Irfan S. Al-Anbagi

Priority- and Delay-Aware Medium Access for Wireless Sensor Networks in the Smart Grid

Monitoring smart-grid assets in a timely manner is highly desired for emerging smart-grid applications such as transformer monitoring, capacitor bank control, plug-in hybrid-electric-vehicle load management, and power quality assessment. Wireless sensor and actor networks (WSANs) are anticipated to be widely utilized in a wide range of smart-grid applications due to their numerous advantages along with their successful adoption in various critical areas including military and health. For resource-constrained WSANs, transmitting delay-critical data from smart-grid assets calls for data prioritization and delay responsiveness. In this paper, we introduce two medium-access approaches, namely, delay-responsive cross-layer (DRX) data transmission and fair and delay-aware cross-layer (FDRX) data transmission, which aim to address the delay and service requirements of smart grids. DRX is based on delay-estimation and data-prioritization steps that are performed by the application layer, in addition to the MAC layer parameters responding to the delay requirements of the smart-grid application and the network condition. On the other hand, FDRX incorporates fairness into DRX by preventing a few nodes from dominating the communication channel. We provide a comprehensive performance evaluation of those approaches. We show that DRX reduces the end-to-end delay while FDRX has lower collision rate compared with DRX. We outline the tradeoffs regarding these approaches and draw future research directions for robust communication protocols for smart-grid monitoring applications.

A Survey on Cross-Layer Quality-of-Service Approaches in WSNs for Delay and Reliability-Aware Applications

Using wireless sensor networks (WSNs) in delay and reliability critical environments is highly desired due to their unique advantages such as low cost, ease of deployment, and redundancy. However, successful deployment of resource-limited WSNs in such applications requires strict quality-of-service (QoS) provisioning techniques to meet the desired latency and reliability targets of those applications. Implementation of QoS techniques in WSNs is significantly challenging since WSNs have been initially devised for low-data-rate non-real-time applications. Therefore, WSN designers and developers resort to different cross-layer interaction and optimization techniques to provision QoS in WSNs. In this paper, we present a survey on the state of the art of cross-layer QoS approaches in wireless terrestrial sensor networks to achieve delay and reliability bounds in critical applications. Our paper provides a unique classification of cross-layer QoS approaches in WSNs that allows surveying a large amount of studies with utmost clarity. Furthermore, we highlight the main challenges of implementing QoS protocols in WSNs and present an overview of QoS-aware WSN applications.

A Reliable IEEE 802.15.4 Model for Cyber Physical Power Grid Monitoring Systems

Cyber physical systems (CPSs) can significantly improve the resiliency of the smart grid. In CPSs, real time and reliable monitoring require an accurate and stable model of the wireless sensor network (WSN)-based monitoring system. Furthermore, WSNs require strict quality of service (QoS) provisioning as the data generated by the monitored equipment is generally delay and reliability-sensitive. QoS provisioning in WSNs has been widely studied in the literature where most of the work addresses the issue by QoS-aware protocol design. However, analytical models that consider delay, throughput, and power consumption have not matured for CPSs. In this paper, we propose a Markov-based model for cluster-tree WSN topologies that enhances the stability of the WSNs. Cluster-tree deployments are particularly of interest to cyber-physical power grid monitoring systems since they are suitable for large-scale deployments. We perform an exhaustive performance evaluation using different traffic and network conditions in star and cluster-tree WSN topologies. Furthermore, we test the accuracy of our model by performing simulations in environments that are consistent with the analytical model.

Design of a delay-sensitive WSN for wind generation monitoring in the smart grid

Wireless sensor networks (WSNs) are promising tools to change the way the power grid is monitored and controlled. This paper presents the design, simulation and evaluation of ZigBee WSNs that are used for condition monitoring of delay sensitive data in wind turbines. It also presents an approach to reduce the end-to-end delay and provide service differentiation for sensor nodes that are transmitting delay sensitive data by modifying the existing IEEE 802.15.4 MAC protocol. Therefore, the results presented in this paper will assist in optimizing the operation of the smart grid in terms of near real-time asset monitoring and enhance the entire demand response process.

A delay mitigation scheme for WSN-based smart grid substation monitoring

The Quality of Service (QoS) in smart grid communications especially in monitoring smart grid assets is becoming significantly important for emerging smart grid applications. Wireless Sensor Networks (WSNs) are expected to be widely utilized in a broad range of smart grid applications due to their numerous advantages along with their successful adoption in various critical areas including military and health. WSNs protocols are not designed to provide QoS provisioning for monitoring applications. Thus, the use of WSNs in transmitting delay-critical data from smart grid assets calls for data prioritization and delay-mitigation schemes. In this paper, we propose a delay-responsive, cross layer scheme with linear backoff (LDRX) mechanism to address delay and service requirements of the smart grid monitoring applications. The LDRX scheme is designed to operate in cluster-tree WSN topology that is suitable for monitoring wide areas such as electrical substations or large installations. We show that LDRX has greater impact on delay reduction compared to previously proposed WSNs delay reduction schemes.

