29,496 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
Connectivity-Aware UAV Path Planning with Aerial Coverage Maps
Cellular networks are promising to support effective wireless communications
for unmanned aerial vehicles (UAVs), which will help to enable various
long-range UAV applications. However, these networks are optimized for
terrestrial users, and thus do not guarantee seamless aerial coverage. In this
paper, we propose to overcome this difficulty by exploiting controllable
mobility of UAVs, and investigate connectivity-aware UAV path planning. To
explicitly impose communication requirements on UAV path planning, we introduce
two new metrics to quantify the cellular connectivity quality of a UAV path.
Moreover, aerial coverage maps are used to provide accurate locations of
scattered coverage holes in the complicated propagation environment. We
formulate the UAV path planning problem as finding the shortest path subject to
connectivity constraints. Based on graph search methods, a novel
connectivity-aware path planning algorithm with low complexity is proposed. The
effectiveness and superiority of our proposed algorithm are demonstrated using
the aerial coverage map of an urban section in Virginia, which is built by ray
tracing. Simulation results also illustrate a tradeoff between the path length
and connectivity quality of UAVs.Comment: This paper has been accepted by IEEE WCNC 201
On Connectivity of Wireless Sensor Networks with Directional Antennas.
In this paper, we investigate the network connectivity of wireless sensor networks with directional antennas. In particular, we establish a general framework to analyze the network connectivity while considering various antenna models and the channel randomness. Since existing directional antenna models have their pros and cons in the accuracy of reflecting realistic antennas and the computational complexity, we propose a new analytical directional antenna model called the iris model to balance the accuracy against the complexity. We conduct extensive simulations to evaluate the analytical framework. Our results show that our proposed analytical model on the network connectivity is accurate, and our iris antenna model can provide a better approximation to realistic directional antennas than other existing antenna models
Performance of wireless network coding: motivating small encoding numbers
This paper focuses on a particular transmission scheme called local network
coding, which has been reported to provide significant performance gains in
practical wireless networks. The performance of this scheme strongly depends on
the network topology and thus on the locations of the wireless nodes. Also, it
has been shown previously that finding the encoding strategy, which achieves
maximum performance, requires complex calculations to be undertaken by the
wireless node in real-time.
Both deterministic and random point pattern are explored and using the
Boolean connectivity model we provide upper bounds for the maximum coding
number, i.e., the number of packets that can be combined such that the
corresponding receivers are able to decode. For the models studied, this upper
bound is of order of , where denotes the (mean) number of
neighbors. Moreover, achievable coding numbers are provided for grid-like
networks. We also calculate the multiplicative constants that determine the
gain in case of a small network. Building on the above results, we provide an
analytic expression for the upper bound of the efficiency of local network
coding. The conveyed message is that it is favorable to reduce computational
complexity by relying only on small encoding numbers since the resulting
expected throughput loss is negligible.Comment: 8 pages, 10 figure
A Key Pre-Distribution Scheme based on Multiple Block Codes for Wireless Sensor Networks
A key pre-distribution scheme (KPS) based on multiple codewords of block
codes is presented for wireless sensor networks. The connectivity and security
of the proposed KPS, quantified in terms of probabilities of sharing common
keys for communications of pairs of nodes and their resilience against
colluding nodes, are analytically assessed. The analysis is applicable to both
linear and nonlinear codes and is simplified in the case of maximum distance
separable codes. It is shown that the multiplicity of codes significantly
enhances the security and connectivity of KPS at the cost of a modest increase
of the nodes storage. Numerical and simulation results are provided, which
sheds light on the effect of system parameters of the proposed KPS on its
complexity and performance. Specifically, it is shown that the probability of
resilience of secure pairs against collusion of other nodes only reduces slowly
as the number of colluding nodes increase
Resource Allocation in Mobile WiMAX Network: An Optimal Approach
In the last few years there has been significant growth in the area of
wireless communication. IEEE 802.16/WiMAX is the network which is designed for
providing high speed wide area broadband wireless access; WiMAX is an emerging
wireless technology for creating multi-hop Mesh network. Future generation
networks will be characterized by variable and high data rates, Quality of
Services (QoS), seamless mobility both within a network and between networks of
different technologies and service providers. A technology is developed to
accomplish these necessities is regular by IEEE, is 802.16, also called as
WiMAX (Worldwide Interoperability for Microwave Access). This architecture aims
to apply Long range connectivity, High data rates, High security, Low power
utilization and Excellent Quality of Services and squat deployment costs to a
wireless access technology on a metropolitan level. In this paper we have
observed the performance analysis of location based resource allocation for
WiMAX and WLAN-WiMAX client and in second phase we observed the rate-adaptive
algorithms. We know that base station (BS) is observed the ranging first for
all subscribers then established the link between them and in final phase they
will allocate the resource with Subcarriers allocation according to the demand
(UL) i.e. video, voice and data application. We propose linear approach,
Active-Set optimization and Genetic Algorithm for Resource Allocation in
downlink Mobile WiMAX networks. Purpose of proposed algorithms is to optimize
total throughput. Simulation results show that Genetic Algorithm and Active-Set
algorithm performs better than previous methods in terms of higher capacities
but GA have high complexity then active set
Improved Interference in Wireless Sensor Networks
Given a set of sensor node distributed on a 2-dimensional
plane and a source node , the {\it interference problem} deals
with assigning transmission range to each such that the
members in maintain connectivity predicate , and the
maximum/total interference is minimum. We propose algorithm for both {\it
minimizing maximum interference} and {\it minimizing total interference} of the
networks. For minimizing maximum interference we present optimum solution with
running time for connectivity predicate like strong connectivity, broadcast ( is the source), -edge(vertex)
connectivity, spanner, where is the time complexity for
checking the connectivity predicate . The running time of the
previous best known solution was [Bil and
Proietti, 2008].
