5,339 research outputs found
Survey on Data-Centric based Routing Protocols for Wireless Sensor Networks
The great concern for energy that grew with the technological advances in the
field of networks and especially in sensor network has triggered various
approaches and protocols that relate to sensor networks. In this context, the
routing protocols were of great interest. The aim of the present paper is to
discuss routing protocols for sensor networks. This paper will focus mainly on
the discussion of the data-centric approach (COUGAR, rumor, SPIN, flooding and
Gossiping), while shedding light on the other approaches occasionally. The
functions of the nodes will be discussed as well. The methodology selected for
this paper is based on a close description and discussion of the protocol. As a
conclusion, open research questions and limitations are proposed to the reader
at the end of this paper
Design and analysis of adaptive hierarchical low-power long-range networks
A new phase of evolution of Machine-to-Machine (M2M) communication has started where vertical Internet of Things (IoT) deployments dedicated to a single application domain gradually change to multi-purpose IoT infrastructures that service different applications across multiple industries. New networking technologies are being deployed operating over sub-GHz frequency bands that enable multi-tenant connectivity over long distances and increase network capacity by enforcing low transmission rates to increase network capacity. Such networking technologies allow cloud-based platforms to be connected with large numbers of IoT devices deployed several kilometres from the edges of the network. Despite the rapid uptake of Long-power Wide-area Networks (LPWANs), it remains unclear how to organize the wireless sensor network in a scaleable and adaptive way. This paper introduces a hierarchical communication scheme that utilizes the new capabilities of Long-Range Wireless Sensor Networking technologies by combining them with broadly used 802.11.4-based low-range low-power technologies. The design of the hierarchical scheme is presented in detail along with the technical details on the implementation in real-world hardware platforms. A platform-agnostic software firmware is produced that is evaluated in real-world large-scale testbeds. The performance of the networking scheme is evaluated through a series of experimental scenarios that generate environments with varying channel quality, failing nodes, and mobile nodes. The performance is evaluated in terms of the overall time required to organize the network and setup a hierarchy, the energy consumption and the overall lifetime of the network, as well as the ability to adapt to channel failures. The experimental analysis indicate that the combination of long-range and short-range networking technologies can lead to scalable solutions that can service concurrently multiple applications
Fast Convergence in Self-stabilizing Wireless Networks.
International audienceThe advent of large scale multi-hop wireless networks highlights problems of fault tolerance and scale in distributed systems, motivating designs that autonomously recover from transient faults and spontaneous reconfigurations. Self-stabilization provides an elegant solution for recovering from such faults. We present a complexity analysis for a family of self-stabilizing vertex coloring algorithms in the context of multi-hop wireless networks. Such "coloring" processes are used in several protocols for solving many different issues (clustering, synchronizing...). Overall, our results show that the actual stabilization time is much smaller than the upper bound provided by previous studies. Similarly, the height of the induced DAG is much lower than the linear dependency on the size of the color domain (that was previously announced). Finally, it appears that symmetry breaking tricks traditionally used to expedite stabilization are in fact harmful when used in networks that are not tightly synchronized
Consensus-based control for a network of diffusion PDEs with boundary local interaction
In this paper the problem of driving the state of a network of identical
agents, modeled by boundary-controlled heat equations, towards a common
steady-state profile is addressed. Decentralized consensus protocols are
proposed to address two distinct problems. The first problem is that of
steering the states of all agents towards the same constant steady-state
profile which corresponds to the spatial average of the agents initial
condition. A linear local interaction rule addressing this requirement is
given. The second problem deals with the case where the controlled boundaries
of the agents dynamics are corrupted by additive persistent disturbances. To
achieve synchronization between agents, while completely rejecting the effect
of the boundary disturbances, a nonlinear sliding-mode based consensus protocol
is proposed. Performance of the proposed local interaction rules are analyzed
by applying a Lyapunov-based approach. Simulation results are presented to
support the effectiveness of the proposed algorithms
Self-stabilization in self-organized multihop wireless networks
International audienceIn large scale multihop wireless networks, flat architectures are not scalable. In order to overcome this major drawback, clusterization is introduced to support self-organization and to enable hierarchical routing. When dealing with multihop wireless networks the robustness is a main issue due to the dynamicity of such networks. Several algorithms have been designed for the clusterization process. As far as we know, very few studies check the robustness feature of their clusterization protocols. Moreover, when it is the case, the evaluation is driven by simulations and never by a theoretical approach. In this paper, we show that a clusterization algorithm, that seems to present good properties of robustness, is self-stabilizing. We propose several enhancements to reduce the stabilization time and to improve stability. The use of a Directed Acyclic Graph ensures that the self-stabilizing properties always hold regardless of the underlying topology. These extra criterion are tested by simulations
Distributed self-(star) minimum connected sensor cover algorithms
Wireless ad-hoc sensor networks are composed of a large number of tiny sensors with embedded microprocessors, that have very limited resources and yet must coordinate amongst themselves to form a connected network. Every sensor has a certain sensing radius, Rs, within which it is capable of covering a particular region by detecting or gathering certain data. Every sensor also has a communication radius, R c, within which it is capable of sending or receiving data; Given a query over a sensor network, the minimum connected sensor cover problem is to select a minimum, or nearly minimum, set of sensors, called a minimum connected sensor cover, such that the selected sensors cover the query region, and form a connected network amongst themselves. In this thesis, we use present three fully distributed, strictly localized, scalable, self-* solutions to the minimum connected sensor cover problem
Constraint and Restoring Force
Long-lived sensor network applications must be able to self-repair and adapt to changing demands. We introduce a new approach for doing so: Constraint and Restoring Force. CRF is a physics-inspired framework for computing scalar fields across a sensor network with occasional changes. We illustrate CRFs usefulness by applying it to gradients, a common building block for sensor network systems. The resulting algorithm, CRF-Gradient, determines locally when to self-repair and when to stop and save energy. CRF-Gradient is self-stabilizing, converges in O(diameter) time, and has been verified experimentally in simulation and on a network of Mica2 motes. Finally we show how CRF can be applied to other algorithms as well, such as the calculation of probability fields
Event-triggered Consensus for Multi-agent Systems with Asymmetric and Reducible Topologies
This paper studies the consensus problem of multi-agent systems with
asymmetric and reducible topologies. Centralized event-triggered rules are
provided so as to reduce the frequency of system's updating. The diffusion
coupling feedbacks of each agent are based on the latest observations from its
in-neighbors and the system's next observation time is triggered by a criterion
based on all agents' information. The scenario of continuous monitoring is
first considered, namely all agents' instantaneous states can be observed. It
is proved that if the network topology has a spanning tree, then the
centralized event-triggered coupling strategy can realize consensus for the
multi-agent system. Then the results are extended to discontinuous monitoring,
where the system computes its next triggering time in advance without having to
observe all agents' states continuously. Examples with numerical simulation are
provided to show the effectiveness of the theoretical results
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