An analytical packet/flow-level modelling approach for wireless LANs with Quality-of-Service support

We present an analytical packet/flow-level modelling approach for the performance analysis of IEEE 802.11e WLAN, where we explicitly take into account QoS differentiation mechanisms based on minimum contention window size values and Arbitration InterFrame Space (AIFS) values, as included in the Enhanced Distributed Channel Access (EDCA) protocol of the 802.11e standard. We first enhance the packet-level approach previously used for best-effort WLANs to include traffic classes with different QoS requirements. The packet-level model approach yields service weights that discriminate among traffic classes. From these observations, the packet/flow-level model for 802.11e is the \textit{generalized} discriminatory processor-sharing (GDPS) queueing model where the state-dependent system capacity is distributed among active traffic classes according to state-dependent priority weights. Extensive simulations show that the discriminatory processor-sharing model closely represents the flow behavior of 802.11e

Complex network statistics to the design of fire breaks for the control of fire spreading

A computational approach for identifying efficient fuel breaks partitions for the containment of fire incidents in forests is proposed. The approach is based on the complex networks statistics, namely the centrality measures and cellular automata modeling. The efficiency of various centrality statistics, such as betweenness, closeness, Bonacich and eigenvalue centrality to select fuel breaks partitions vs. the random-based distribution is demonstrated. Two examples of increasing complexity are considered: (a) an artificial forest of randomly distributed density of vegetation, and (b) a patch from the area of Vesuvio, National Park of Campania, Italy. Both cases assume flat terrain and single type of vegetation. Simulation results over an ensemble of lattice realizations and runs show that the proposed approach appears very promising as it produces statistically significant better outcomes when compared to the random distribution approach

A tight bound on the throughput of queueing networks with blocking

In this paper, we present a bounding methodology that allows to compute a tight lower bound on the cycle time of fork--join queueing networks with blocking and with general service time distributions. The methodology relies on two ideas. First, probability masses fitting (PMF) discretizes the service time distributions so that the evolution of the modified network can be modelled by a Markov chain. The PMF discretization is simple: the probability masses on regular intervals are computed and aggregated on a single value in the orresponding interval. Second, we take advantage of the concept of critical path, i.e. the sequence of jobs that covers a sample run. We show that the critical path can be computed with the discretized distributions and that the same sequence of jobs offers a lower bound on the original cycle time. The tightness of the bound is shown on computational experiments. Finally, we discuss the extension to split--and--merge networks and approximate estimations of the cycle time.queueing networks, blocking, throughput, bound, probability masses fitting, critical path.

zCap: a zero configuration adaptive paging and mobility management mechanism

Today, cellular networks rely on fixed collections of cells (tracking areas) for user equipment localisation. Locating users within these areas involves broadcast search (paging), which consumes radio bandwidth but reduces the user equipment signalling required for mobility management. Tracking areas are today manually configured, hard to adapt to local mobility and influence the load on several key resources in the network. We propose a decentralised and self-adaptive approach to mobility management based on a probabilistic model of local mobility. By estimating the parameters of this model from observations of user mobility collected online, we obtain a dynamic model from which we construct local neighbourhoods of cells where we are most likely to locate user equipment. We propose to replace the static tracking areas of current systems with neighbourhoods local to each cell. The model is also used to derive a multi-phase paging scheme, where the division of neighbourhood cells into consecutive phases balances response times and paging cost. The complete mechanism requires no manual tracking area configuration and performs localisation efficiently in terms of signalling and response times. Detailed simulations show that significant potential gains in localisation effi- ciency are possible while eliminating manual configuration of mobility management parameters. Variants of the proposal can be implemented within current (LTE) standards