65,681 research outputs found
On Optimal Neighbor Discovery
Mobile devices apply neighbor discovery (ND) protocols to wirelessly initiate
a first contact within the shortest possible amount of time and with minimal
energy consumption. For this purpose, over the last decade, a vast number of ND
protocols have been proposed, which have progressively reduced the relation
between the time within which discovery is guaranteed and the energy
consumption. In spite of the simplicity of the problem statement, even after
more than 10 years of research on this specific topic, new solutions are still
proposed even today. Despite the large number of known ND protocols, given an
energy budget, what is the best achievable latency still remains unclear. This
paper addresses this question and for the first time presents safe and tight,
duty-cycle-dependent bounds on the worst-case discovery latency that no ND
protocol can beat. Surprisingly, several existing protocols are indeed optimal,
which has not been known until now. We conclude that there is no further
potential to improve the relation between latency and duty-cycle, but future ND
protocols can improve their robustness against beacon collisions.Comment: Conference of the ACM Special Interest Group on Data Communication
(ACM SIGCOMM), 201
On Heterogeneous Neighbor Discovery in Wireless Sensor Networks
Neighbor discovery plays a crucial role in the formation of wireless sensor
networks and mobile networks where the power of sensors (or mobile devices) is
constrained. Due to the difficulty of clock synchronization, many asynchronous
protocols based on wake-up scheduling have been developed over the years in
order to enable timely neighbor discovery between neighboring sensors while
saving energy. However, existing protocols are not fine-grained enough to
support all heterogeneous battery duty cycles, which can lead to a more rapid
deterioration of long-term battery health for those without support. Existing
research can be broadly divided into two categories according to their
neighbor-discovery techniques---the quorum based protocols and the co-primality
based protocols.In this paper, we propose two neighbor discovery protocols,
called Hedis and Todis, that optimize the duty cycle granularity of quorum and
co-primality based protocols respectively, by enabling the finest-grained
control of heterogeneous duty cycles. We compare the two optimal protocols via
analytical and simulation results, which show that although the optimal
co-primality based protocol (Todis) is simpler in its design, the optimal
quorum based protocol (Hedis) has a better performance since it has a lower
relative error rate and smaller discovery delay, while still allowing the
sensor nodes to wake up at a more infrequent rate.Comment: Accepted by IEEE INFOCOM 201
Communication Primitives in Cognitive Radio Networks
Cognitive radio networks are a new type of multi-channel wireless network in
which different nodes can have access to different sets of channels. By
providing multiple channels, they improve the efficiency and reliability of
wireless communication. However, the heterogeneous nature of cognitive radio
networks also brings new challenges to the design and analysis of distributed
algorithms.
In this paper, we focus on two fundamental problems in cognitive radio
networks: neighbor discovery, and global broadcast. We consider a network
containing nodes, each of which has access to channels. We assume the
network has diameter , and each pair of neighbors have at least ,
and at most , shared channels. We also assume each node has at
most neighbors. For the neighbor discovery problem, we design a
randomized algorithm CSeek which has time complexity
. CSeek is flexible and robust,
which allows us to use it as a generic "filter" to find "well-connected"
neighbors with an even shorter running time. We then move on to the global
broadcast problem, and propose CGCast, a randomized algorithm which takes
time. CGCast uses
CSeek to achieve communication among neighbors, and uses edge coloring to
establish an efficient schedule for fast message dissemination.
