A survey of middleware for sensor networks

Henricksen, Karen; Robinson, Ricky

doi:10.1145/1176866.1176877

Cited by 90 publications

(6 citation statements)

References 26 publications

(30 reference statements)

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“…In addition, there have been a number of software development projects on sensor network OSs and middleware including TinyOS, Mate, Magnet, Impala, and Milan [4, 5, 13, 44–49]. Although these projects aim at middleware software for WSNs, they do not address issues in the conceptual management and integration of a large number of sensor networks.…”

Section: Related Workmentioning

confidence: 99%

CSN: The Conceptually Manageable Sensor Network

Joe

Lee

Jeong

2015

International Journal of Distributed Sensor Networks

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For the last decade, computer science and information technology have been rapidly expanding their application areas from computation and data processing inside computers to the real time monitoring and management of the real world outside computers. For those emerging applications such as Internet of Things, the flexible, scalable, and interoperable, collaborating sensor networks are crucial. In this paper, we present a sensor network system called the conceptually manageable sensor network (CSN). CSN is intended to support the conceptual management and integration of sensor networks and to provide well-defined and logical APIs for the facilitation of application development. The CSN design is based on the simple and intuitive conceptual model: sets and message queues. In order to minimize the system development efforts and to inherit the system quality of production level open source software, the CSN system is intentionally implemented as a set of extensions to the open source messaging system called ActiveMQ. We conducted some preliminary usability and performance tests for the current CSN implementation. For the usability test, we used data sets from a real world project for the energy-efficient management of Indoor Air Quality in subway stations. Both usability and performance tests showed promising results.

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Section: Related Workmentioning

confidence: 99%

CSN: The Conceptually Manageable Sensor Network

Joe

Lee

Jeong

2015

International Journal of Distributed Sensor Networks

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“…In our architecture, experiments across multiple gardens are indistinguishable from traditional experiments located at a single site from the perspective of information and control. One architectural solution that has emerged is middleware Middleware solutions targeting sensor networking have been developed in the last decade [45], [46], and approaches for targeting the networked control applications have recently emerged [29].…”

Section: Sega Middlewarementioning

confidence: 99%

Towards Cyber-Eco Systems: Networked Sensing, Inference and Control for Distributed Ecological Experiments

Flikkema

Yamamoto²,

Boegli

et al. 2012

2012 IEEE International Conference on Green Computing and Communications

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New applications are motivating and informing the design of sensor/actuator networks, and, more broadly, research in cyber-physical systems (CPS). Our knowledge of many physical systems is uncertain, so that sensing and actuation must be mediated by inference of the structure and parameters of physical-system models. One CPS application domain of growing interest is ecological systems, motivated by the need to understand plant survival and growth as a function of genetics, environment, and climate change. For this effort to be successful, we must be able to infer coupled, data-driven predictive models of plant growth dynamics in response to climate drivers that allow incorporation of uncertainty. We are developing an architecture and implementation for precise fine-scale control of irrigation in an array of geographicallydistributed outdoor gardens on an elevational gradient of over 1500 m, allowing design of experiments that combine control of temperature and water availability. This paper describes a system architecture and implementation for this class of cybereco systems, including sensor/actuator node design, site-level networking, data assimilation, inference, and distributed control. Among its innovations are a modular, parallel-processing node hardware design allowing real-time processing and heterogeneous nodes, energy-aware hardware/software design, and a networking protocol that builds in trade-offs between energy conservation and latency. Throughout, we emphasize the changes in system architecture required as missions evolve from sensing-only to sensing, inference, and control. We also describe our developmental implementation of the architecture and its planned deployment. Future extensions will likely add negative control of precipitation using active rain-out shelters and additional plant-level control of air or soil temperature.

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“…Adaptive data collection in WSNs has also been investigated by means of middleware solutions for proactive resource adaptation [17]. Among them, many solutions such as [18][19][20] actually focus on dense WSNs where nodes are static (or at most have a limited mobility), and assume some coordination between nodes which is difficult to achieve in sparse WSNs.…”

Section: Related Workmentioning

confidence: 99%

A framework for Resource-Aware Data Accumulation in sparse wireless sensor networks

Shah

Francesco

Anastasi

et al. 2011

Computer Communications

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Wireless sensor networks (WSNs) have become an enabling technology for a wide range of applications. In contrast with traditional scenarios where static sensor nodes are densely deployed, a sparse WSN architecture can also be used in many cases. In a sparse WSN, special mobile data collectors (MDCs) are used to gather data from ordinary sensor nodes. In general, sensor nodes do not know when they will be in contact with the MDC, hence they need to discover its presence in their communication range. To this end, discovery mechanisms based on periodic listening and a duty-cycle have shown to be effective in reducing the energy consumption of sensor nodes. However, if not properly tuned, such mechanisms can hinder the data collection process. In this paper, we introduce a Resource-Aware Data Accumulation (RADA), a novel and lightweight framework which allows nodes to learn the MDC arrival pattern, and tune the discovery duty-cycle accordingly. Furthermore, RADA is able to adapt to changes in the operating conditions, and is capable of effectively supporting a number of different MDC mobility patterns. Simulation results show that our solution obtains a higher discovery efficiency and a lower energy consumption than comparable schemes.

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A survey of middleware for sensor networks

Cited by 90 publications

References 26 publications

CSN: The Conceptually Manageable Sensor Network

CSN: The Conceptually Manageable Sensor Network

Towards Cyber-Eco Systems: Networked Sensing, Inference and Control for Distributed Ecological Experiments

A framework for Resource-Aware Data Accumulation in sparse wireless sensor networks

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