MQTT, one of the most popular protocols for the IoT, works according to a publish/subscribe pattern in which multiple clients connect to a single broker, generally hosted in the cloud. However, such a centralised approach does not scale well considering the massive numbers of IoT devices forecasted in the next future, thus calling for distributed solutions in which multiple brokers cooperate together. Indeed, distributed brokers can be moved from traditional cloud-based infrastructure to the edge of the network (as it is envisioned by the upcoming MEC technology of 5G cellular networks), with clear improvements in terms of latency, for example. This paper proposes MQTT-ST, a protocol able to create such a distributed architecture of brokers, organised through a spanning tree. The protocol uses in-band signalling (i.e., reuses MQTT primitives for the control messages) and allows for full message replication among brokers, as well as robustness against failures. We tested MQTT-ST in different experimental scenarios and we released it as open-source project to allow for reproducible research.

The success of Wi-Fi technology as an efficient and low-cost last-mile access solution has enabled massive spontaneous deployments generating storms of beacons all across the globe. Emerging location systems are using these beacons to observe mobility patterns of people through portable or wearable devices and offer use-cases that can help solve critical problems in the developing world. In this paper, we design and develop a novel prototype to organise these spontaneous deployments of Access Points into what we call virtual cells (vcells). We compute virtual cells from a list of Access Points collected from different active scans for a geographical region. We argue that virtual cells can be encoded using Bloom filters to implement the location process. Lastly, we present two illustrative use-cases to showcase the suitability and challenges of the technique.

IEEE 802.11 networks are the most popular option to have wireless access to the Internet. The popularity of these networks have raised a costly topology discovery and connection process, in which any device has to pass through an expensive scanning process of available Access Points. In order to improve the connection process, we propose a novel architecture for asynchronous assistance for topology discovery. We discuss the role of a Topology Manager that uses computational intelligence for generating optimal scanning sequences. Preliminary results show that this approach results in 30% to 70% improvements on AP discovery rate in chaotic deployments.

TV White Spaces (TVWS) technology and regulation has the potential to make connectivity both technically and economically feasible in rural Africa where affordable access remains a challenge. The superior propagation characteristics of TVWS technology make it particularly well suited to connecting remote communities. Evidence collected from our measurements in Malawi and Zambia suggest that most UHF spectrum is already available both in urban as well as in rural areas and could be used to provide Internet connectivity. In this paper we present the findings of a TVWS spectrum measurement initiative in Malawi and Zambia. We introduce an open hardware device that geo-tags spectrum measurements and saves the results on a micro SD card. The device can also be used to record the use of spectrum over long periods of time.

In this paper, we study the IEEE 802.11 discovery process needed for handovers and propose an adaptive scanning strategy based on application requirements. The scanning process consists in actively probing the radio channels to gather access points information. We consider a well decoupled situation in which the scanning latency, the scanning failure rate and the number of discovered access points define the scanning performance. We model these scanning metrics by analytical expressions to represent the performance trade-off, i.e., finding the largest number of access points with a minimum latency. We present a novel approach based on a multi-objective optimization approach to obtain the optimal number of channels to scan, the optimal channel sequence and its correspondent scanning timers. Finally, we compare one fixed and two adaptive scanning approaches by means of simulations. We show that our adaptive scanning strategies better manage the performance trade-off and allow different application profiles to match with specific scanning latency.

In wireless communication, the discovery of the surrounding access points is crucial to provide seamless connectivity to mobile users. In IEEE 802.11, this discovery process is performed by passive and active scanning functions. For both, timers are usually constant (within the 802.11 driver) and their configuration affects the two main scanning performance metrics, i.e., scanning latency and scanning failure. In order to manage this trade-off, we propose a couple of adaptive scanning algorithms that are aware of the access point's signal power and congestion level using cross-layer information from the physical layer. As shown by experimentation in a real testbed, this allows a faster topology discovery while mostly reducing the failure rate.

In IEEE 802.16 networks, bandwidth allocation is centralized at the base station (BS). For the uplink traffic, data transmission is scheduled after the BS processes bandwidth requests (BW-REQs) sent by mobile stations (MSs). In this paper we focus on the multicast/broadcast polling method, where MSs send their BW-REQs during contention periods. Contention-based polling is deemed suitable for Best-Effort TCP flows, since the latter have less stringent needs, in terms of delay and throughput, than traffic carried by other classes of service. We propose a novel analytical model for Best-Effort TCP performance over 802.16 networks. This model explicitly considers the impact of the uplink request/grant mechanism, including the influence of bandwidth-perception mismatch at the BS. The effect of MAC-layer parameters, such as the MAC queue length, is also studied. The accuracy of the model is verified by means of ns-2 simulations.

In 802.16 networks, bandwidth request-grant mechanisms allow managing the uplink bandwidth needs of subscriber stations. Subscriber stations send their bandwidth requests to the base station, where most of the bandwidth scheduling is centralized. After processing such requests, the base station schedules the transmission of uplink traffic. In this paper we present a preliminary investigation of some bandwidth allocation issues, related to the management of the perception of subscriber stations' bandwidth needs at the base station. We illustrate how the bandwidth perception varies depending on the policy used to manage bandwidth requests and grants. Focusing on the case of TCP Best Effort traffic, we assess by simulation the potential impact of such policies on the system's aggregate throughput.

The IEEE 802.16 is the standard for broadband wireless access. One promise of this technology (also called WiMAX) is to provide high-speed access to the Internet where the transmission control protocol (TCP) is the core transport protocol. In this paper, we study the impact of network asymmetry in WiMAX on TCP performance. In particular, we investigate the dependence of the aggregate throughput and goodput of TCP on factors such as frame duration, direction of flow, DL:UL ratio, modulation and coding schemes, and offered loads. We find that these factors affect TCP performance by exacerbating the network asymmetry inherent to the MAC layer.

Nowadays Internet Mobile terminals are now all equipped with 802.11 devices. Moreover, a high and increasing number of hot spots are deployed in a variety of places, such as homes, cafes and airports. A typical mobile user uses TCP-based applications to access emails, browse the web or download files from the Internet. Thus the selfish interest for a user to have a better performing version of the Transmission Control Protocol (TCP).