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In this paper, a cloud radio access network (C-RAN) is considered where the remote radio heads (RRHs) are separated from the baseband units which form a common pool of computational resource units. Depending on their capacity, the RRHs may form one or more clusters. Each RRH accommodates multiservice traffic, i.e., calls from different service-classes with different radio and computational resource requirements. Arriving calls follow a Poisson process and simultaneously require radio and computational resource units in order to be accepted in the serving RRH. If their resource requirements cannot be met then calls are blocked and lost. Otherwise, calls remain in the serving RRH for a generally distributed service time. Assuming the single-cluster C-RAN, we model it as a multiservice loss system, prove that a product form solution exists for the steady-state probabilities and determine call blocking probabilities via an efficient convolution algorithm whose accuracy is validated via simulation. Furthermore, we generalize the previous multiservice loss model by considering the more complex multi-cluster case where RRHs of the same capacity are grouped in different clusters.

Designing, dimensioning, and optimization of communication networks resources and services have been inseparable parts of the development of telecommunications since the very beginning of their existence [...]

IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is a popular routing protocol used in wireless sensor networks and in the Internet of Things (IoT). RPL was standardized by the IETF in 2012 and has been designed for devices with limited resources and capabilities. Open-source RPL implementations are supported by popular IoT operating systems (OS), such as ContikiOS and TinyOS. In this work, we investigate the possibility of battery drain Denial-of-Service (DoS) attacks in the RPL implementation of ContikiOS. In particular, we use the popular Cooja simulator and implement two types of DoS attacks, particularly version number modification and “Hello” flooding. We demonstrate the impact of these attacks on the power consumption of IoT devices. Finally, we discuss potential defenses relying on distributed intrusion detection modules.

In recent years, we have been experiencing fast proliferation of different types of ransomware targeting home users, companies and even critical telecommunications infrastructure elements. Modern day ransomware relies on sophisticated infection, persistence and recovery prevention mechanisms. Some recent examples that received significant attention include WannaCry, Petya and BadRabbit. To design and develop appropriate defense mechanisms, it is important to understand the characteristics and the behavior of different types of ransomware. Dynamic analysis techniques are typically used to achieve that purpose, where the malicious binaries are executed in a controlled environment and are then observed. In this work, the dynamic analysis results focusing on the infamous WannaCry ransomware are presented. In particular, WannaCry is examined, during its execution in a purpose-built virtual lab environment, in order to analyze its infection, persistence, recovery prevention and propagation mechanisms. The results obtained may be used for developing appropriate detection and defense solutions for WannaCry and other ransomware families that exhibit similar behaviors

This paper proposes multirate teletraffic loss models of a link that accommodates different service-classes of elastic and adaptive calls. Calls follow a Poisson process, can tolerate bandwidth compression and have an exponentially distributed service time. When bandwidth compression occurs, the service time of new and in-service elastic calls increases. Adaptive calls do not alter their service time. All calls compete for the available link bandwidth under the combination of the Threshold (TH) and the Bandwidth Reservation (BR) policies. The TH policy can provide different QoS among service-classes by limiting the number of calls of a service-class up to a predefined threshold, which can be different for each service-class. The BR policy reserves part of the available link bandwidth to benefit calls of high bandwidth requirements. The analysis of the proposed models is based on approximate but recursive formulas, whereby authors determine call blocking probabilities and link utilization. The accuracy of the proposed formulas is verified through simulation and found to be very satisfactory.

We apply the max-min fairness policy (MMF) for elastic services with min and max bandwidth requirements (approximated MMF) not to a single link but to a whole connection-oriented network. To achieve it we propose a Call Admission Control (CAC) procedure consisting of several scenarios dependent on the number of paths between the origin-destination (O-D) network nodes. We evaluate the global network performance at the call level by comparing the maximum Call Blocking Probability (CBP) of the proposed scheme with that of a no fair bandwidth allocation policy scheme. Simulation results show significant traffic savings in the case of the approximated MMF policy.

In this paper, a multirate loss model for the calculation of time and call congestion probabilities in a Wideband Code Division Multiple Access (W-CDMA) cell is considered. It utilizes the Bandwidth Reservation (BR) policy and supports calls generated by an infinite or finite number of users. The BR policy achieves QoS equalization by equalizing congestion probabilities among calls of different service-classes. In the proposed models a multiple access interference is considered, and the notion of local blocking, user's activity and interference cancelation. Although the analysis of the proposed models reveals that the steady state probabilities do not have a product form solution, the authors show that the calculation of time and call congestion probabilities can be based on approximate but recursive formulas, whose accuracy is verified through simulation and found to be quite satisfactory.