From MANET to people-centric networking: Milestones and open research challenges

In this paper, we discuss the state of the art of (mobile) multi-hop ad hoc networking with the aim to present the current status of the research activities and identify the consolidated research areas, with limited research opportunities, and the hot and emerging research areas for which further research is required. We start by briefly discussing the MANET paradigm, and why the research on MANET protocols is now a cold research topic. Then we analyze the active research areas. Specifically, after discussing the wireless-network technologies, we analyze four successful ad hoc networking paradigms, mesh networks, opportunistic networks, vehicular networks, and sensor networks that emerged from the MANET world. We also present an emerging research direction in the multi-hop ad hoc networking field: people centric networking, triggered by the increasing penetration of the smartphones in everyday life, which is generating a people-centric revolution in computing and communications

Intelligent Traffic Monitoring Systems for Vehicle Classification: A Survey

A traffic monitoring system is an integral part of Intelligent Transportation Systems (ITS). It is one of the critical transportation infrastructures that transportation agencies invest a huge amount of money to collect and analyze the traffic data to better utilize the roadway systems, improve the safety of transportation, and establish future transportation plans. With recent advances in MEMS, machine learning, and wireless communication technologies, numerous innovative traffic monitoring systems have been developed. In this article, we present a review of state-of-the-art traffic monitoring systems focusing on the major functionality--vehicle classification. We organize various vehicle classification systems, examine research issues and technical challenges, and discuss hardware/software design, deployment experience, and system performance of vehicle classification systems. Finally, we discuss a number of critical open problems and future research directions in an aim to provide valuable resources to academia, industry, and government agencies for selecting appropriate technologies for their traffic monitoring applications.Comment: Published in IEEE Acces

Vehicle classification in intelligent transport systems: an overview, methods and software perspective

Vehicle Classification (VC) is a key element of Intelligent Transportation Systems (ITS). Diverse ranges of ITS applications like security systems, surveillance frameworks, fleet monitoring, traffic safety, and automated parking are using VC. Basically, in the current VC methods, vehicles are classified locally as a vehicle passes through a monitoring area, by fixed sensors or using a compound method. This paper presents a pervasive study on the state of the art of VC methods. We introduce a detailed VC taxonomy and explore the different kinds of traffic information that can be extracted via each method. Subsequently, traditional and cutting edge VC systems are investigated from different aspects. Specifically, strengths and shortcomings of the existing VC methods are discussed and real-time alternatives like Vehicular Ad-hoc Networks (VANETs) are investigated to convey physical as well as kinematic characteristics of the vehicles. Finally, we review a broad range of soft computing solutions involved in VC in the context of machine learning, neural networks, miscellaneous features, models and other methods

Tackling different aspects of drone services utilizing technologies from cross-sectional industries

Enabling autonomous and Beyond Visual Line of Sight (BVLOS) operation of Unmanned Aerial Vehicles (UAVs) in the Very Low Level (VLL) airspace requires further advancement of technologies such as sensing the environment or secure and reliable communication. This paper addresses these challenges by presenting solutions developed within the project Airborne Data Collection on Resilient System Architectures (ADACORSA). Here, findings from cross-sectional areas such as the automotive industry are being further enhanced to fulfill the demands of aviation, in particular for use in the UAV domain. The developed technologies include an advanced Ethernet-based deterministic network for reliable onboard communication, a multi-sensor architecture for sensing the spatial environment as well as a multi-link communication gateway that provides reliable communication to the ground and a secure handover architecture.ADACORSA has received funding from the ECSEL Joint Undertaking (JU) and National Authorities under grant agreement No 876019. Follow www.adacorsa.eu for more informatio

Business Case and Technology Analysis for 5G Low Latency Applications

A large number of new consumer and industrial applications are likely to change the classic operator's business models and provide a wide range of new markets to enter. This article analyses the most relevant 5G use cases that require ultra-low latency, from both technical and business perspectives. Low latency services pose challenging requirements to the network, and to fulfill them operators need to invest in costly changes in their network. In this sense, it is not clear whether such investments are going to be amortized with these new business models. In light of this, specific applications and requirements are described and the potential market benefits for operators are analysed. Conclusions show that operators have clear opportunities to add value and position themselves strongly with the increasing number of services to be provided by 5G.Comment: 18 pages, 5 figure

Tree TDMA MAC Algorithm Using Time and Frequency Slot Allocations in Tree-Based WSNs

In this paper, we propose a tree-based time division multiple access (Tree TDMA) media access control (MAC) algorithm based on the IEEE 802.15.4 PHY standard. The method involves the simultaneous use of two algorithms, a time slot allocation algorithm (TSAA) and a frequency slot allocation algorithm (FSAA), at low power consumption to support voice and data communication to solve the problems afflicting prevalent MAC protocols in tree topology networks. The TSAA first generates routing paths through the control channel in a super frame prior to transmitting packets, and allocates time slots for each node to transmit packets. The FSAA then allocates frequencies to each path according to the routing paths generated following its application. The overhearing problem and the funneling effect in TDMA as well as carrier sense multiple access with collision avoidance (CSMA/CA) MACs are resolved by these two algorithms because a given node and its neighbors are orthogonal in terms of time and frequency. The problem of inter-node synchronization is addressed by periodically sending a beacon from higher to lower nodes, and the issue of low power is solved by leaving unsigned time slots in an idle state. To test the effectiveness of the proposed algorithm, we used a MATLAB simulation to compare its performance with that of contention-based CSMA MAC and non-contention-based TreeMAC in terms of network throughput, network delay, energy efficiency, and energy consumption. We also tested the performance of the algorithms for increasing number of nodes and transmission packets in the tree topology network.This work was supported by the ICT R&D Program of MSIP/IITP. [B0126-16-1018, The IoT Platform for Virtual Things, Distributed Autonomous Intellgence and Data Federation/Analysis