Fine-grained performance analysis of massive MTC networks with scheduling and data aggregation

Abstract. The Internet of Things (IoT) represents a substantial shift within wireless communication and constitutes a relevant topic of social, economic, and overall technical impact. It refers to resource-constrained devices communicating without or with low human intervention. However, communication among machines imposes several challenges compared to traditional human type communication (HTC). Moreover, as the number of devices increases exponentially, different network management techniques and technologies are needed. Data aggregation is an efficient approach to handle the congestion introduced by a massive number of machine type devices (MTDs). The aggregators not only collect data but also implement scheduling mechanisms to cope with scarce network resources. This thesis provides an overview of the most common IoT applications and the network technologies to support them. We describe the most important challenges in machine type communication (MTC). We use a stochastic geometry (SG) tool known as the meta distribution (MD) of the signal-to-interference ratio (SIR), which is the distribution of the conditional SIR distribution given the wireless nodes’ locations, to provide a fine-grained description of the per-link reliability. Specifically, we analyze the performance of two scheduling methods for data aggregation of MTC: random resource scheduling (RRS) and channel-aware resource scheduling (CRS). The results show the fraction of users in the network that achieves a target reliability, which is an important aspect to consider when designing wireless systems with stringent service requirements. Finally, the impact on the fraction of MTDs that communicate with a target reliability when increasing the aggregators density is investigated

The Mobile Commerce Prospects: A Strategic Analysis of Opportunities in the Banking Sector

Mobile Commerce has gained increasing acceptance amongst various sections of the society in previous years. The reasons for its growth can be traced back to technological and demographical developments that have influenced many aspects of the socio-cultural behaviour in today's world. The need (and/or wish) for mobility seems to be the driving force behind Mobile Commerce. The launch of UMTS technology has provided Mobile Commerce with the necessary verve.Mobile Banking presents an opportunity for banks to retain their existing, technology-savvy customer base by offering value-added, innovative services and to attract new customers from corresponding sections of the society. The customer survey provides evidence that such sections in the meanwhile include the affluent and financially relevant groups of the society in Germany. The time seems to be ripe to convert this non-negligible customer interest into business-driving customer demand. A proactive attitude on the part of the banks seems to be therefore recommendable.Many banks in Germany have come to regard Mobile Banking as a necessary tool for thwarting negative differentiation vis-à-vis rivals and to foster/retain an innovative image. This self-reinforcing dynamism is expected to gain currency in near-future so that Mobile Banking services could soon advance to a standard product - on the lines of Online Banking - offered by more or less each and every bank

Feature Papers of Drones - Volume II

[EN] The present book is divided into two volumes (Volume I: articles 1–23, and Volume II: articles 24–54) which compile the articles and communications submitted to the Topical Collection ”Feature Papers of Drones” during the years 2020 to 2022 describing novel or new cutting-edge designs, developments, and/or applications of unmanned vehicles (drones). Articles 24–41 are focused on drone applications, but emphasize two types: firstly, those related to agriculture and forestry (articles 24–35) where the number of applications of drones dominates all other possible applications. These articles review the latest research and future directions for precision agriculture, vegetation monitoring, change monitoring, forestry management, and forest fires. Secondly, articles 36–41 addresses the water and marine application of drones for ecological and conservation-related applications with emphasis on the monitoring of water resources and habitat monitoring. Finally, articles 42–54 looks at just a few of the huge variety of potential applications of civil drones from different points of view, including the following: the social acceptance of drone operations in urban areas or their influential factors; 3D reconstruction applications; sensor technologies to either improve the performance of existing applications or to open up new working areas; and machine and deep learning development