Maximizing Profit in Green Cellular Networks through Collaborative Games

In this paper, we deal with the problem of maximizing the profit of Network Operators (NOs) of green cellular networks in situations where Quality-of-Service (QoS) guarantees must be ensured to users, and Base Stations (BSs) can be shared among different operators. We show that if NOs cooperate among them, by mutually sharing their users and BSs, then each one of them can improve its net profit. By using a game-theoretic framework, we study the problem of forming stable coalitions among NOs. Furthermore, we propose a mathematical optimization model to allocate users to a set of BSs, in order to reduce costs and, at the same time, to meet user QoS for NOs inside the same coalition. Based on this, we propose an algorithm, based on cooperative game theory, that enables each operator to decide with whom to cooperate in order to maximize its profit. This algorithms adopts a distributed approach in which each NO autonomously makes its own decisions, and where the best solution arises without the need to synchronize them or to resort to a trusted third party. The effectiveness of the proposed algorithm is demonstrated through a thorough experimental evaluation considering real-world traffic traces, and a set of realistic scenarios. The results we obtain indicate that our algorithm allows a population of NOs to significantly improve their profits thanks to the combination of energy reduction and satisfaction of QoS requirements.Comment: Added publisher info and citation notic

Forensic Analysis of the ChatSecure Instant Messaging Application on Android Smartphones

We present the forensic analysis of the artifacts generated on Android smartphones by ChatSecure, a secure Instant Messaging application that provides strong encryption for transmitted and locally-stored data to ensure the privacy of its users. We show that ChatSecure stores local copies of both exchanged messages and files into two distinct, AES-256 encrypted databases, and we devise a technique able to decrypt them when the secret passphrase, chosen by the user as the initial step of the encryption process, is known. Furthermore, we show how this passphrase can be identified and extracted from the volatile memory of the device, where it persists for the entire execution of ChatSecure after having been entered by the user, thus allowing one to carry out decryption even if the passphrase is not revealed by the user. Finally, we discuss how to analyze and correlate the data stored in the databases used by ChatSecure to identify the IM accounts used by the user and his/her buddies to communicate, as well as to reconstruct the chronology and contents of the messages and files that have been exchanged among them. For our study we devise and use an experimental methodology, based on the use of emulated devices, that provides a very high degree of reproducibility of the results, and we validate the results it yields against those obtained from real smartphones

A Game-Theoretic Approach to Coalition Formation in Fog Provider Federations

In this paper we deal with the problem of making a set of Fog Infrastructure Providers (FIPs) increase their profits when allocating their resources to process the data generated by IoT applications that need to meet specific QoS targets in face of time-varying workloads. We show that if FIPs cooperate among them, by mutually sharing their workloads and resources, then each one of them can improve its net profit. By using a game-theoretic framework, we study the problem of forming stable coalitions among FIPs. Furthermore, we propose a mathematical optimization model for profit maximization to allocate IoT applications to a set of FIPs, in order to reduce costs and, at the same time, to meet the corresponding QoS targets. Based on this, we propose an algorithm, based on cooperative game theory, that enables each FIP to decide with whom to cooperate in order to increase its profits. The effectiveness of the proposed algorithm is demonstrated through an experimental evaluation considering various workload intensities. The results we obtain from these experiments show the ability of our algorithm to form coalitions of FIPs that are stable and profitable in all the scenarios we consider

Melusin is a new muscle-specific interactor for beta(1) integrin cytoplasmic domain.

Here we describe the isolation and partial characterization of a new muscle-specific protein (Melusin) which interacts with the integrin cytoplasmic domain. The cDNA encoding Melusin was isolated in a two-hybrid screening of a rat neonatal heart library using beta(1)A and beta(1)D integrin cytoplasmic regions as baits. Melusin is a cysteine-rich cytoplasmic protein of 38 kDa, with a stretch of acidic amino acid residues at the extreme carboxyl-terminal end. In addition, putative binding sites for SH3 and SH2 domains are present in the amino-terminal half of the molecule. Chromosomic analysis showed that melusin gene maps at Xq12.1/13 in man and in the synthenic region X band D in mouse. Melusin is expressed in skeletal and cardiac muscles but not in smooth muscles or other tissues. Immunofluorescence analysis showed that Melusin is present in a costamere-like pattern consisting of two rows flanking alpha-actinin at Z line. Its expression is up-regulated during in vitro differentiation of the C2C12 murine myogenic cell line, and it is regulated during in vivo skeletal muscle development. A fragment corresponding to the tail region of Melusin interacted strongly and specifically with beta(1) integrin cytoplasmic domain in a two-hybrid test, but the full-length protein did not. Because the tail region of Melusin contains an acidic amino acid stretch resembling high capacity and low affinity calcium binding domains, we tested the possibility that Ca(2+) regulates Melusin-integrin association. In vitro binding experiments demonstrated that interaction of full-length Melusin with detergent-solubilized integrin heterodimers occurred only in absence of cations, suggesting that it can be regulated by intracellular signals affecting Ca(2+) concentration

dcsr-workload-characterization

A set of reusable R libraries aimed at performing statistical analysis of workloads characterizing different computing system