Advances in Computer Science and Engineering

The book Advances in Computer Science and Engineering constitutes the revised selection of 23 chapters written by scientists and researchers from all over the world. The chapters cover topics in the scientific fields of Applied Computing Techniques, Innovations in Mechanical Engineering, Electrical Engineering and Applications and Advances in Applied Modeling

Pervasive service discovery in low-power and lossy networks

Pervasive Service Discovery (SD) in Low-power and Lossy Networks (LLNs) is expected to play a major role in realising the Internet of Things (IoT) vision. Such a vision aims to expand the current Internet to interconnect billions of miniature smart objects that sense and act on our surroundings in a way that will revolutionise the future. The pervasiveness and heterogeneity of such low-power devices requires robust, automatic, interoperable and scalable deployment and operability solutions. At the same time, the limitations of such constrained devices impose strict challenges regarding complexity, energy consumption, time-efficiency and mobility. This research contributes new lightweight solutions to facilitate automatic deployment and operability of LLNs. It mainly tackles the aforementioned challenges through the proposition of novel component-based, automatic and efficient SD solutions that ensure extensibility and adaptability to various LLN environments. Building upon such architecture, a first fully-distributed, hybrid pushpull SD solution dubbed EADP (Extensible Adaptable Discovery Protocol) is proposed based on the well-known Trickle algorithm. Motivated by EADPs’ achievements, new methods to optimise Trickle are introduced. Such methods allow Trickle to encompass a wide range of algorithms and extend its usage to new application domains. One of the new applications is concretized in the TrickleSD protocol aiming to build automatic, reliable, scalable, and time-efficient SD. To optimise the energy efficiency of TrickleSD, two mechanisms improving broadcast communication in LLNs are proposed. Finally, interoperable standards-based SD in the IoT is demonstrated, and methods combining zero-configuration operations with infrastructure-based solutions are proposed. Experimental evaluations of the above contributions reveal that it is possible to achieve automatic, cost-effective, time-efficient, lightweight, and interoperable SD in LLNs. These achievements open novel perspectives for zero-configuration capabilities in the IoT and promise to bring the ‘things’ to all people everywhere

A Survey on Wireless Sensor Network Security

Wireless sensor networks (WSNs) have recently attracted a lot of interest in the research community due their wide range of applications. Due to distributed nature of these networks and their deployment in remote areas, these networks are vulnerable to numerous security threats that can adversely affect their proper functioning. This problem is more critical if the network is deployed for some mission-critical applications such as in a tactical battlefield. Random failure of nodes is also very likely in real-life deployment scenarios. Due to resource constraints in the sensor nodes, traditional security mechanisms with large overhead of computation and communication are infeasible in WSNs. Security in sensor networks is, therefore, a particularly challenging task. This paper discusses the current state of the art in security mechanisms for WSNs. Various types of attacks are discussed and their countermeasures presented. A brief discussion on the future direction of research in WSN security is also included.Comment: 24 pages, 4 figures, 2 table

Effects of Data Replication on Data Exfiltration in Mobile Ad hoc Networks Utilizing Reactive Protocols

A swarm of autonomous UAVs can provide a significant amount of ISR data where current UAV assets may not be feasible or practical. As such, the availability of the data the resides in the swarm is a topic that will benefit from further investigation. This thesis examines the impact of le replication and swarm characteristics such as node mobility, swarm size, and churn rate on data availability utilizing reactive protocols. This document examines the most prominent factors affecting the networking of nodes in a MANET. Factors include network routing protocols and peer-to-peer le protocols. It compares and contrasts several open source network simulator environments. Experiment implementation is documented, covering design considerations, assumptions, and software implementation, as well as detailing constant, response and variable factors. Collected data is presented and the results show that in swarms of sizes of 30, 45, and 60 nodes, le replication improves data availability until network saturation is reached, with the most significant benefit gained after only one copy is made. Mobility, churn rate, and swarm density all influence the replication impact

Design of an energy-efficient geographic routing protocol for mobile ad-hoc networks

