Osama Arouk

Low-Altitude Unmanned Aerial Vehicles-Based Internet of Things Services: Comprehensive Survey and Future Perspectives

Recently, unmanned aerial vehicles (UAVs), or drones, have attracted a lot of attention, since they represent a new potential market. Along with the maturity of the technology and relevant regulations, a worldwide deployment of these UAVs is expected. Thanks to the high mobility of drones, they can be used to provide a lot of applications, such as service delivery, pollution mitigation, farming, and in the rescue operations. Due to its ubiquitous usability, the UAV will play an important role in the Internet of Things (IoT) vision, and it may become the main key enabler of this vision. While these UAVs would be deployed for specific objectives (e.g., service delivery), they can be, at the same time, used to offer new IoT value-added services when they are equipped with suitable and remotely controllable machine type communications (MTCs) devices (i.e., sensors, cameras, and actuators). However, deploying UAVs for the envisioned purposes cannot be done before overcoming the relevant challenging issues. These challenges comprise not only technical issues, such as physical collision, but also regulation issues as this nascent technology could be associated with problems like breaking the privacy of people or even use it for illegal operations like drug smuggling. Providing the communication to UAVs is another challenging issue facing the deployment of this technology. In this paper, a comprehensive survey on the UAVs and the related issues will be introduced. In addition, our envisioned UAV-based architecture for the delivery of UAV-based value-added IoT services from the sky will be introduced, and the relevant key challenges and requirements will be presented.

Group Paging-Based Energy Saving for Massive MTC Accesses in LTE and Beyond Networks

Next generation cellular networks (5G) have to deal with massive deployment of machine-type-communication (MTC) devices, expected to cause congestion and system overload in both the radio access network (RAN) and the core network (CN). Moreover, not only would the network suffer from the system overload, but also the MTC devices would experience high latency to access the channel and high power consumption due to the retransmission attempts. Indeed, power consumption is a critical issue in MTC, as the devices are not plugged into the electrical supply, e.g., in the case of sensor devices. To alleviate system overload (caused by the massive MTC deployment), the 3GPP proposed the group paging (GP) method. However, its performances dramatically decrease when increasing the number of MTC devices being paged. In this paper, we devise a novel method, named further improvement-traffic scattering for group paging (FI-TSFGP), which aims to improve the performance of GP when the number of MTC devices is high. FI-TSFGP scatters the paging operation of the MTC devices over a GP interval instead of letting all of the devices start the channel access procedure at nearly the same time. By doing so, FI-TSFGP achieves high-channel access probability for MTC devices, leading to the reduction of both the channel access latency and power consumption. Compared to GP and two other schemes, simulation results clearly demonstrate the high performance of FI-TSFGP in terms of: success and collision probabilities, average access delay, average number of preamble transmissions, and ultimately energy conservation.

General Model for RACH Procedure Performance Analysis

This letter introduces an analytical model aiming at modeling the performance of the Random Access CHannel (RACH) procedure, with a special focus on the case of highly synchronized machine type communication (MTC) traffic activated according to beta distribution. The accuracy of the proposed model is then verified through computer simulation. Obtained results demonstrate the effectiveness of the model to capture the RACH procedure behavior when MTC devices are activated in a highly synchronized way. Note that 1) the proposed model is not dedicated only to beta distribution, but other distributions could be used and 2) this model could be used with any congestion control method managing the number of new arrivals, such as access class barring (ACB).

Multi-channel slotted aloha optimization for machine-type-communication

Deploying a massive number of MTC (Machine - Type - Communication) devices in the current cellular mobile networks represents a great challenge as they may cause congestion and system overload for both RAN (Radio Access Network) and CN (Core Network) parts. To address this issue, we propose a novel algorithm, named Multi-Channel Slotted ALOHA-Optimal Estimation (MCSA-OE), which estimates the network status (the number of active devices), and thus better controlling the RAN access. Unlike most existing methods that consider only one channel, MCSA-OE uses the statistics of all the channels in order to estimate the number of arrivals (UE and MTC devices) in each RA (Random Access) slot. Simulation results demonstrate that MCSA-OE well tracks the number of arrivals as long as they are smaller than ln(RR), where R is the number of channels. Moreover, we propose to use MCSA-OE estimation to dynamically adjust the acbBarringFactor of the Access Class Barring (ACB) mechanism. Again, simulation results show that the behavior of our proposition merely tends to that of the best acknowledgment case, i.e. when the number of arrivals in each RA slot is well known.

