This paper presents an analytical model to compute the average service time and jitter experienced by a packet when transmitted in a saturated IEEE 802.11 ad hoc network. In contrast to traditional work in the literature, in which a distribution is usually fitted or assumed, we use a bottom-up approach and build the first two moments of the service time based on the IEEE 802.11 binary exponential backoff algorithm and the events underneath its operation. Our model is general enough to be applied to any type of IEEE 802.11 wireless ad hoc network where the channel state probabilities driving a node's backoff operation are known. We apply our model to saturated single-hop ad hoc networks under ideal channel conditions. We validate our model through extensive simulations and conduct a performanceevaluation of a node's average service time and jitter for both direct sequence and frequency-hopping spread spectrum physical layers.

This work addresses the problem of using Unmanned Aerial Vehicles (UAV) to deploy a wireless aerial relay communications infrastructure for stations scattered on the ground. In our problem, every station in the network must be assigned to a single UAV, which is responsible for handling all data transfer on behalf of the stations that are assigned to it. Consequently, the placement of UAVs is key to achieving both network coverage and the maximization of the aggregate link capacities between UAVs and stations, and among the UAVs themselves. Because the complexity of this problem increases significantly with the number of stations to cover, for a given fixed number p of available UAVs, we model it as a single allocation p-hub median optimization problem, and we propose a hybrid metaheuristic algorithm to solve it. A series of numerical experiments illustrate the efficiency of the proposed algorithm against traditional optimization tools, which achieves high-quality results in very short time intervals, thus making it an attractive solution for real-world application scenarios.

We introduce the Selective-Awakening MAC (SA‐MAC) protocol which is a synchronized duty‐cycled protocol with pipelined scheduling for Linear Sensor Networks (LSNs). In the proposed protocol, nodes selectively awake depending on node density and traffic load conditions and on the state of the buffers of the receiving nodes. In order to characterize the performance of the proposed protocol, we present a Discrete‐Time Markov Chain‐based analysis that is validated through extensive discrete‐event simulations. Our results show that SA‐MAC significantly outperforms previous proposals in terms of energy consumption, throughput, and packet loss probability. This is particularly true under high node density and high traffic load conditions, which are expected to be common scenarios in the context of IoT applications. We also present an analysis by grade (i.e., the number of hops to the sink, which is located at one end of the LSN) that reveals that LSNs exhibit heterogeneous performance depending on the nodes’ grade. Such results can be used as a design guideline for future LSN implementations.