3,158 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
Pseudo-scheduling: A New Approach to the Broadcast Scheduling Problem
The broadcast scheduling problem asks how a multihop network of broadcast
transceivers operating on a shared medium may share the medium in such a way
that communication over the entire network is possible. This can be naturally
modeled as a graph coloring problem via distance-2 coloring (L(1,1)-labeling,
strict scheduling). This coloring is difficult to compute and may require a
number of colors quadratic in the graph degree. This paper introduces
pseudo-scheduling, a relaxation of distance-2 coloring. Centralized and
decentralized algorithms that compute pseudo-schedules with colors linear in
the graph degree are given and proved.Comment: 8th International Symposium on Algorithms for Sensor Systems,
Wireless Ad Hoc Networks and Autonomous Mobile Entities (ALGOSENSORS 2012),
13-14 September 2012, Ljubljana, Slovenia. 12 page
Latency Optimal Broadcasting in Noisy Wireless Mesh Networks
In this paper, we adopt a new noisy wireless network model introduced very
recently by Censor-Hillel et al. in [ACM PODC 2017, CHHZ17]. More specifically,
for a given noise parameter any sender has a probability of
of transmitting noise or any receiver of a single transmission in its
neighborhood has a probability of receiving noise.
In this paper, we first propose a new asymptotically latency-optimal
approximation algorithm (under faultless model) that can complete
single-message broadcasting task in time units/rounds in any
WMN of size and diameter . We then show this diameter-linear
broadcasting algorithm remains robust under the noisy wireless network model
and also improves the currently best known result in CHHZ17 by a
factor.
In this paper, we also further extend our robust single-message broadcasting
algorithm to multi-message broadcasting scenario and show it can broadcast
messages in time rounds. This new robust
multi-message broadcasting scheme is not only asymptotically optimal but also
answers affirmatively the problem left open in CHHZ17 on the existence of an
algorithm that is robust to sender and receiver faults and can broadcast
messages in time rounds.Comment: arXiv admin note: text overlap with arXiv:1705.07369 by other author
A Faithful Distributed Implementation of Dual Decomposition and Average Consensus Algorithms
We consider large scale cost allocation problems and consensus seeking
problems for multiple agents, in which agents are suggested to collaborate in a
distributed algorithm to find a solution. If agents are strategic to minimize
their own individual cost rather than the global social cost, they are endowed
with an incentive not to follow the intended algorithm, unless the tax/subsidy
mechanism is carefully designed. Inspired by the classical
Vickrey-Clarke-Groves mechanism and more recent algorithmic mechanism design
theory, we propose a tax mechanism that incentivises agents to faithfully
implement the intended algorithm. In particular, a new notion of asymptotic
incentive compatibility is introduced to characterize a desirable property of
such class of mechanisms. The proposed class of tax mechanisms provides a
sequence of mechanisms that gives agents a diminishing incentive to deviate
from suggested algorithm.Comment: 8 page
Delay Considerations for Opportunistic Scheduling in Broadcast Fading Channels
We consider a single-antenna broadcast block fading
channel with n users where the transmission is packetbased.
We define the (packet) delay as the minimum number of channel uses that guarantees all n users successfully receive m packets. This is a more stringent notion of delay than average delay and is the worst case (access) delay among the users. A delay optimal scheduling scheme, such as round-robin, achieves the delay of mn. For the opportunistic scheduling (which is throughput optimal) where the transmitter sends the packet to the user with the best channel conditions at each channel use, we derive the mean and variance of the delay for any m and n. For large n and in a homogeneous network, it is proved that the expected delay in receiving one packet by all the receivers scales as n log n, as opposed to n for the round-robin scheduling. We also show that when m grows faster than (log n)^r, for some r > 1, then the delay scales as mn. This roughly determines the timescale required for the system to behave fairly in a homogeneous network. We then propose a scheme to significantly reduce the delay at the expense of a small throughput hit. We further look into the advantage of multiple transmit antennas on the delay. For a system with M antennas in the transmitter where at each channel use packets are sent to M different users, we obtain the expected delay in receiving one packet by all the users
Towards Optimal Distributed Node Scheduling in a Multihop Wireless Network through Local Voting
In a multihop wireless network, it is crucial but challenging to schedule
transmissions in an efficient and fair manner. In this paper, a novel
distributed node scheduling algorithm, called Local Voting, is proposed. This
algorithm tries to semi-equalize the load (defined as the ratio of the queue
length over the number of allocated slots) through slot reallocation based on
local information exchange. The algorithm stems from the finding that the
shortest delivery time or delay is obtained when the load is semi-equalized
throughout the network. In addition, we prove that, with Local Voting, the
network system converges asymptotically towards the optimal scheduling.
Moreover, through extensive simulations, the performance of Local Voting is
further investigated in comparison with several representative scheduling
algorithms from the literature. Simulation results show that the proposed
algorithm achieves better performance than the other distributed algorithms in
terms of average delay, maximum delay, and fairness. Despite being distributed,
the performance of Local Voting is also found to be very close to a centralized
algorithm that is deemed to have the optimal performance
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