Section: New Results

Wireless data collection

Participants: Yosra Bahri Zguira, Alexis Duque, Junaid Ahmed Khan, Abdoul-Aziz Mbacké, Romain Pujol, Hervé Rivano, Razvan Stanica, Fabrice Valois.

Smart Parking Systems

Considering the increase of urban population and traffic congestion, smart parking is always a strategic issue to work on, not only in the research field but also from economic interests. Thanks to information and communication technology evolution, drivers can more efficiently find satisfying parking spaces with smart parking services. The existing and ongoing works on smart parking are complicated and transdisciplinary. While deploying a smart parking system, cities, as well as urban engineers, need to spend a very long time to survey and inspect all the possibilities. Moreover, many varied works involve multiple disciplines, which are closely linked and inseparable.

To give a clear overview, we introduce a smart parking ecosystem and propose a comprehensive and thoughtful classification by identifying their functionalities and problematic focuses [5]. We go through the literature over the period of 2000-2016 on parking solutions as they were applied to smart parking development and evolution, and propose three macro-themes: information collection, system deployment, and service dissemination. In each macro-theme, we explain and synthesize the main methodologies used in the existing works and summarize their common goals and visions to solve current parking difficulties. Lastly, we give our engineering insights and show some challenges and open issues.

Data Offloading

Mobile users in an urban environment access content on the Internet from different locations. It is challenging for the current service providers to cope with the increasing content demand from a large number of collocated mobile users. In-network caching to offload content at nodes closer to users alleviates the issue, though efficient cache management is required to find out who should cache what, when and where in an urban environment, given nodes limited computing, communication and caching resources. To address this [14], we first define a novel relation between content popularity and availability in the network and investigate a node eligibility to cache content based on its urban reachability. We then allow nodes to self-organize into mobile fogs to increase the distributed cache and maximize content availability in a cost-effective manner. However, to cater rational nodes, we propose a coalition game for the nodes to offer a maximum virtual cache assuming a monetary reward is paid to them by the service/content provider. Nodes are allowed to merge into different spatio-temporal coalitions in order to increase the distributed cache size at the network edge. Results obtained through simulations using realistic urban mobility trace validate the performance of our caching system showing a ratio of 60 − 85% of cache hits compared to the 30 − 40% obtained by the existing schemes and 10% in case of no coalition.

Another option for data offloading is represented by vehicular traffic. With over 300 billion vehicle trips made in the USA and 64 billion in France per year, network operators have the opportunity to utilize the existing road and highway network as an alternative data network to offload large amounts of delay-tolerant traffic. To enable the road network as a large-capacity transmission system, we exploit the existing mobility of vehicles equipped with wireless and storage capacities together with a collection of offloading spots [1]. An offloading spot is a data storage equipment located where vehicles usually park. Data is transloaded from a conventional data network to the closest offloading spot and then shipped by vehicles along their line of travel. The subsequent offloading spots act as data relay boxes where vehicles can drop off data for later pickups by other vehicles, depending on their direction of travel. The main challenges of this offloading system are how to compute the road path matching the performance requirements of a data transfer and how to configure the sequence of offloading spots involved in the transfer. We propose a scalable and adaptive centralized architecture built on SDN that maximizes the utilization of the flow of vehicles connecting consecutive offloading spots. We simulate the performance of our system using real roads traffic counts for France. Results show that the centralized controlled offloading architecture can achieve an efficient and fair allocation of concurrent data transfers between major cities in France.

Hybrid Short/Long Range Networks

Despite the success of dedicated IoT networks, such as Sigfox or LoRa, several use cases can not be accommodated by these new technologies, mainly because of capacity constraints. For example, mobile sensing and proximity-based applications require smart devices to find other nodes in vicinity, though it is challenging for a device to find neighbors in an energy efficient manner, while also running on low duty cycles.

Neighbor discovery schemes allow nodes to follow a schedule to become active and send beacons or listen for other active nodes in order to discover each other with a bounded latency. However, a trade-off exists between the energy consumption and the time a node takes to discover neighbors using a given activity schedule. Moreover, energy consumption is not the only bottleneck, as theoretically perfect schedules can result in discovery failures in a real environment. In [12], we provide an in-depth study on neighbor discovery, by first defining the relation between energy efficiency, discovery latency and the fraction of discovered neighbors. We evaluate existing mechanisms using extensive simulations for up to 100 nodes and testbed implementations for up to 15 nodes, with no synchronization between nodes and using duty cycles as low as 1% and 5%. Moreover, the literature assumes that multiple nodes active simultaneously always result in neighbor discovery, which is not true in practice as this can lead to collisions between the transmitted messages. Our findings reveal such scalability issues in existing schemes, where discovery fails because of collisions between beacons from multiple nodes active at the same time. Therefore, we show that energy efficient discovery schemes do not necessarily result in successful discovery of all neighbors, even when the activity schedules are computed in a deterministic manner.

