| 1. |
- Farag, Hossam, et al.
(författare)
-
A Delay-Bounded MAC Protocol for Mission- and Time-Critical Applications in Industrial Wireless Sensor Networks
- 2018
-
Ingår i: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 18:6, s. 2607-2616
-
Tidskriftsartikel (refereegranskat)abstract
- Industrial Wireless Sensor Networks (IWSNs) designedfor mission- and time-critical applications require timelyand deterministic data delivery within stringent deadline bounds.Exceeding delay limits for such applications can lead to system malfunction or ultimately dangerous situations that can threaten human safety. In this paper, we propose SS-MAC, an efficient slot stealing MAC protocol to guarantee predictable and timely channel access for time-critical data in IWSNs. In the proposed SS-MAC, aperiodic time-critical traffic opportunistically steals time slots assigned to periodic non-critical traffic. Additionally, a dynamic deadline-based scheduling is introduced to provide guaranteed channel access in emergency and event-based situations where multiple sensor nodes are triggered simultaneously to transmit time-critical data to the controller. The proposed protocol is evaluated mathematically to provide the worst-case delay bound for the time-critical traffic. Performance comparisons are carried out between the proposed SS-MAC and WirelessHARTstandard and they show that, for the time-critical traffic, theproposed SS-MAC can achieve, at least, a reduction of almost 30% in the worst-case delay with a significant channel utilization efficiency.
|
|
| 2. |
- Farag, Hossam, et al.
(författare)
-
Priority-Aware Wireless Fieldbus Protocol for Mixed-Criticality Industrial Wireless Sensor Networks
- 2019
-
Ingår i: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 19:7, s. 2767-2780
-
Tidskriftsartikel (refereegranskat)abstract
- Industrial wireless sensor networks are becoming popular for critical monitoring and control applications in industrial automation systems. For such type of applications, providing reliable real-time performance regarding data delivery is considered as a fundamental challenge. The problem becomes more prominent with mixed-criticality systems, where different data flow with different levels of criticality (importance) coexist and characterized by different requirements regarding delay and reliability. In this paper, we propose a wireless fieldbus protocol to enable real-time communication and service differentiation for cluster-based mixed-criticality networks. A process monitoring scenario of plastic extrusion is used to define the protocol requirements and elaborate the working principle of the proposed work. In our proposed protocol, each data flow is scheduled for channel access based on its criticality level using a distributed prioritized medium access mechanism that ensures a guaranteed channel access for the most critical traffic over other traffic types. The performance of the proposed protocol is analyzed analytically using a discrete-time Markov chain model to evaluate the performance in terms of delay and throughput. Moreover, the extensive simulations are conducted to prove the analytical claims and different performance assessments are provided, which also demonstrate the effectiveness of the proposed approach compared with the related existing work.
|
|
| 3. |
- Guntupalli, Lakshmikanth, et al.
(författare)
-
Energy Efficient Consecutive Packet Transmissions in Receiver-initiated Wake-up Radio Enabled WSNs
- 2018
-
Ingår i: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 18:11, s. 4733-4745
-
Tidskriftsartikel (refereegranskat)abstract
- In wake-up radio (WuR)-enabled wireless sensor networks, data communication among nodes is triggered in an on-demand manner, by either a sender or a receiver. For receiver-initiated WuR (RI-WuR), a~receiving node wakes up sending nodes through a wake-up call. Correspondingly sending nodes transmit packets in a traditional way by competing with one another multiple times in a single operational cycle. In~this paper, we propose a receiver-initiated consecutive packet transmission WuR (RI-CPT-WuR) medium access control (MAC) protocol, which eliminates multiple competitions to achieve higher energy efficiency. Furthermore, we develop two associated discrete time Markov chains (DTMCs) for evaluating the performance of RI-CPT-WuR and an existing RI-WuR MAC protocol. Using the solutions from the DTMC models, closed-form expressions for network throughput, average delay, packet reliability ratio, energy consumption and lifetime, and energy efficiency for both protocols are obtained. Numerical results demonstrate the superiority of the RI-CPT-WuR protocol.
|
|
| 4. |
- Zhang, Weiting, et al.
(författare)
-
CarNet : A Dual Correlation Method for Health Perception of Rotating Machinery
- 2019
-
Ingår i: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 19:16, s. 7095-7106
-
Tidskriftsartikel (refereegranskat)abstract
- As a key component of rotating machinery, the health perception of hearings is essential to ensure the safe and reliable operation of industrial equipment. In recent years, research on equipment health perception based on data-driven methods has received extensive attention. Overall, most studies focus on several public datasets to verify the effectiveness of their algorithms. However, the scale of these datasets cannot completely satisfy the representation learning of deep models. Therefore, this paper proposes a novel method, called CarNet, to obtain a more robust model and ensure that the model is sufficiently trained on a limited dataset. Specifically, it is composed of a data augmentation method named equitable sliding stride segmentation (ESSS) and a hybrid-stacked deep model (HSDM). The ESSS not only amplifies the scale of the original dataset but also enables newly generated data with both spatial and temporal correlations. The HSDM can, therefore, extract shallow spatial features and deep temporal information from the strongly correlated 2-dimensional (2-D) sensor array using a CNN and a bi-GRU, respectively. Moreover, the integrated attention mechanism contributes to focusing limited resources on informative areas. The effectiveness of CarNet is evaluated on the CWRU dataset, and an optimal diagnostic accuracy of 99.92% is achieved.
|
|
