3,088 research outputs found
From carbon nanotubes and silicate layers to graphene platelets for polymer nanocomposites
In spite of extensive studies conducted on carbon nanotubes and silicate layers for their polymer-based nanocomposites, the rise of graphene now provides a more promising candidate due to its exceptionally high mechanical performance and electrical and thermal conductivities. The present study developed a facile approach to fabricate epoxyâgraphene nanocomposites by thermally expanding a commercial product followed by ultrasonication and solution-compounding with epoxy, and investigated their morphologies, mechanical properties, electrical conductivity and thermal mechanical behaviour. Graphene platelets (GnPs) of 3.5
GEAMS: a Greedy Energy-Aware Multipath Stream-based Routing Protocol for WMSNs
Because sensor nodes operate on power limited batteries, sensor
functionalities have to be designed carefully. In particular, designing
energy-efficient packet forwarding is important to maximize the lifetime of the
network and to minimize the power usage at each node. This paper presents a
Geographic Energy-Aware Multipath Stream-based (GEAMS) routing protocol for
WMSNs. GEAMS routing decisions are made online, at each forwarding node in such
a way that there is no need to global topology knowledge and maintenance. GEAMS
routing protocol performs load-balancing to minimize energy consumption among
nodes using twofold policy: (1) smart greedy forwarding and (2) walking back
forwarding. Performances evaluations of GEAMS show that it can maximize the
network lifetime and guarantee quality of service for video stream transmission
in WMSNs
Two-Hop Routing with Traffic-Differentiation for QoS Guarantee in Wireless Sensor Networks
This paper proposes a Traffic-Differentiated Two-Hop Routing protocol for
Quality of Service (QoS) in Wireless Sensor Networks (WSNs). It targets WSN
applications having different types of data traffic with several priorities.
The protocol achieves to increase Packet Reception Ratio (PRR) and reduce
end-to-end delay while considering multi-queue priority policy, two-hop
neighborhood information, link reliability and power efficiency. The protocol
is modular and utilizes effective methods for estimating the link metrics.
Numerical results show that the proposed protocol is a feasible solution to
addresses QoS service differenti- ation for traffic with different priorities.Comment: 13 page
Selecting source image sensor nodes based on 2-hop information to improve image transmissions to mobile robot sinks in search \& rescue operations
We consider Robot-assisted Search Rescue operations enhanced with some
fixed image sensor nodes capable of capturing and sending visual information to
a robot sink. In order to increase the performance of image transfer from image
sensor nodes to the robot sinks we propose a 2-hop neighborhood
information-based cover set selection to determine the most relevant image
sensor nodes to activate. Then, in order to be consistent with our proposed
approach, a multi-path extension of Greedy Perimeter Stateless Routing (called
T-GPSR) wherein routing decisions are also based on 2-hop neighborhood
information is proposed. Simulation results show that our proposal reduces
packet losses, enabling fast packet delivery and higher visual quality of
received images at the robot sink
Overlapping Multi-hop Clustering for Wireless Sensor Networks
Clustering is a standard approach for achieving efficient and scalable
performance in wireless sensor networks. Traditionally, clustering algorithms
aim at generating a number of disjoint clusters that satisfy some criteria. In
this paper, we formulate a novel clustering problem that aims at generating
overlapping multi-hop clusters. Overlapping clusters are useful in many sensor
network applications, including inter-cluster routing, node localization, and
time synchronization protocols. We also propose a randomized, distributed
multi-hop clustering algorithm (KOCA) for solving the overlapping clustering
problem. KOCA aims at generating connected overlapping clusters that cover the
entire sensor network with a specific average overlapping degree. Through
analysis and simulation experiments we show how to select the different values
of the parameters to achieve the clustering process objectives. Moreover, the
results show that KOCA produces approximately equal-sized clusters, which
allows distributing the load evenly over different clusters. In addition, KOCA
is scalable; the clustering formation terminates in a constant time regardless
of the network size
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
MAP: Medial Axis Based Geometric Routing in Sensor Networks
One of the challenging tasks in the deployment of dense wireless networks (like sensor networks) is in devising a routing scheme for node to node communication. Important consideration includes scalability, routing complexity, the length of the communication paths and the load sharing of the routes. In this paper, we show that a compact and expressive abstraction of network connectivity by the medial axis enables efficient and localized routing. We propose MAP, a Medial Axis based naming and routing Protocol that does not require locations, makes routing decisions locally, and achieves good load balancing. In its preprocessing phase, MAP constructs the medial axis of the sensor field, defined as the set of nodes with at least two closest boundary nodes. The medial axis of the network captures both the complex geometry and non-trivial topology of the sensor field. It can be represented compactly by a graph whose size is comparable with the complexity of the geometric features (e.g., the number of holes). Each node is then given a name related to its position with respect to the medial axis. The routing scheme is derived through local decisions based on the names of the source and destination nodes and guarantees delivery with reasonable and natural routes. We show by both theoretical analysis and simulations that our medial axis based geometric routing scheme is scalable, produces short routes, achieves excellent load balancing, and is very robust to variations in the network model
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