An expanding mobile cellular network data transfer service offers cheaper wireless solutions for various data transfer needs. This paper presents an experimental testing of data transfer performance in 3G and 4G modes. The purpose of testing was to check the possibility of real-time and critical data transfer over the mobile cellular networks. The testing was performed in Riga in July and August 2016 using the most popular mobile service operators in Latvia: Tele2-LV, BITE-LV and LMT. The testing confirmed that the overload of Riga’s 4G networks causes serious service deterioration or even interruption. Riga’s 3G networks are more stable. However, 3G network service quality depends on a cell load. Lightly loaded 3G network meets real-time data transfer requirements of 100 ms one-way delay of the small packet traffic.
Mojtaba Eskandari, Bruno Kessler, Maqsood Ahmad, Anderson Santana de Oliveira and Bruno Crispo
The article presents a model of Bring Your Own Device (BYOD) as a model network, which provides the user reliable access to network resources. BYOD is a model dynamically developing, which can be applied in many areas. Research network has been launched in order to carry out the test, in which as a service of BYOD model Work Folders service was used. This service allows the user to synchronize files between the device and the server. An access to the network is completed through the wireless communication by the 802.11n standard. Obtained results are shown and analyzed in this article.
Automatic data reading from smart meters is being developed in many parts of the world, including Latvia. The key drivers for that are developments of smart technologies and economic benefits for consumers. Deployment of smart meters could be launched in a massive scale.
Several pilot projects were implemented to verify the feasibility of smart meters for individual consumer groups. Preliminary calculations indicate that installation of smart meters for approximately 23 % of electricity consumers would be economically viable. Currently, the data for the last two years is available for an in-depth mathematical analysis. The continuous analysis of consumption data would be established, when more measurements from smart meters are available.
The extent of introduction of smart meters should be specified during this process in order to gain the maximum benefit for the whole society (consumers, grid companies, state authorities), because there are still many uncertain and variable factors. For example, it is necessary to consider statistical load variations by hour, dependence of electricity consumption on temperature fluctuations, consumer behaviour and demand response to market signals to reduce electricity consumption in the short and long term, consumer’s ambitions and capability to install home automation for regulation of electricity consumption.
To develop the demand response, it is necessary to analyse the whole array of additional factors, such as expected cost reduction of smart meters, possible extension of their functionality, further development of information exchange systems, as well as standard requirements and different political and regulatory decisions regarding the reduction of electricity consumption and energy efficiency.
Traditional Wireless Sensor Networks (WSNs) are designed for connecting pure electronic or mechanical sensors through wireless communication. Nowadays, WSNs are combined with other technologies like big data and cloud for data management. While combining the sensors (low level devices) with a high end network like Internet, data communication should be taken care of in the gateway between these two networks. With this type of WSNs, if all the sensors are in direct communication with the high end network, then a lot of energy will be consumed, requiring complex protocols for making this communication possible. So, to reduce the energy wastage, the clustering concept is used in WSN. Although so many complex and innovative clustering techniques are available for WSN, this paper describes a very simple clustering technique for environmental monitoring WSN with proven results.
I. Alagiri, V. Madhuviswanatham and P. VenkataKrishna
Mobile Ad-hoc NETwork (MANET) is a prevalent deployable network for easy plug-in and it is widely applied for many real time scenarios. Clustering is a well known solution for efficient communication among nodes with least control overheads. The communication link breaks between nodes when a node moves beyond the transmission range of another node because of mobility. Frequent link breaks happen because of nodes mobility which cannot be controlled without increasing the network control overheads. The authors propose an Mobility Adjustment Routing (MAR) routing algorithm for establishing a stable path between the source and the destination. In this approach the choice of cluster heads based on the smallest weight age, node mobility and remaining battery power are used as a metric for weight computation. The cluster head and the gate way nodes forward RREQ packets to set up a path between the source and the destination which proves efficient communication, before forwarding a RREQ packet cluster the head/gateway node compares its mobility value with RREQ and updates the least value in RREQ. The destination node advertises the least mobility value to the remaining nodes in the path with the help of RREP packet, therefore stable paths are found without increasing the network control overheads. The simulation results done with the help of network simulator 2 show that the algorithm proposed performs well even at higher traffic load compared to existing algorithms.
. Svoboda, P. Romirer-Maierhofer, N. Nikaein, F. Ricciato, and M. Rupp, “A Comparison Between One-way Delays in Operating HSPA and LTE Networks,” 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt) , May 14–18, 2012.
 D. Brodņevs and A. Kutins, “An Experimental Study of Ground-Based Equipment Real Time DataTransfer Possibility by Using Cellular Networks,” Electr. Control Commun. Eng. , vol. 12, no. 1, pp. 11–19, 2017. https://doi.org/10.1515/ecce-2017-0002
 D. Brodnevs and A. Kutins, “Cellular
Remotely piloted operations of lightweight Unmanned Air Vehicles (UAV) are limited by transmitter power consumption and are always restricted to Line-of-Sight (LOS) distance. The use of mobile cellular network data transfer services (e.g. 3G HSPA and LTE) as well as long-range terrestrial links (e.g. LoraWAN) makes it possible to significantly extend the operation range of the remotely piloted UAV. This paper describes the development of a long-range communication solution for the UAV telemetry system. The proposed solution is based on (but not restricted to) cellular data transfer service and is implemented on Raspberry Pi under Gentoo Linux control. The goal of the project is to develop a flexible system for implementing optimized redundant network solutions for the Non-LOS remote control of the UAV
We propose a multi-layer cluster based energy aware routing protocol for Low Power and Lossy Networks, which divides the network area into equal length rings. The intra-ring clustering process divides a ring into equal sized clusters and inter-cluster routing applies the fuzzy logic to select the best route for data transfer. It increases the network lifetime and packet delivery ratio by 18-22% and 5-8%, respectively.
Evelina N. Pencheva, Ivaylo I. Atanasov and Vladislav G. Vladislavov
5th Generation (5G) mobile system is expected to support the requirements of mission critical communications for ultra reliability and availability, and very low latency. With the development of messaging and data transfer in mobile networks, mission critical communication users see more and more potential in data communications. In this paper, we explore the capabilities of Multi-access Edge Computing (MEC) that appears to be a key 5G component, to provide short messaging service at the network edge. The provided use cases illustrate the capabilities for transferring mobile originating and mobile terminating short messages to and from mission critical mobile edge applications. The data model describes the service resource structure and the Application Programming Interface definitions illustrate how the mobile edge applications can use the service. Some implementation aspects related to behavioral logic of the network and applications are provided. The performance analysis enables estimation of latency introduced by the service.