The 18th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt 2020)

The 14th Workshop on Spatial Stochastic Models for Wireless Networks (SPASWIN)

Session SPASWIN-Papers

SPASWIN Session

Conference
12:01 AM — 11:59 PM EEST
Local
Jun 18 Thu, 5:01 PM — 4:59 PM EDT

Coverage Probability in Wireless Networks with Determinantal Scheduling

B. Błaszczyszyn, A. Brochard and H.P. Keeler

0
We propose a new class of algorithms for randomly scheduling network transmissions. The idea is to use (discrete) de-terminantal point processes (subsets) to randomly assign medium access to various repulsive subsets of potential transmitters. This approach can be seen as a natural extension of (spatial) Aloha, which schedules transmissions independently. Under a general path loss model and Rayleigh fading, we show that, similarly to Aloha, they are also subject to elegant analysis of the coverage probabilities and transmission attempts (also known as local delay). This is mainly due to the explicit, determinantal form of the conditional (Palm) distribution and closed-form expressions for the Laplace functional of determinantal processes. Interesiingly, the derived performance characteristics of the network are amenable to various optimizations of the scheduling parameters, which are determinantal kernels, allowing the use of techniques developed for statistical learning with determinantal processes. Well-established sampling algorithms for determinantal processes can be used to cope with implementation issues, which is is beyond the scope of this paper, but it creates paths for further research.

Malware Propagation in Urban D2D Networks

A. Hinsen, B. Jahnel, E. Cali, and J.-P. Wary

0
We introduce and analyze models for the propagation of malware in pure D2D networks given via stationary Cox–Gilbert graphs. Here, the devices form a Poisson point process with random intensity measure λΛ, where Λ is stationary and given, for example, by the edge-length measure of a realization of a Poisson–Voronoi tessellation that represents an urban street system. We assume that, at initial time, a typical device at the center of the network carries a malware and starts to infect neighboring devices after random waiting times. Here we focus on Markovian models, where the waiting times are exponential random variables, and non-Markovian models, where the waiting times feature strictly positive minimal and finite maximal waiting times. We present numerical results for the speed of propagation depending on the system parameters. In a second step, we introduce and analyze a counter measure for the malware propagation given by special devices called white knights, which have the ability, once attacked, to eliminate the malware from infected devices and turn them into white knights. Based on simulations, we isolate parameter regimes in which the malware survives or is eliminated, both in the Markovian and non-Markovian setting.

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