Job Selection in a Network of Autonomous UAVs for Delivery of Goods

This article analyzes two classes of job selection policies that control how a network of autonomous aerial vehicles delivers goods from depots to customers. Customer requests (jobs) occur according to a spatio-temporal stochastic process not known by the system. If job selection uses a policy in which the first job (FJ) is served first, the system may collapse to instability by removing just one vehicle. Policies that serve the nearest job (NJ) first show such threshold behavior only in some settings and can be implemented in a distributed manner. The timing of job selection has significant impact on delivery time and stability for NJ while it has no impact for FJ. Based on these findings we introduce a methodological approach for decision-making support to set up and operate such a system, taking into account the trade-off between monetary cost and service quality. In particular, we compute a lower bound for the infrastructure expenditure required to achieve a certain expected delivery time. The approach includes three time horizons: long-term decisions on the number of depots to deploy in the service area, mid-term decisions on the number of vehicles to use, and short-term decisions on the policy to operate the vehicles

Packet Travel Times in Wireless Relay Chains under Spatially and Temporally Dependent Interference

We investigate the statistics of the number of time slots $T$ that it takes a packet to travel through a chain of wireless relays. Derivations are performed assuming an interference model for which interference possesses spatiotemporal dependency properties. When using this model, results are harder to arrive at analytically, but they are more realistic than the ones obtained in many related works that are based on independent interference models. First, we present a method for calculating the distribution of $T$. As the required computations are extensive, we also obtain simple expressions for the expected value $\mathrm{E} [T]$ and variance $\mathrm{var} [T]$. Finally, we calculate the asymptotic limit of the average speed of the packet. Our numerical results show that spatiotemporal dependence has a significant impact on the statistics of the travel time $T$. In particular, we show that, with respect to the independent interference case, $\mathrm{E} [T]$ and $\mathrm{var} [T]$ increase, whereas the packet speed decreases

Cooperative Relaying in Wireless Networks under Spatially and Temporally Correlated Interference

We analyze the performance of an interference-limited, decode-and-forward, cooperative relaying system that comprises a source, a destination, and $N$ relays, placed arbitrarily on the plane and suffering from interference by a set of interferers placed according to a spatial Poisson process. In each transmission attempt, first the transmitter sends a packet; subsequently, a single one of the relays that received the packet correctly, if such a relay exists, retransmits it. We consider both selection combining and maximal ratio combining at the destination, Rayleigh fading, and interferer mobility. We derive expressions for the probability that a single transmission attempt is successful, as well as for the distribution of the transmission attempts until a packet is transmitted successfully. Results provide design guidelines applicable to a wide range of systems. Overall, the temporal and spatial characteristics of the interference play a significant role in shaping the system performance. Maximal ratio combining is only helpful when relays are close to the destination; in harsh environments, having many relays is especially helpful, and relay placement is critical; the performance improves when interferer mobility increases; and a tradeoff exists between energy efficiency and throughput