Linear topologies arise naturally in the context of Internet-of-Things (IoT) applications for smart cities, where the infrastructure itself commonly has a linear or semi-linear structure. This is the case of buildings, public transportation systems, road infrastructure, and utility distribution networks. Given the prevalence of this type of topologies, several Medium Access Control (MAC) protocols have been designed to take advantage of their particular properties. Unfortunately, most of them do not scale well as the node density and the distance in hops to the sink increases. The result is that packets generated many hops away from the sink tend to experience unacceptable high end-to-end delay and low delivery probabilities. This paper introduces HP-MAC, a synchronized duty-cycled MAC protocol for Linear Sensor Networks (LSNs) that assigns transmission priorities to nodes to avoid collisions, through the implementation of distributed elections based on hash functions. HP-MAC also implements a packet queuing scheme that acts as a mechanism to control the amount of network resources allocated to data flows generated at different distances to the sink. This way, packets can reach their destination with loss probability and end-to-end delay that do not depend on their distance to the sink. We use a Discrete-Time Markov Chain (DTMC) to model the performance of the proposed protocol. Numerical solutions of this model show that HP-MAC outperforms state-of-the-art representatives in terms of throughput, end-to-end delay, power consumption, and packet loss probability. These results are validated through extensive discrete-event simulations.

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.

The reliability and scalability of Linear Wireless Sensor Networks (LWSNs) are limited by the high packet loss probabilities (PLP) experienced by the packets generated at nodes far from the sink node. This is an important limitation in Smart City applications, where timely data collection is critical for decision making. Unfortunately, previous works have not addressed this problem and have only focused on improving the network’s overall performance. In this work, we propose a Distance-Based Queuing (DBQ) scheme that can be incorporated into MAC protocols for LWSNs to improve reliability and scalability without requiring extra local processing or additional signaling at the nodes. The DBQ scheme prioritizes the transmission of relay packets based on their hop distance to the sink node, ensuring that all packets experience the same PLP. To evaluate the effectiveness of our proposal, we developed an analytical model and conducted extensive discrete-event simulations. Our numerical results demonstrate that the DBQ scheme significantly improves the reliability and scalability of the network by achieving the same average PLP and throughput for all nodes, regardless of traffic intensities and network sizes.

We describe a Peer-to-Peer (P2P) network that is designed to support Video on Demand (VoD) services. This network is based on a video-file sharing mechanism that classifies peers according to the window (segment of the file) that they are downloading. This classification easily allows identifying peers that are able to share windows among them, so one of our major contributions is the definition of a mechanism that could be implemented to efficiently distribute video content in future 5G networks. Considering that cooperation among peers can be insufficient to guarantee an appropriate system performance, we also propose that this network must be assisted by upload bandwidth from servers; since these resources represent an extra cost to the service provider, especially in mobile networks, we complement our work by defining a scheme that efficiently allocates them only to those peers that are in windows with resources scarcity (we called it prioritized windows distribution scheme). On the basis of a fluid model and a Markov chain, we also developed a methodology that allows us to select the system parameters values (e.g., windows sizes or minimum servers upload bandwidth) that satisfy a set of Quality of Experience (QoE) parameters.

In this paper, we introduce H-MAC (Hash-based Medium Access Protocol), a collision-free, energy-efficient MAC protocol designed for Linear Sensor Networks (LSN) with applications to the Internet-of-Things (IoT), In our proposal, the LSN is divided in grades composed of nodes located at the same hop-distance to the sink. Nodes in the same grade follow a synchronized duty cycle to transit from the different operation modes (transmission, reception, sleeping). In order to transmit packets from one grade to the next, nodes use pipeline scheduling to coordinate transmissions between adjacent grades. During a transmission slot, H-MAC employs hash functions to implement a distributed election whose winner can access to the channel in an interference-free fashion. Extensive simulation results show that H - MAC outperforms state of the art proposals in terms of throughput, source-to-sink packet delay, packet loss probability and energy consumption. This is particularly true in scenarios where the LSN has from medium to high node density, which is a common condition in the context of the IoT.

In this paper, we analyze the performance of Heterogeneous Networks (HetNets) that are operating under Almost Blank Subframes (ABS) and Cell Range Expansion (CRE) by taking into consideration the effect of geographical information. In order to achieve such analyses, we develope a simulator that incorporates data from a Geographic Information System (GIS); specifically, a set of parameters that define the morphology of buildings and streets in urban areas. We describe the implemented methods to estimate the received power, as well as the average throughput, over an area of interest. Our numerical results clearly demonstrate that the overall network performance significantly depends on geographical information; hence our main contribution consists in developing a simulator that incorporates such information in the analysis and evaluation of ABS-CRE HetNets, which allows proposing design guidelines to improve the performance of these networks in realistic scenarios. To the best of our knowledge, this kind of proposal has not been reported in previous works.