Cross-layer activity management in an 802-15.4 sensor network

Mišić, Jelena; Shafi, Shairmina; Mišić, Vojislav B.

doi:10.1109/mcom.2006.1580943

Cited by 36 publications

(16 citation statements)

References 8 publications

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“…Most of these approaches focus on the joint optimization of the physical and MAC layers, or the MAC and networking (e.g., routing) layers. For instance, the activity management scheme presented in [10] jointly exploits the MAC and the physical layer. In addition, only a limited number of works specifically deals with the IEEE 802.15.4/ZigBee standards.…”

Section: Related Workmentioning

confidence: 99%

Reliability and Energy-Efficiency in IEEE 802.15.4/ZigBee Sensor Networks: An Adaptive and Cross-Layer Approach

Francesco

Anastasi

Conti

et al. 2011

IEEE J. Select. Areas Commun.

156

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Abstract-A major concern in wireless sensor networks (WSNs) is energy conservation, since battery-powered sensor nodes are expected to operate autonomously for a long time, e.g., for months or even years. Another critical aspect of WSNs is reliability, which is highly application-dependent. In most cases it is possible to trade-off energy consumption and reliability in order to prolong the network lifetime, while satisfying the application requirements. In this paper we propose an adaptive and cross-layer framework for reliable and energy-efficient data collection in WSNs based on the IEEE 802.15.4/ZigBee standards. The framework involves an energy-aware adaptation module that captures the application's reliability requirements, and autonomously configures the MAC layer based on the network topology and the traffic conditions in order to minimize the power consumption. Specifically, we propose a low-complexity distributed algorithm, called ADaptive Access Parameters Tuning (ADAPT), that can effectively meet the application-specific reliability under a wide range of operating conditions, for both single-hop and multi-hop networking scenarios. Our solution can be integrated into WSNs based on IEEE 802.15.4/ZigBee without requiring any modification to the standards. Simulation results show that ADAPT is very energy-efficient, with near-optimal performance.

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Section: Related Workmentioning

confidence: 99%

Reliability and Energy-Efficiency in IEEE 802.15.4/ZigBee Sensor Networks: An Adaptive and Cross-Layer Approach

Francesco

Anastasi

Conti

et al. 2011

IEEE J. Select. Areas Commun.

156

View full text Add to dashboard Cite

show abstract

“…Some cross-layer design challenges of the physical, MAC, and network layers to minimize the energy consumption of WSNs have been surveyed in [34], [35], [36]. Many of the cross-layer solutions proposed in the literature are hardly useful for the application domain we are targeting, because they require sophisticated processing resources, or instantaneous global network knowledge, which are out of reach of the capabilities of real nodes.…”

Section: Related Workmentioning

confidence: 99%

Breath: An Adaptive Protocol for Industrial Control Applications Using Wireless Sensor Networks

Park

Fischione

Bonivento

et al. 2011

IEEE Trans. on Mobile Comput.

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Abstract-An energy-efficient, reliable and timely data transmission is essential for Wireless Sensor Networks (WSNs) employed in scenarios where plant information must be available for control applications. To reach a maximum efficiency, cross-layer interaction is a major design paradigm to exploit the complex interaction among the layers of the protocol stack. This is challenging because latency, reliability, and energy are at odds, and resource-constrained nodes support only simple algorithms. In this paper, the novel protocol Breath is proposed for control applications. Breath is designed for WSNs where nodes attached to plants must transmit information via multihop routing to a sink. Breath ensures a desired packet delivery and delay probabilities while minimizing the energy consumption of the network. The protocol is based on randomized routing, medium access control, and duty-cycling jointly optimized for energy efficiency. The design approach relies on a constrained optimization problem, whereby the objective function is the energy consumption and the constraints are the packet reliability and delay. The challenging part is the modeling of the interactions among the layers by simple expressions of adequate accuracy, which are then used for the optimization by in-network processing. The optimal working point of the protocol is achieved by a simple algorithm, which adapts to traffic variations and channel conditions with negligible overhead. The protocol has been implemented and experimentally evaluated on a testbed with off-the-shelf wireless sensor nodes, and it has been compared with a standard IEEE 802.15.4 solution. Analytical and experimental results show that Breath is tunable and meets reliability and delay requirements. Breath exhibits a good distribution of the working load, thus ensuring a long lifetime of the network. Therefore, Breath is a good candidate for efficient, reliable, and timely data gathering for control applications.

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“…An adaptive cross-layer framework called TinyCube provides a generic interface and a repository for the multi-layer information exchange and management (Marron et al, 2004). Under the IEEE standard 802.15.4, cross-layer between MAC and PHY has been explored using a distributed algorithm to manage the activities of sensor nodes (Misic et al, 2006).…”

Section: Cross-layer Design For Wsn From Network Infrastructure Aspectmentioning

confidence: 99%

Wireless Sensor Networks for Networked Manufacturing Systems

Li¹,

Zhang²,

Wong³

2010

Factory Automation

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Trend towards the Networked Manufacturing SystemsWith the continuing trend towards globalization and focusing on high value with low volume, the manufacturing system architecture is evolving from traditional centralised model to the distributed model and to the recent networked model. In the modern manufacturing environment, the manufacturing systems are in networked framework via a variety of networking communication systems integrating the heterogeneous collections of manufacturing equipment, devices and real-time information. Such networked manufacturing system monitors and controls with the clear objective of maximizing the Quality of Service (QoS) provided by the prevailing manufacturing resources and to achieve near zero down time operations. For such networked framework for manufacturing and execution, the key issue is how to sustain networked manufacturing operations' capability in providing robust, zerobreakdown performance with various uncertainties (e.g., machine breakdown, device malfunction, sensor failure, communication delay, and data loss). The challenge therefore lies in the identification, characterization and generalization, and development of technologies to minimize their adverse impact on system performance and serviceability. Hence from the aspect of system availability, substantial research efforts have devoted to the prognosis of equipment condition. The objective is to prolong the useful life of critical manufacturing elements by estimating the life span of components, devices and equipment. This kind of technology is widely utilized for maintenance operations with the help of the advancement of sensor and sensor fusion techniques. From the perspective of manufacturing control, the machine health information is able to reflect the prevailing health status of the equipment and influence the control decision for networked manufacturing systems. The supervisory controllers are able to take proactive measures to ensure the continual operation by executing the fall back strategies. However from the aspect of system performance, considering the networked manufacturing systems that are connected through heterogeneous networks, hence, the decision making process is distributed to the individual control agents based on the common global goal. The collaborative decision ensures to make best choice from the consideration for all possible options. Various network models can be applied for such networked manufacturing system, particularly the wireless communication for sensory information fusion. Though such 7 www.intechopen.com

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Cross-layer activity management in an 802-15.4 sensor network

Cited by 36 publications

References 8 publications

Reliability and Energy-Efficiency in IEEE 802.15.4/ZigBee Sensor Networks: An Adaptive and Cross-Layer Approach

Reliability and Energy-Efficiency in IEEE 802.15.4/ZigBee Sensor Networks: An Adaptive and Cross-Layer Approach

Breath: An Adaptive Protocol for Industrial Control Applications Using Wireless Sensor Networks

Wireless Sensor Networks for Networked Manufacturing Systems

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