Maximizing Network Lifetime of WirelessHART Networks under Graph Routing

Wu, Chengjie; Gunatilaka, Dolvara; Saifullah, Abusayeed; Sha, Mo; Tiwari, Paras Babu; Lu, Chenyang; Chen, Yixin

doi:10.1109/iotdi.2015.43

Cited by 39 publications

(20 citation statements)

References 23 publications

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“…In this paper, all routing graphs were specified before generating schedules. Some previously published routing methods [11], [17] can be used to obtain routing graphs. The manager assigns a time slot and a channel offset to each hop in these routing graphs; the channel offset is used to calculate which channel can be used.…”

Section: System Overviewmentioning

confidence: 99%

“…The set Λ t contains the vertices that have been scheduled in time slot t. If the chosen vertex interferes with the scheduled vertices, it cannot be scheduled in this time slot (lines [13][14], which corresponds to constraint (4.a). Otherwise, it is scheduled when it satisfies constraint (4.b) (lines [15][16][17]. Note that a vertex is scheduled periodically.…”

Section: Our Heuristic Algorithm: Extended Rate-monotonic (E-rm)mentioning

confidence: 99%

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Reliability and Temporality Optimization for Multiple Coexisting WirelessHART Networks in Industrial Environments

Jin

Kong

et al. 2017

IEEE Trans. Ind. Electron.

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Abstract-WirelessHART is a networking technology that is widely used in industrial wireless sensor networks. Its reliability and real-time performance are essential to industrial production. Many works have studied these two aspects, primarily focusing on a single WirelessHART network. However, multiple WirelessHART networks usually coexist in a real industrial environment. Applying existing approaches to such coexisting networks would cause performance degradation due to communication interference among these networks. In this paper, we propose a holistic framework that optimizes both reliability and temporality for multiple coexisting networks. The framework consists of two levels. The upper level targets communication channel management, and the lower level addresses data flow scheduling. For the upper level, we propose a network isolation algorithm that improves the data transmission reliability through dynamically adjusting channel assignments to different WirelessHART networks. For the lower level, we propose data flow scheduling algorithms that guarantee the temporality of data flows within each isolated network. These algorithms minimize the number of channels reserved by each isolated network and further enhance the transmission reliability through alleviating channel resource contention. We conduct trace-driven simulations of the channel management algorithm, and the results demonstrate that our algorithm exhibits stable performance and reduces packet loss by 36%. For the scheduling algorithms, the simulations demonstrate that in contrast with existing algorithms, the greater the number of coexisting networks, the fewer resources our algorithms use. When eight networks coexist, our algorithms outperform existing ones by consuming up to 63% fewer channel resources.

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Section: System Overviewmentioning

confidence: 99%

Section: Our Heuristic Algorithm: Extended Rate-monotonic (E-rm)mentioning

confidence: 99%

Reliability and Temporality Optimization for Multiple Coexisting WirelessHART Networks in Industrial Environments

Jin

Kong

et al. 2017

IEEE Trans. Ind. Electron.

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“…A conflict-aware real-time routing algorithm for industrial WSAN was presented in [35]. An energy-efficient routing approach was introduced in [34]. Energy-aware routing for real-time and reliable wireless industrial sensor networks was introduced in [16].…”

Section: Related Workmentioning

confidence: 99%

“…While the asymmetric routing approach can be based on any source and graph routing algorithms, our current implementation extends the energy-efficient source routing and graph routing algorithms presented in [34]. Those original algorithms were designed to improve the network lifetime of a WirelessHART network, e.g., the operation time till the first field device's battery runs out.…”

Section: Asymmetric Routingmentioning

confidence: 99%

Wireless Routing and Control: A Cyber-Physical Case Study

Li¹,

Ma²,

Westenbroek

et al. 2016

2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS)

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Wireless sensor-actuator networks (WSANs) are being adopted in process industries because of their advantages in lowering deployment and maintenance costs. While there has been significant theoretical advancement in networked control design, only limited empirical results that combine control design with realistic WSAN standards exist. This paper presents a cyberphysical case study on a wireless process control system that integrates state-of-the-art network control design and a WSAN based on the WirelessHART standard. The case study systematically explores the interactions between wireless routing and control design in the process control plant. The network supports alternative routing strategies, including single-path source routing and multi-path graph routing. To mitigate the effect of data loss in the WSAN, the control design integrates an observer based on an Extended Kalman Filter with a model predictive controller and an actuator buffer of recent control inputs. We observe that sensing and actuation can have different levels of resilience to packet loss under this network control design. We then propose a flexible routing approach where the routing strategy for sensing and actuation can be configured separately. Finally, we show that an asymmetric routing configuration with different routing strategies for sensing and actuation can effectively improve control performance under significant packet loss. Our results highlight the importance of co-joining the design of wireless network protocols and control in wireless control systems. * The first two authors contributed equally to this work.

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“…al. [5] Represented the network lifetime maximization problem of WirelessHART network under graph routing and prove it is NP-Hard. They are proposed an optimal algorithm based on integer programming, a linear programming relaxation algorithm and a greedy heuristic algorithm to improve network lifetime of WirelessHART network.…”

Section: Introductionmentioning

confidence: 99%

Analysis of energy efficient connected target coverage algorithm for static and dynamic nodes in IWSNs

Mittal

Aggarwal

Kaur

2016

Int. J. Adv. Intell. Informatics

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Today breakthroughs in wireless technologies have greatly spurred the emergence of industrial wireless sensor networks (IWSNs).To facilitate the adaptation of IWSNs to industrial applications, concerns about networks full coverage and connectivity must be addressed to fulfill reliability and real time requirements. Although connected target coverage algorithms have been studied notice both limitations and applicability of various coverage areas from an industry viewpoint. In this paper is discuss the two energy efficiency connected target coverage (CTC) algorithms CWGC(Communication Weighted Greedy Cover) and OTTC(Overlapped Target and Connected Coverage) algorithm based on dynamic node to resolve the problem of Coverage improvement. This paper uses the simulation in MATLAB represent the performance of two CTC algorithms with Dynamic node to improve network lifetime and low energy consumption and quality of service. Compare the dynamic nodes results with static nodes results

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Maximizing Network Lifetime of WirelessHART Networks under Graph Routing

Cited by 39 publications

References 23 publications

Reliability and Temporality Optimization for Multiple Coexisting WirelessHART Networks in Industrial Environments

Reliability and Temporality Optimization for Multiple Coexisting WirelessHART Networks in Industrial Environments

Wireless Routing and Control: A Cyber-Physical Case Study

Analysis of energy efficient connected target coverage algorithm for static and dynamic nodes in IWSNs

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