Towards the end of the paper, we give lower bounds for solving the two
problems. These lower bounds demonstrate that in many situations, CSeek and
CGCast are near optimal
NATIVE NODE DETECTION IN WIRELESS NETWORKS WITH MULTIPACKET PARTY
In wsn Neighbor discovery is one of the first steps in configuring and managing a wireless network. Most existing studies on neighbor discovery assume a single-packet reception model where only a single packet can be received successfully at a receiver. Neighbor discovery in MPR networks is studied that allow packets from multiple simultaneous transmitters to be received successfully at a receiver. Starting with a clique of n nodes, a simple Aloha-like algorithm is analyzed and show that it takes time to discover all neighbors with high probability when allowing up to k simultaneous transmissions. Two adaptive neighbor discovery algorithms is designed that dynamically adjust the transmission probability for each node. The adaptive algorithms yield improvement over the Aloha-like scheme for a clique with n nodes and are thus order-optimal
FOREIGNER DETECTION TRENDY WIRELESS GRIDS BY MULTI PACKET FUNCTION
The primary idea behind our adaptive neighbor discovery schemes should be to provide feedback for that transmitting nodes permitting individuals to prevent transmitting once they've been discovered by their neighbors. During this paper, motivated using the growing prevalence of multipack reception (MPR) technologies for example CDMA and MIMO, we study neighbor discovery in MPR systems which allow packets from multiple synchronized transmitters to obtain received effectively in the receiver. Beginning obtaining a clique of n nodes, we first evaluate an easy Aloha-like formula and show needed time for you to uncover all neighbors wealthy in probability when permitting around k synchronized transmissions. Neighbor discovery is most likely the procedures in configuring and controlling a hidden network. Most existing studies on neighbor discovery assume just one-packet reception model where just only one packet may be received effectively in the receiver. You have to design two adaptive neighbor discovery calculations that dynamically adjust the transmission probability for every node. We consider first a clique of n nodes by which node transmissions are synchronous and the amount of nodes, n, is famous. We show the adaptive calculations yield an apparent difference within the Aloha-like request any clique with n nodes and they are thus order-optimal. Finally, we evaluate our calculations within the general multi-hop network setting. We show the best possible bound of for the Aloha-like formula once the maximum node degree is D that's typically an issue in n worse in comparison with optimal. In addition, when D is large, we show the adaptive calculations are order optimal, i.e., possess a running time, which inserts the lower bound for the problem
FOREIGNER CONNECTION CONFIDENCE AGAINST SEALE ATTACK IN POINT TO POINT E-COMMERCE
The main idea behind our adaptive neighbor discovery schemes ought to be to provide feedback for your transmitting nodes permitting visitors to prevent transmitting once they have been discovered by their neighbors. In this paper, motivated while using growing prevalence of multipack reception (MPR) technologies for instance CDMA and MIMO, we study neighbor discovery in MPR systems which permit packets from multiple synchronized transmitters to acquire received effectively within the receiver. Beginning acquiring a clique of n nodes, we first evaluate a simple Aloha-like formula and show needed time to uncover all neighbors wealthy in probability when permitting around k synchronized transmissions. Neighbor discovery is the measures in configuring and controlling a concealed network. Most existing studies on neighbor discovery assume only one-packet reception model where just one packet might be received effectively within the receiver. You need to design two adaptive neighbor discovery calculations that dynamically adjust the transmission probability for each node. We consider first a clique of n nodes through which node transmissions are synchronous and the quantity of nodes, n, is known. We show the adaptive calculations yield an evident difference inside the Aloha-like request any clique with n nodes and they're thus order-optimal. Finally, we evaluate our calculations inside the general multi-hop network setting. We show the perfect bound of for that Aloha-like formula when the maximum node degree is D that's typically a problem in n worse in comparison to optimal. Additionally, when D is big, we show the adaptive calculations are order optimal, i.e., have a very running time, which inserts the low bound for that problem
Combinatorics of least squares trees
A recurring theme in the least squares approach to phylogenetics has been the
discovery of elegant combinatorial formulas for the least squares estimates of
edge lengths. These formulas have proved useful for the development of
efficient algorithms, and have also been important for understanding
connections among popular phylogeny algorithms. For example, the selection
criterion of the neighbor-joining algorithm is now understood in terms of the
combinatorial formulas of Pauplin for estimating tree length.
We highlight a phylogenetically desirable property that weighted least
squares methods should satisfy, and provide a complete characterization of
methods that satisfy the property. The necessary and sufficient condition is a
multiplicative four point condition that the the variance matrix needs to
satisfy. The proof is based on the observation that the Lagrange multipliers in
the proof of the Gauss--Markov theorem are tree-additive. Our results
generalize and complete previous work on ordinary least squares, balanced
minimum evolution and the taxon weighted variance model. They also provide a
time optimal algorithm for computation
Talk More Listen Less: Energy-Efficient Neighbor Discovery in Wireless Sensor Networks
Neighbor discovery is a fundamental service for initialization and managing
network dynamics in wireless sensor networks and mobile sensing applications.
In this paper, we present a novel design principle named Talk More Listen Less
(TMLL) to reduce idle-listening in neighbor discovery protocols by learning the
fact that more beacons lead to fewer wakeups. We propose an extended neighbor
discovery model for analyzing wakeup schedules in which beacons are not
necessarily placed in the wakeup slots. Furthermore, we are the first to
consider channel occupancy rate in discovery protocols by introducing a new
metric to trade off among duty-cycle, latency and channel occupancy rate.
Guided by the TMLL principle, we have designed Nihao, a family of
energy-efficient asynchronous neighbor discovery protocols for symmetric and
asymmetric cases. We compared Nihao with existing state of the art protocols
via analysis and real-world testbed experiments. The result shows that Nihao
significantly outperforms the others both in theory and practice.Comment: 9 pages, 14 figures, published in IEEE INFOCOM 201
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