For the minimizing total interference we propose optimum algorithm for the
connectivity predicate broadcast. The running time of the propose algorithm is
O(n). For the same problem, the previous best known result was -factor approximation algorithm [Bil and Proietti, 2008]. We
also propose a heuristic for minimizing total interference in the case of
strongly connected predicate and compare our result with the best result
available in the literature. Experimental results demonstrate that our
heuristic outperform existing result.Comment: 10 pages, 1 figur
A Connectivity-Aware Approximation Algorithm for Relay Node Placement in Wireless Sensor Networks
In two-tiered Wireless Sensor Networks (WSNs) relay node placement is one of
the key factors impacting the network energy consumption and the system
overhead. In this paper, a novel connectivity-aware approximation algorithm for
relay node placement in WSNs is proposed to offer a major step forward in
saving system overhead. Specifically, a unique Local Search Approximation
Algorithm (LSAA) is introduced to solve the Relay Node Single Cover (RNSC)
problem. In this proposed LSAA approach, the sensor nodes are allocated into
groups and then a local Set Cover (SC) for each group is achieved by a local
search algorithm. The union set of all local SCs constitutes a SC of the RNSC
problem. The approximation ratio and the time complexity of the LSAA are
analyzed by rigorous proof. Additionally, the LSAA approach has been extended
to solve the relay node double cover problem. Then, a Relay Location Selection
Algorithm (RLSA) is proposed to utilize the resulting SC from LSAA in combining
RLSA with the minimum spanning tree heuristic to build the high-tier
connectivity. As the RLSA searches for a nearest location to the sink node for
each relay node, the high-tier network built by RLSA becomes denser than that
by existing works. As a result, the number of added relay nodes for building
the connectivity of the high-tier WSN can be significantly saved. Simulation
results clearly demonstrate that the proposed LSAA outperforms the approaches
reported in literature and the RLSA-based algorithm can noticeably save relay
nodes newly deployed for the high-tier connectivity.Comment: 14 pages, 24 figure
A time dependent performance model for multihop wireless networks with CBR traffic
In this paper, we develop a performance modeling technique for analyzing the time varying network layer queueing behavior of multihop wireless networks with constant bit rate traffic. Our approach is a hybrid of fluid flow queueing modeling and a time varying connectivity matrix. Network queues are modeled using fluid-flow based differential equation models which are solved using numerical methods, while node mobility is modeled using deterministic or stochastic modeling of adjacency matrix elements. Numerical and simulation experiments show that the new approach can provide reasonably accurate results with significant improvements in the computation time compared to standard simulation tools. © 2010 IEEE
Leveraging Physical Layer Capabilites: Distributed Scheduling in Interference Networks with Local Views
In most wireless networks, nodes have only limited local information about
the state of the network, which includes connectivity and channel state
information. With limited local information about the network, each node's
knowledge is mismatched; therefore, they must make distributed decisions. In
this paper, we pose the following question - if every node has network state
information only about a small neighborhood, how and when should nodes choose
to transmit? While link scheduling answers the above question for
point-to-point physical layers which are designed for an interference-avoidance
paradigm, we look for answers in cases when interference can be embraced by
advanced PHY layer design, as suggested by results in network information
theory.
To make progress on this challenging problem, we propose a constructive
distributed algorithm that achieves rates higher than link scheduling based on
interference avoidance, especially if each node knows more than one hop of
network state information. We compare our new aggressive algorithm to a
conservative algorithm we have presented in [1]. Both algorithms schedule
sub-networks such that each sub-network can employ advanced
interference-embracing coding schemes to achieve higher rates. Our innovation
is in the identification, selection and scheduling of sub-networks, especially
when sub-networks are larger than a single link.Comment: 14 pages, Submitted to IEEE/ACM Transactions on Networking, October
201
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