On improving the group paging method for machine-type-communications

Machine-type-Communication (MTC) is seen as a major service in next generation cellular mobile networks. However, the forecasted very large number of MTC devices may overload the RAN (Radio Access Network) part of the network, which may impact Non-MTC communications. Group paging is considered as one of the most efficient mechanisms proposed to alleviate the problem of the RAN overload. In this paper, we introduce a new solution to improve the performance of the current group paging method and overcome its disadvantages. The proposed solution is intended for MTC devices in the RRC CONNECTED OUT OF SYNC state, in which MTC devices have an RRC context without being synchronized with the network. Numerical results demonstrate that the proposed solution highly improves the performance of existing group paging mechanisms.

How accurate is the RACH procedure model in LTE and LTE-A?

In Long Term Evolution (LTE) networks, User Equipments (UE)s should proceed Random Access CHannel (RACH) procedure to attach to the Base Station and access the channel. One limitation of this procedure is the congestion that may appear when high number of UEs are simultaneously trying to attach to the channel. Such use-case happens when high number of Machine Type Communication (MTC) devices are deployed in one LTE cell. In order to evaluate the RACH performances, in terms of success, collision and idle probabilities, when the traffic load is high, accurate models are needed. However, most of existing models ignore one important constraint, which is the fact that the eNB can knowledge only a limited number of UEs in each RACH round, leading to a mis-formulation of these metrics in the context of LTE, and especially in the presence of high number of devices competing for the channel access. In this paper, we tackle the above-mentioned issue by devising a new model for the RACH procedure taking in consideration this constraint. Computer simulation demonstrates that unlike the existing models, our proposed model achieve high accuracy to estimate the performance of the RACH procedure, whatever the traffic load.

Multi-objective placement of virtual network function chains in 5G

In this paper we propose a novel algorithm, namely Multi-Objective Placement (MOP), for the efficient placement of Virtualized Network Function (VNF) chains in future 5G systems. Real datasets are used to evaluate the performance of MOP in terms of acceptance ratio and embedding time when placing the time critical radio access network (RAN) functions as a chain. In addition, we rely on a realistic infrastructure topology to assess the performance of MOP with two main objectives: maximizing the number of base stations that could be embedded in the Cloud and load balancing. The results reveal that the acceptance ratio of embedding RAN functions is only 5% less than the one obtained with the optimal solution for the majority of considered scenarios, with a speedup factor of up to 2000 times.

Performance Analysis of RACH Procedure with Beta Traffic-Activated Machine-Type-Communication

Machine-Type-Communication (MTC) is a key enabler for a variety of novel smart systems, such as smart grid, eHealth, Intelligent Transport System (ITS), and smart city, opening the area of the cyber physical systems. These systems may require the use of a huge number of MTC devices, which will put a great pressure on the whole network, i.e. Radio Access Network (RAN) and Core Network (CN) parts, resulting in the shape of congestion and system overload. Aiming at better evaluating the network performance under the existence of MTC traffic and also the effectiveness of the congestion control methods, the 3rd Generation Partnership Project (3GPP) group has proposed two traffic models: Uniform Distribution (over 60 s) and Beta Distribution (over 10 s). In this paper, a recursive operation-based analytical model, namely General Recursive Estimation (GRE), for modeling the performance of RACH procedure in the existence of MTC with Beta traffic is proposed. In order to show the effectiveness of our analytical model GRE, many metrics have been considered, such as the total number of MTC devices in each Random Access (RA) slot, the number of success MTC devices in each RA slot, and the Cumulative Distribution Function (CDF) of preamble transmission. Numerical results demonstrate the accuracy of GRE. Moreover, our model GRE could be used to model the performance of RACH procedure with any type of traffic.