A low latency data transmission scheme for smart grid condition monitoring applications

Condition monitoring of smart grid assets in a near real time manner is essential for the success of emerging smart grid applications. Wireless Sensor and Actor Networks (WSANs) are likely to be widely employed in a wide range of smart grid applications due to their various advantages. Transmitting delay-critical data from smart grid assets to the controller base station may require data prioritization and delay-responsiveness in condition monitoring applications. In this paper, we introduce a medium access scheme, namely delay-responsive, cross layer (DRX) data transmission that aims to address delay and service differentiation requirements of the smart grid. The DRX scheme is based on delay-estimation and data prioritization procedures that are performed by the application layer for which the MAC layer responds to the delay requirements of the smart grid application and the network condition. We provide a comprehensive performance evaluation of this scheme and show that DRX reduces the end-to-end delay and provide data prioritization to critical data. We outline the tradeoffs regarding this scheme and draw future research directions for robust communication protocols for smart grid condition monitoring applications.

Fairness in delay-aware cross layer data transmission scheme for wireless sensor networks

Prioritization of the data collected by the Wireless Sensor Networks (WSNs) can provide promising performance enhancements for applications that monitor and control the critical systems. Particularly, in smart grid, defense and e-health applications, delivering high priority data with low latency is important. Previous works have focused on various cross layer approaches for providing Quality of Service (QoS) in WSNs. However, in the ad hoc nature of WSNs it is highly challenging to become aware of selfish nodes that may exploit those QoS-aware approaches. In our previous work, we have proposed a delay-aware cross layer technique for WSNs. In this paper, we propose a cross layer scheme that is both fairness-aware and delay-aware. Our fairness in delay-aware cross layer data transmission scheme (FDRX) is based on delay-estimation and data prioritization steps that are performed before the data transmission by the application layer. If the estimated delay is higher than the acceptable latency range for the high priority data, MAC layer parameters respond to the delay requirements of the application and vary channel access mechanism in a fair manner. Our results show that the proposed FDRX scheme is able to reduce end-to-end delay for data demanding timely delivery while the latency of the other packets is slightly impacted. Furthermore, our approach is able to maintain acceptable performance in terms packet delivery and energy consumption.

An adaptive QoS scheme for WSN-based smart grid monitoring

In Wireless Sensor Network (WSN) based smart grid condition monitoring applications (e.g., the detection of a Partial Discharge (PD) event in high voltage transformers), network traffic dramatically increases when cascaded faults occur. Reliability and delay are among the main issues that are affected by this increase in the traffic rates. In this paper, we present an adaptive Quality of Service (QoS) scheme for WSNs that provides service differentiation by reducing the delay of critical data in smart grid monitoring and control applications. This scheme is tailored for large-scale WSN deployments with multi-hop cluster-tree topologies. Analytical and simulation results show that our proposed scheme satisfies the delay requirement of the smart grid while maintaining high reliability.

Delay Critical Smart Grid Applications and Adaptive QoS Provisioning

Wireless sensor networks (WSNs) are anticipated to be widely adopted in the various monitoring and control applications due to their versatility and low cost. One of the most promising and emerging WSNs applications is their use in monitoring smart grid assets. Although WSNs can provide cost efficient and reliable solutions, they are not suitable for delay critical application, because they were initially designed for low data rate applications and they may be challenged when sudden faults or failures occur in the monitored environments. Therefore, to prevent extensive delays of critical data, appropriate quality of service (QoS) techniques should be used. In this paper, we present an adaptive QoS scheme (AQoS) and an adaptive guaranteed time slot (AGTS) allocation scheme for IEEE 802.15.4-based WSNs used in high traffic intensity smart grid monitoring applications. Both AQoS and AGTS schemes can adaptively reduce the end-to-end delay and flexibly tune the GTS to provide the required QoS differentiation to delay critical smart grid monitoring applications.

A realistic and stable Markov-based model for WSNs

Certain Wireless Sensor Network (WSN) applications such as patient monitoring, smart grid and equipment condition monitoring require accurate estimation of specific WSN parameters such as the end-to-end delay, the reliability and the power consumption. The estimation of these parameters calls for an accurate and lightweight WSN model that is suitable for the low processing capabilities of sensor nodes. In this paper, we present a realistic and stable Markov based model for WSNs. We perform a comprehensive performance analysis using different traffic and network conditions. Furthermore, we test the accuracy of our model by conducting extensive simulations in environments that are equivalent to the analytical model. The proposed model takes into account the traffic generation probabilities and considers the impact of a finite MAC-level buffer size on the end-to-end delay, reliability and power consumption.