Abstract

Abstract
In this article we discuss three different notions of linearity: syntactical, operational and denotational. We briefly define each notion of linearity, pointing out some of the main results in the area, and describe applications of linear languages and type systems.

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
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.