4,381 research outputs found
Wireless industrial monitoring and control networks: the journey so far and the road ahead
While traditional wired communication technologies have played a crucial role in industrial monitoring and control networks over the past few decades, they are increasingly proving to be inadequate to meet the highly dynamic and stringent demands of today’s industrial applications, primarily due to the very rigid nature of wired infrastructures. Wireless technology, however, through its increased pervasiveness, has the potential to revolutionize the industry, not only by mitigating the problems faced by wired solutions, but also by introducing a completely new class of applications. While present day wireless technologies made some preliminary inroads in the monitoring domain, they still have severe limitations especially when real-time, reliable distributed control operations are concerned. This article provides the reader with an overview of existing wireless technologies commonly used in the monitoring and control industry. It highlights the pros and cons of each technology and assesses the degree to which each technology is able to meet the stringent demands of industrial monitoring and control networks. Additionally, it summarizes mechanisms proposed by academia, especially serving critical applications by addressing the real-time and reliability requirements of industrial process automation. The article also describes certain key research problems from the physical layer communication for sensor networks and the wireless networking perspective that have yet to be addressed to allow the successful use of wireless technologies in industrial monitoring and control networks
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
Optimal Compression and Transmission Rate Control for Node-Lifetime Maximization
We consider a system that is composed of an energy constrained sensor node
and a sink node, and devise optimal data compression and transmission policies
with an objective to prolong the lifetime of the sensor node. While applying
compression before transmission reduces the energy consumption of transmitting
the sensed data, blindly applying too much compression may even exceed the cost
of transmitting raw data, thereby losing its purpose. Hence, it is important to
investigate the trade-off between data compression and transmission energy
costs. In this paper, we study the joint optimal compression-transmission
design in three scenarios which differ in terms of the available channel
information at the sensor node, and cover a wide range of practical situations.
We formulate and solve joint optimization problems aiming to maximize the
lifetime of the sensor node whilst satisfying specific delay and bit error rate
(BER) constraints. Our results show that a jointly optimized
compression-transmission policy achieves significantly longer lifetime (90% to
2000%) as compared to optimizing transmission only without compression.
Importantly, this performance advantage is most profound when the delay
constraint is stringent, which demonstrates its suitability for low latency
communication in future wireless networks.Comment: accepted for publication in IEEE Transactions on Wireless
Communicaiton
HoPP: Robust and Resilient Publish-Subscribe for an Information-Centric Internet of Things
This paper revisits NDN deployment in the IoT with a special focus on the
interaction of sensors and actuators. Such scenarios require high
responsiveness and limited control state at the constrained nodes. We argue
that the NDN request-response pattern which prevents data push is vital for IoT
networks. We contribute HoP-and-Pull (HoPP), a robust publish-subscribe scheme
for typical IoT scenarios that targets IoT networks consisting of hundreds of
resource constrained devices at intermittent connectivity. Our approach limits
the FIB tables to a minimum and naturally supports mobility, temporary network
partitioning, data aggregation and near real-time reactivity. We experimentally
evaluate the protocol in a real-world deployment using the IoT-Lab testbed with
varying numbers of constrained devices, each wirelessly interconnected via IEEE
802.15.4 LowPANs. Implementations are built on CCN-lite with RIOT and support
experiments using various single- and multi-hop scenarios
Efficient Power Management based on Application Timing Semantics for Wireless Sensor Networks
This paper proposes Efficient Sleep Scheduling based on Application Timing (ESSAT), a novel power manage-ment scheme that aggressively exploits the timing seman-tics of wireless sensor network applications. We present three ESSAT protocols each of which integrates (1) a light-weight traffic shaper that actively shapes the workload inside the network to achieve predictable timing proper-ties over multiple hops, and (2) a local scheduling algorithm that wakes up nodes just-in-time based on the tim-ing properties of shaped workloads. Our ESSAT protocols have several distinguishing features. First, they can save significant energy with minimal delay penalties. Second, they do not maintain TDMA schedules or communication backbones; as such, they are highly efficient and suitable for resource constrained sensor platforms. Moreover, the protocols are robust in highly dynamic network environ-ments, i.e., they can handle variable multi-hop communication delays and aggregate workloads involving multiple queries, and can adapt to varying workload and network topologies. Our simulations showed that DTS-SS, an ES-SAT protocol, achieved an average node duty cycle 38-87% lower than SPAN, and query latencies 36-98% lower than PSM and SYNC
Data Aggregation and Cross-layer Design in WSNs
Over the past few years, advances in electrical engineering have allowed electronic devices to shrink in both size and cost. It has become possible to incorporate environmental sensors into a single device with a microprocessor and memory to interpret the data and wireless transceivers to communicate the data. These sensor nodes have become small and cheap enough that they can be distributed in very large numbers into the area to be monitored and can be considered disposable. Once deployed, these sensor nodes should be able to self-organize themselves into a usable network. These wireless sensor networks, or WSNs, differ from other ad hoc networks mainly in the way that they are used. For example, in ad hoc networks of personal computers, messages are addressed from one PC to another. If a message cannot be routed, the network has failed. In WSNs, data about the environment is requested by the data sink. If any or multiple sensor nodes can return an informative response to this request, the network has succeeded. A network that is viewed in terms of the data it can deliver as opposed to the individual devices that make it up has been termed a data-centric network [26]. The individual sensor nodes may fail to respond to a query, or even die, as long as the final result is valid. The network is only considered useless when no usable data can be delivered.
In this thesis, we focus on two aspects. The first is data aggregation with accurate timing control. In order to maintain a certain degree of service quality and a reasonable system lifetime, energy needs to be optimized at every stage of system operation. Because wireless communication consumes a major amount of the limited battery power for these sensor nodes, we propose to limit the amount of data transmitted by combining redundant and complimentary data as much as possible in order to transmit smaller and fewer messages. By using mathematical models and computer simulations, we will show that our aggregation-focused protocol does, indeed, extend system lifetime. Our secondary focus is a study of cross-layer design. We argue that the extremely specialized use of WSNs should convince us not to adhere to the traditional OSI networking model. Through our experiments, we will show that significant energy savings are possible when a custom cross-layer communication model is used
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