A Priority Rate-Based Routing Protocol for wireless multimedia sensor networks

The development of affordable hardware has made it possible to transmit multimedia data over a wireless medium using sensor devices. Deployed sensors span larger geographical areas, generating different kinds of traffic that need to be communicated either in real-time or non-real-time mode to the sink. The tiny sized design of sensor nodes has made them even more attractive in various environments as they can be left unattended for longer periods. Since sensor nodes are equipped with limited resources, newer energy-efficient protocols and architectures are required in order to meet requirements within their limited capabilities when dealing with multimedia data. This is because multimedia applications are characterized by strict quality of service requirements that distinctively differentiate them from other data types during transmission. However, the large volume of data produced by the sensor nodes can easily cause traffic congestion making it difficult to meet these requirements. Congestion has negative impacts on the data transmitted as well as the sensor network at large. Failure to control congestion will affect the quality of multimedia data received at the sink and further shorten the system lifetime. Next generation wireless sensor networks are predicted to deploy a different model where service is allocated to multimedia while bearing congestion in mind. Applying traditional wireless sensor routing algorithms to wireless multimedia sensor networks may lead to high delay and poor visual quality for multimedia applications. In this research, a Priority Rate-Based Routing Protocol (PRRP) that assigns priorities to traffic depending on their service requirements is proposed. PRRP detects congestion by using adaptive random early detection (A-RED) and a priority rate-based adjustment technique to control congestion. We study the performance of our proposed multi-path routing algorithm for real-time traffic when mixed with three non real-time traffic each with a different priority: high, medium or low. Simulation results show that the proposed algorithm performs better when compared to two existing algorithms, PCCP and PBRC-SD, in terms of queueing delay, packet loss and throughput

Real-Time Performance of Industrial IoT Communication Technologies: A Review

With the growing need for automation and the ongoing merge of OT and IT, industrial networks have to transport a high amount of heterogeneous data with mixed criticality such as control traffic, sensor data, and configuration messages. Current advances in IT technologies furthermore enable a new set of automation scenarios under the roof of Industry 4.0 and IIoT where industrial networks now have to meet new requirements in flexibility and reliability. The necessary real-time guarantees will place significant demands on the networks. In this paper, we identify IIoT use cases and infer real-time requirements along several axes before bridging the gap between real-time network technologies and the identified scenarios. We review real-time networking technologies and present peer-reviewed works from the past 5 years for industrial environments. We investigate how these can be applied to controllers, systems, and embedded devices. Finally, we discuss open challenges for real-time communication technologies to enable the identified scenarios. The review shows academic interest in the field of real-time communication technologies but also highlights a lack of a fixed set of standards important for trust in safety and reliability, especially where wireless technologies are concerned.Comment: IEEE Internet of Things Journal 2023 | Journal article DOI: 10.1109/JIOT.2023.333250

To mesh or not to mesh: flexible wireless indoor communication among mobile robots in industrial environments

Mobile robots such as automated guided vehicles become increasingly important in industry as they can greatly increase efficiency. For their operation such robots must rely on wireless communication, typically realized by connecting them to an existing enterprise network. In this paper we motivate that such an approach is not always economically viable or might result in performance issues. Therefore we propose a flexible and configurable mixed architecture that leverages on mesh capabilities whenever appropriate. Through experiments on a wireless testbed for a variety of scenarios, we analyse the impact of roaming, mobility and traffic separation and demonstrate the potential of our approach

The 5G Cellular Backhaul Management Dilemma: To Cache or to Serve

With the introduction of caching capabilities into small cell networks (SCNs), new backaul management mechanisms need to be developed to prevent the predicted files that are downloaded by the at the small base stations (SBSs) to be cached from jeopardizing the urgent requests that need to be served via the backhaul. Moreover, these mechanisms must account for the heterogeneity of the backhaul that will be encompassing both wireless backhaul links at various frequency bands and a wired backhaul component. In this paper, the heterogeneous backhaul management problem is formulated as a minority game in which each SBS has to define the number of predicted files to download, without affecting the required transmission rate of the current requests. For the formulated game, it is shown that a unique fair proper mixed Nash equilibrium (PMNE) exists. Self-organizing reinforcement learning algorithm is proposed and proved to converge to a unique Boltzmann-Gibbs equilibrium which approximates the desired PMNE. Simulation results show that the performance of the proposed approach can be close to that of the ideal optimal algorithm while it outperforms a centralized greedy approach in terms of the amount of data that is cached without jeopardizing the quality-of-service of current requests.Comment: Accepted for publication at Transactions on Wireless Communication