Mobile Ad-hoc networks extend communications beyond the limit of infrastructure based networks. Future wireless applications will take advantage of rapidly deployable, self-configuring multi-hop mobile Ad-hoc networks. In order to provide robust performance in mobile Ad-hoc networks and hence cope with dynamic path loss conditions, it is apparent that research and development of energy efficient geographic routing protocols is of great importance. Therefore various mobile Ad-hoc routing protocols have been studied for their different approaches. Forwarding strategies for geographic routing protocols are discussed and there is a particular focus on the pass loss model used by those routing protocols, the restriction and disadvantage of using such path loss model is then discussed. A novel geographic routing protocol which incorporates both the link quality and relay node location information has been developed to determine an energy efficient route from source to destination. The concepts of a gain region and a relay region to minimize the energy consumption have been proposed to define the area in where the candidate relay nodes will be selected with the minimized hop count. The signalling overhead required by the protocol has been analyzed in various scenarios with different traffic load, node densities and network sizes. Discrete event simulation models are therefore developed to capture the behaviour and characteristics of the operation of the developed routing protocol under different path loss conditions and network scenarios. A non-free space path loss model has been developed with a random loss between the nodes to simulate a realistic path loss scenario in the network. An enhanced signalling process has been designed in order to achieve advanced routing information exchange and assist routing determination. Comparison of simulated characteristics demonstrates the significant improvement of the new routing protocol because of its novel features, the gain region to ensure the deductiono f the energyc onsumptiont,h e relay region to ensuret he forward progress to the destination and hence maintain an optimised hop count. The simulation results showed that the energy consumption under the operation of the developed protocol is 30% of that with a conventionagl eographicarl outing protocol

Evaluation of on-demand routing in mobile ad hoc networks and proposal for a secure routing protocol

Secure routing Mobile Ad hoc Networks (MANETs) has emerged as an important MANET research area. Initial work in MANET focused mainly on the problem of providing efficient mechanisms for finding paths in very dynamic networks, without considering the security of the routing process. Because of this, a number of attacks exploit these routing vulnerabilities to manipulate MANETs. In this thesis, we performed an in-depth evaluation and performance analysis of existing MANET Routing protocols, identifying Dynamic Source Routing (DSR) as the most robust (based on throughput, latency and routing overhead) which can be secured with negligible routing efficiency trade-off. We describe security threats, specifically showing their effects on DSR. We proposed a new routing protocol, named Authenticated Source Routing for Ad hoc Networks (ASRAN) which is an out-of-band certification-based, authenticated source routing protocol with modifications to the route acquisition process of DSR to defeat all identified attacks. Simulation studies confirm that ASRAN has a good trade-off balance in reference to the addition of security and routing efficiency

Data Analysis Methods for Software Systems

Using statistics, econometrics, machine learning, and functional data analysis methods, we evaluate the consequences of the lockdown during the COVID-19 pandemics for wage inequality and unemployment. We deduce that these two indicators mostly reacted to the first lockdown from March till June 2020. Also, analysing wage inequality, we conduct analysis separately for males and females and different age groups.We noticed that young females were affected mostly by the lockdown.Nevertheless, all the groups reacted to the lockdown at some level

Internet of Underwater Things and Big Marine Data Analytics -- A Comprehensive Survey

The Internet of Underwater Things (IoUT) is an emerging communication ecosystem developed for connecting underwater objects in maritime and underwater environments. The IoUT technology is intricately linked with intelligent boats and ships, smart shores and oceans, automatic marine transportations, positioning and navigation, underwater exploration, disaster prediction and prevention, as well as with intelligent monitoring and security. The IoUT has an influence at various scales ranging from a small scientific observatory, to a midsized harbor, and to covering global oceanic trade. The network architecture of IoUT is intrinsically heterogeneous and should be sufficiently resilient to operate in harsh environments. This creates major challenges in terms of underwater communications, whilst relying on limited energy resources. Additionally, the volume, velocity, and variety of data produced by sensors, hydrophones, and cameras in IoUT is enormous, giving rise to the concept of Big Marine Data (BMD), which has its own processing challenges. Hence, conventional data processing techniques will falter, and bespoke Machine Learning (ML) solutions have to be employed for automatically learning the specific BMD behavior and features facilitating knowledge extraction and decision support. The motivation of this paper is to comprehensively survey the IoUT, BMD, and their synthesis. It also aims for exploring the nexus of BMD with ML. We set out from underwater data collection and then discuss the family of IoUT data communication techniques with an emphasis on the state-of-the-art research challenges. We then review the suite of ML solutions suitable for BMD handling and analytics. We treat the subject deductively from an educational perspective, critically appraising the material surveyed.Comment: 54 pages, 11 figures, 19 tables, IEEE Communications Surveys & Tutorials, peer-reviewed academic journa