A second use-case requiring a combination of long range and short range communications is related to intelligent transportation systems. As a matter of fact, communication is essential to the coordination of public transport systems. Nowadays, cities are facing an increasing number of bikes used by citizens therefore the need of monitoring and managing their traffic becomes crucial. Public bike sharing system has been introduced as an urban transportation system that can collect data from mobile devices. In this context, we introduce IoB-DTN [29], a protocol based on the Delay/Disruption Tolerant Network (DTN) paradigm adapted for an IoT-like applications running on bike sharing system based sensor network. We present simulation results obtained by evaluating the Binary Spray and Wait inspired variant of IoB-DTN with four buffer management policies and by comparing three variants of IoB-DTN by varying the number of packet copies sprayed in the network.

Visible Light Communications in IoT Networks

With the increasing consumer demand for smart objects, Visible Light Communications (VLC), and especially LED-to-Camera communication, appears as a low-cost alternative to radio to make any conventional device smart. Since LEDs are already on most electronics devices, that is achieved at the cost of negligible hardware modifications. However, as these LEDs are very different from the widely studied ceiling ones, several challenges need to be addressed to make this happen. In our work [31], we propose a line of sight bi-directional communication system between an ordinary LED and an off-the-shelf smartphone. We designed a cheap multi sensors device as a proof of concept of a near communication module for the IoT.

Among the issues we observed experimenting with this platform, we note the constrained physical layer data unit (PHY-SDU) length that complicates the use of coding strategies to cope with bits or packets erasure. To break this limitation, we present SeedLight [8], a coding scheme designed to face the inherent packet losses and enhance line-of-sight LED-to-Camera communication goodput. SeedLight leverages random linear coding to provide an efficient redundancy mechanism that works even on PHY-SDU of tens of bits. The key idea of SeedLight is to reduce the code overhead by replacing the usual coding coefficients by a seed. Since this work addresses IoT devices with low computational resources, SeedLight encoding algorithm complexity remains low. We develop an implementation of SeedLight on a low-cost MCU and a smartphone to evaluate both the communication and algorithmic performances. Experimental results show that SeedLight introduces a negligible overhead and can be implemented even on the cheapest MCU, such as the ones used in many IoT devices. The achievable goodput can be up to 2.5kbps, while the gain compared to a trivial retransmissions scheme is up to 100%.

To ease the evaluation of VLC systems, we present CamComSim [28], the first simulator for development and rapid prototyping of LED-to-Camera communication systems. Our event driven simulator relies on a standalone Java application that is easily extensible through a set of interfaces. A range of low and high-level parameters, such as the camera characteristics, the PHY-SDU size, or the redundancy mechanism can be chosen. CamComSim uses empirically validated models for the LED-to-Camera channel and the broadcast protocols, configurable with a finely grained precision. To validate CamComSim implementation and accuracy, we use the previously discussed testbed, based on a color LED and a smartphone, and compare the performance reached by the testbed with the results given by our simulator. We illustrate with a real use case the full usage of CamComSim, tuning a broadcast protocol that implements the transmission of 1 kbyte of information. The results highlight that our simulator is very precise and predicts the performance of a real LED-to-Camera system with less than 10% of error in most cases.

Data Collection with RFID Devices

The popularization of Radio Frequency Identification (RFID) systems has conducted to large deployments of RFID solutions in various areas under different criteria. However, such deployments, specially in dense environments, can be subject to RFID collisions which in turn affect the quality of readings. In [17], [18], we propose two distributed and efficient solutions for dense mobile deployments of RFID systems. mDEFAR is an adaptation of a previous work highly performing in terms of collisions reduction, efficiency and fairness in dense static deployments. CORA is more of a locally mutual solution where each reader relies on its neighborhood to enable itself or not. Using a beaconing mechanism, each reader is able to identify potential (non-)colliding neighbors in a running frame and as such chooses to read or not. Performance evaluation shows high performance in terms of coverage delay for both proposals quickly achieving 100% coverage depending on the considered use case while always maintaining consistent efficiency levels above 70%. Compared to GDRA, our solutions proved to be better suited for highly dense and mobile environments, offering both higher throughput and efficiency. The results reveal that depending on the application considered, choosing either mDEFAR or CORA helps improve efficiency and coverage delay.

RFID solutions encounter two main issues: the first one is inherent to the technology itself which is readers collisions, the second one being the gathering of read data up to a base station, potentially in a multihop fashion. While the first one has been a main research subject in the late years, the second one has not been investigated for the sole purpose of RFID, but rather for wireless adhoc networks. This multihop tag information collection must be done in regards of the application requirements but it should also care for the deployment strategy of readers to take advantage of their relative positions, coverage, reading activity and deployment density to avoid interfering between tag reading and data forwarding. To the best of our knowledge, the issue for a joint scheduling between tag reading and forwarding has never been investigated so far in the literature, although important. In [17], we propose two new distributed, cross-layer solutions meant for the reduction of collisions and better efficiency of the RFID system, but also serving as a routing solution towards a base station. Simulations show high levels of throughput while not lowering on the fairness on medium access staying above 85% in the highest deployment density with up to 500 readers, also providing a 90% increase in data rate.