Square Error and Mean Absolute Percent Error of predicted values over observed values from a real cloud computing data set, collected by monitoring the utilization of Dropbox.

Abstract
We characterize the secrecy level of communication under Uncoordinated Frequency Hopping, a spread spectrum scheme where a transmitter and a receiver randomly hop through a set of frequencies with the goal of deceiving an adversary. In our work, the goal of the legitimate parties is to land on a given frequency without the adversary eavesdroppers doing so, therefore being able to communicate securely in that period, that may be used for secret-key exchange. We also consider the effect on secrecy of the availability of friendly jammers that can be used to obstruct eavesdroppers by causing them interference. Our results show that tuning the number of frequencies and adding friendly jammers are effective countermeasures against eavesdroppers.