2,415 research outputs found
Fundamentals of Large Sensor Networks: Connectivity, Capacity, Clocks and Computation
Sensor networks potentially feature large numbers of nodes that can sense
their environment over time, communicate with each other over a wireless
network, and process information. They differ from data networks in that the
network as a whole may be designed for a specific application. We study the
theoretical foundations of such large scale sensor networks, addressing four
fundamental issues- connectivity, capacity, clocks and function computation.
To begin with, a sensor network must be connected so that information can
indeed be exchanged between nodes. The connectivity graph of an ad-hoc network
is modeled as a random graph and the critical range for asymptotic connectivity
is determined, as well as the critical number of neighbors that a node needs to
connect to. Next, given connectivity, we address the issue of how much data can
be transported over the sensor network. We present fundamental bounds on
capacity under several models, as well as architectural implications for how
wireless communication should be organized.
Temporal information is important both for the applications of sensor
networks as well as their operation.We present fundamental bounds on the
synchronizability of clocks in networks, and also present and analyze
algorithms for clock synchronization. Finally we turn to the issue of gathering
relevant information, that sensor networks are designed to do. One needs to
study optimal strategies for in-network aggregation of data, in order to
reliably compute a composite function of sensor measurements, as well as the
complexity of doing so. We address the issue of how such computation can be
performed efficiently in a sensor network and the algorithms for doing so, for
some classes of functions.Comment: 10 pages, 3 figures, Submitted to the Proceedings of the IEE
Cooperative Synchronization in Wireless Networks
Synchronization is a key functionality in wireless network, enabling a wide
variety of services. We consider a Bayesian inference framework whereby network
nodes can achieve phase and skew synchronization in a fully distributed way. In
particular, under the assumption of Gaussian measurement noise, we derive two
message passing methods (belief propagation and mean field), analyze their
convergence behavior, and perform a qualitative and quantitative comparison
with a number of competing algorithms. We also show that both methods can be
applied in networks with and without master nodes. Our performance results are
complemented by, and compared with, the relevant Bayesian Cram\'er-Rao bounds
Feedback Control Goes Wireless: Guaranteed Stability over Low-power Multi-hop Networks
Closing feedback loops fast and over long distances is key to emerging
applications; for example, robot motion control and swarm coordination require
update intervals of tens of milliseconds. Low-power wireless technology is
preferred for its low cost, small form factor, and flexibility, especially if
the devices support multi-hop communication. So far, however, feedback control
over wireless multi-hop networks has only been shown for update intervals on
the order of seconds. This paper presents a wireless embedded system that tames
imperfections impairing control performance (e.g., jitter and message loss),
and a control design that exploits the essential properties of this system to
provably guarantee closed-loop stability for physical processes with linear
time-invariant dynamics. Using experiments on a cyber-physical testbed with 20
wireless nodes and multiple cart-pole systems, we are the first to demonstrate
and evaluate feedback control and coordination over wireless multi-hop networks
for update intervals of 20 to 50 milliseconds.Comment: Accepted final version to appear in: 10th ACM/IEEE International
Conference on Cyber-Physical Systems (with CPS-IoT Week 2019) (ICCPS '19),
April 16--18, 2019, Montreal, QC, Canad
LPDQ: a self-scheduled TDMA MAC protocol for one-hop dynamic lowpower wireless networks
Current Medium Access Control (MAC) protocols for data collection scenarios with a large number of nodes that generate bursty traffic are based on Low-Power Listening (LPL) for network synchronization and Frame Slotted ALOHA (FSA) as the channel access mechanism. However, FSA has an efficiency bounded to 36.8% due to contention effects, which reduces packet throughput and increases energy consumption. In this paper, we target such scenarios by presenting Low-Power Distributed Queuing (LPDQ), a highly efficient and low-power MAC protocol. LPDQ is able to self-schedule data transmissions, acting as a FSA MAC under light traffic and seamlessly converging to a Time Division Multiple Access (TDMA) MAC under congestion. The paper presents the design principles and the implementation details of LPDQ using low-power commercial radio transceivers. Experiments demonstrate an efficiency close to 99% that is independent of the number of nodes and is fair in terms of resource allocation.Peer ReviewedPostprint (author’s final draft
Randomized and efficient time synchronization in dynamic wireless sensor networks: a gossip-consensus-based approach
This paper proposes novel randomized gossip-consensus-based sync (RGCS) algorithms to realize efficient time correction in dynamic wireless sensor networks (WSNs). First, the unreliable links are described by stochastic connections, reflecting the characteristic of changing connectivity gleaned from dynamicWSNs. Secondly, based on the mutual drift estimation, each pair of activated nodes fully adjusts clock rate and offset to achieve network-wide time synchronization by drawing upon the gossip consensus approach. The converge-to-max criterion is introduced to achieve a much faster convergence speed. The theoretical results on the probabilistic synchronization performance of the RGCS are presented. Thirdly, a Revised-RGCS is developed to counteract the negative impact of bounded delays, because the uncertain delays are always present in practice and would lead to a large deterioration of algorithm performances. Finally, extensive simulations are performed on the MATLAB and OMNeT++ platform for performance evaluation. Simulation results demonstrate that the proposed algorithms are not only efficient for synchronization issues required for dynamic topology changes but also give a better performance in term of converging speed, collision rate, and the robustness of resisting delay, and outperform other existing protocols
Modelling Clock Synchronization in the Chess gMAC WSN Protocol
We present a detailled timed automata model of the clock synchronization
algorithm that is currently being used in a wireless sensor network (WSN) that
has been developed by the Dutch company Chess. Using the Uppaal model checker,
we establish that in certain cases a static, fully synchronized network may
eventually become unsynchronized if the current algorithm is used, even in a
setting with infinitesimal clock drifts
Self-Synchronization in Duty-cycled Internet of Things (IoT) Applications
In recent years, the networks of low-power devices have gained popularity.
Typically these devices are wireless and interact to form large networks such
as the Machine to Machine (M2M) networks, Internet of Things (IoT), Wearable
Computing, and Wireless Sensor Networks. The collaboration among these devices
is a key to achieving the full potential of these networks. A major problem in
this field is to guarantee robust communication between elements while keeping
the whole network energy efficient. In this paper, we introduce an extended and
improved emergent broadcast slot (EBS) scheme, which facilitates collaboration
for robust communication and is energy efficient. In the EBS, nodes
communication unit remains in sleeping mode and are awake just to communicate.
The EBS scheme is fully decentralized, that is, nodes coordinate their wake-up
window in partially overlapped manner within each duty-cycle to avoid message
collisions. We show the theoretical convergence behavior of the scheme, which
is confirmed through real test-bed experimentation.Comment: 12 Pages, 11 Figures, Journa
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