Real-Time Communication Support for Over-water Wireless Multi-hop Networks

https://www.bsc.es/education/predoctoral-phd/doctoral-symposium/7th-bsc-so-doctoral-symposiumThe prospect scenario for wireless communications and networking technologies in aquatic environments is nowadays promising. The growing interest around this subject in the last decades has recently been accelerated due to the more powerful capabilities of a number of sensing, control and communication devices. Moored, fixed, drifting, and vehicular nodes form now a rich ecosystem of autonomous embedded systems potentially connected in a multi-hop (and over-water) fashion, which demand innovative solutions to satisfy the ever-increasing requirements of reliability, bandwidth, latency and cost. The efforts in this direction, mostly as a result of the push from the Internet-of-Thing (IoT) and related communication paradigms, are now at an early stage, and thus still pose significant, technical and research challenges, especially from the perspective of communication and networking for applications involving real-time and/or multimedia networking traffic. In this research, we focus on the communication and networking aspects of over-water multi-hop networks aiming at support real-time and/or multimedia (audio/video) traffic using IEEE 802.11 (WiFi) commodity technologies. Special attention is devoted to the impact of cyclic water-level variations (such as tides and waves) on the overall network performance, and how an integrated approach to (i) network design, (ii) protocol adaptation and (iii) routing can contribute to mitigating such an issue.info:eu-repo/semantics/publishedVersio

Channel acquisition and routing system for real-time cognitive radio sensor networks

The need for efficient spectrum utilization and routing has ignited interest in the Cognitive Radio Sensor Network (CRSN) paradigm among researchers. CRSN ensures efficient spectrum utilization for wireless sensor network. However, the main challenge faced by CRSN users have to deal with is the issue of service quality in terms of interference when using channels and degradation in multi-hop communication. This thesis proposes to overcome the interference due to contention and routing issues through the design of an efficient Channel Acquisition and Reliable routing System (CARS). CARS is designed to reduce carrier sense multiple access contention and enhance routing in CRSNs. CARS comprises of Lightweight Distributed Geographical (LDG), and Reliable Opportunists Routing (ROR) modules. LDG is a medium access control centric; cross-layer designed protocol to acquire a common control channel for signalling to determine the data channel. ROR is a network-centric cross-layer designed protocol to decide on a path for routing data packets. The result shows that LDG significantly reduces the overhead of media access contention and energy cost by at an average of 70% and 80% respectively compared to other approaches that use common control channel acquisition like Efficient Recovery Control Channel (ERCC) protocol. In addition, LDG achieves a 16.3% boost in the time to rendezvous on the control channel above ERCC and a 36.9% boost above Coordinated Channel Hopping (CCH) protocol. On the other hand, the virtual clustering framework inspired by ROR has further improved network performance. The proposed ROR significantly increases packet received at the sink node by an average of over 20%, reduces end-to-end latency by an average of 37% and minimizes energy consumption by an average of 22% as compared to Spectrum-aware Clustering for Efficient Multimedia routing (SCEEM) protocol. In brief, the design of CARS which takes the intrinsic characteristics of CRSNs into consideration helps to significantly reduce the energy needed for securing a control channel and to guarantee that end-to-end, real-time conditions are preserved in terms of latency and media content. Thus, LDG and ROR are highly recommended for real-time data transmission such as multimedia data transfer in CRSN

Real-Time Sensor Networks and Systems for the Industrial IoT

The Industrial Internet of Things (Industrial IoT—IIoT) has emerged as the core construct behind the various cyber-physical systems constituting a principal dimension of the fourth Industrial Revolution. While initially born as the concept behind specific industrial applications of generic IoT technologies, for the optimization of operational efficiency in automation and control, it quickly enabled the achievement of the total convergence of Operational (OT) and Information Technologies (IT). The IIoT has now surpassed the traditional borders of automation and control functions in the process and manufacturing industry, shifting towards a wider domain of functions and industries, embraced under the dominant global initiatives and architectural frameworks of Industry 4.0 (or Industrie 4.0) in Germany, Industrial Internet in the US, Society 5.0 in Japan, and Made-in-China 2025 in China. As real-time embedded systems are quickly achieving ubiquity in everyday life and in industrial environments, and many processes already depend on real-time cyber-physical systems and embedded sensors, the integration of IoT with cognitive computing and real-time data exchange is essential for real-time analytics and realization of digital twins in smart environments and services under the various frameworks’ provisions. In this context, real-time sensor networks and systems for the Industrial IoT encompass multiple technologies and raise significant design, optimization, integration and exploitation challenges. The ten articles in this Special Issue describe advances in real-time sensor networks and systems that are significant enablers of the Industrial IoT paradigm. In the relevant landscape, the domain of wireless networking technologies is centrally positioned, as expected

Design and Implementation of a Self Adaptive Architecture for QoS (SAAQ) in IoT based Wireless Networks

The rapid growth of Internet of Things (IoT) applications has made ensuring quality of service (QoS) in wireless networks essential. This paper presents the design and implementation of a Self-Adaptive Architecture for QoS (SAAQ) in IoT-based wireless networks, using the NS-2 simulation tool as a foundation for analysis and evaluation. The SAAQ framework is carefully tailored to meet the dynamic demands of IoT applications, enabling real-time adjustment of QoS parameters such as packet delivery ratio, throughput, end-to-end delay, packet loss ratio, energy consumption and routing overhead. By integrating with NS-2, a simulation tool in network research, we conduct extensive simulations and experiments to evaluate the SAAQ's effectiveness in diverse IoT scenarios. This paper explores the adaptability and scalability of the SAAQ architecture and results of experiments reveal the practical benefits of the SAAQ in enhancing QoS in a simulated IoT application over other methods such as AODV, AOMDV, and LEACH

QoS in Node-disjoint Routing for Ad Hoc Networks

PhDA mobile ad hoc network (MANET) is a collection of mobile nodes that can communicate with each other without using any fixed infrastructure. It is necessary for MANETs to have efficient routing protocol and quality of service (QoS) mechanism to support multimedia applications such as video and voice. Node-Disjoint Multipath Routing Protocol (NDMR) is a practical protocol in MANETs: it reduces routing overhead dramatically and achieves multiple node-disjoint routing paths. Because QoS support in MANETs is important as best-effort routing is not efficient for supporting multimedia applications, this thesis presents a novel approach to provide that support. In this thesis NDMR is enhanced to provide a QoS enabled NDMR that decreases the transmission delay between source and destination nodes. A multi-rate mechanism is also implemented in the new protocol so that the NDMR QoS can minimise the overall delays. It is shown that these approaches lead to significant performance gains. A modification to NDMR is also proposed to overcome some of the limitations of the original

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs