The demand for highly lightweight decentralised selfmanagement of Wireless Sensor Networks has lead to the pursuit of emergent or bio-inspired solutions. However, many of the algorithms produced to manage a WSN focus' on one managerial aspect or parameter limiting their usefulness and consuming already scarce resources. We have identified sets of common structures and elements of many well-known emergent algorithms. In this paper present one example algorithm that exploited this knowledge to efficiently manage more than one managerial parameter. This algorithm was then tested using simulations (a standard practice for the field). However, when implementing the algorithm on actual devices we soon found some unexpected results. We discuss this phenomenon and suggest some causes aiming to illustrate that current WSN bio-inspired research simulations have limited usefulness in the real world. Node synchronization while disseminating data over WSNsWireless sensor networks (WSN) are networks of small resource constrained devices which sense the environment and report the results via wireless networks. They allow spatial or temporal measurements of phenomenon previously difficult to analyse [3]. One of the current challenges in the WSN field is the development of management systems which allow WSN to be easily deployed in various application domains [4,6] as different WSN application domains often have different management requirements. However after our five years experience in developing algorithms and applications for WSN we have began to see many common requirements to all. One such requirement is that global system parameters such as time and location need to be managed and ideally together to save resources. However given that WSN are very restricted in terms of resources and usually battery powered, overheads involving communication are to be avoided as much as possible.Therefore lightweight decentralised management solutions are favoured. To this end, we have been investigating the usage of Bio-inspired solutions to the maintenance of global system parameters where the management solution emerges.A definition of an emergent algorithm is given in [2] which state that an emergent algorithm produces predictable, or stable global effects with respect to one or more system parameters, by communicating with only immediate neighbours and in the absence of global control or information. Our method of engineering emergent algorithms is to base them on a simple algorithmic structure which is common to many algorithms that show emergent behaviour.Many bio-inspired algorithms use simple rules and local information to create a global consensus of a single parameter, such as clock time in the flashing firefly algorithm [7], or location in the slime algorithm [11]. Our research has identified the control loop as the core structure of several bio-inspired algorithms and within this we can combine loops either serially, and nested to allow the control of multiple parameters on a global level without the use of a centralised poin...
Wide Area Cyber-Physical Systems (WA-CPSs) are a class of control systems that integrate low-powered sensors, heterogeneous actuators, and computer controllers into large infrastructure that span multi-kilometre distances. Current wireless communication technologies are incapable of meeting the communication requirements of range and bounded delays needed for the control of WA-CPSs. To solve this problem, we use a Control Communication Co-design approach for WA-CPSs, that we refer to as the C 3 approach, to design a novel Low-Power Wide Area (LPWA) MAC protocol called Ctrl-MAC and its associated event-triggered controller that can guarantee the closed-loop stability of a WA-CPS. This is the first article to show that LPWA wireless communication technologies can support the control of WA-CPSs. LPWA technologies are designed to support one-way communication for monitoring and are not appropriate for control. We present this work using an example of a water distribution network application, which we evaluate both through a co-simulator (modeling both physical and cyber subsystems) and testbed deployments. Our evaluation demonstrates full control stability, with up to 50% better packet delivery ratios and 80% less average end-to-end delays when compared to a state-of-the-art LPWA technology. We also evaluate our scheme against an idealised, wired, centralised, control architecture, and show that the controller maintains stability and the overshoots remain within bounds.
This document presents the views expressed in the submissions and discussions at the FAILSAFE workshop about the common problems that plague embedded sensor system deployments in the wild. We present analysis gathered from the submissions and the panel session of the FAILSAFE 2017 workshop held at the SenSys 2017 conference. The FAILSAFE call for papers specifically asked for descriptions of wireless sensor network (WSN) deployments and their problems and failures. The submissions, the questions raised at the presentations, and the panel discussion give us a sufficient body of work to review, and draw conclusions regarding the effect that the environment has as the most common cause of embedded sensor system failures. CCS CONCEPTS • Networks → Routing protocols; • Security and privacy → Security protocols;
This paper presents the LoRaWAN at the Edge Dataset (LoED), an open LoRaWAN packet dataset collected at gateways. Real-world LoRaWAN datasets are important for repeatable sensor-network and communications research and evaluation as, if carefully collected, they provide realistic working assumptions. LoED data is collected from nine gateways over a four month period in a dense urban environment. The dataset contains packet header information and all physical layer properties reported by gateways such as the CRC, RSSI, SNR and spreading factor. Files are provided to analyse the data and get aggregated statistics. The dataset is available at: doi.org/10.5281/zenodo.4048321 CCS CONCEPTS • Networks → Link-layer protocols; • Computer systems organization → Embedded and cyber-physical systems.
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