15 research outputs found
Optimal Offline and Competitive Online Strategies for Transmitter-Receiver Energy Harvesting
Transmitter-receiver energy harvesting model is assumed, where both the
transmitter and receiver are powered by random energy source. Given a fixed
number of bits, the problem is to find the optimal transmission power profile
at the transmitter and ON-OFF profile at the receiver to minimize the
transmission time. Structure of the optimal offline strategy is derived
together with an optimal offline policy. An online policy with competitive
ratio of strictly less than two is also derived
On Distributed Power Control for Uncoordinated Dual Energy Harvesting Links: Performance Bounds and Near-Optimal Policies
In this paper, we consider a point-to-point link between an energy harvesting
transmitter and receiver, where neither node has the information about the
battery state or energy availability at the other node. We consider a model
where data is successfully delivered only in slots where both nodes are active.
Energy loss occurs whenever one node turns on while the other node is in sleep
mode. In each slot, based on their own energy availability, the transmitter and
receiver need to independently decide whether or not to turn on, with the aim
of maximizing the long-term time-average throughput. We present an upper bound
on the throughput achievable by analyzing a genie-aided system that has
noncausal knowledge of the energy arrivals at both the nodes. Next, we propose
an online policy requiring an occasional one-bit feedback whose throughput is
within one bit of the upper bound, asymptotically in the battery size. In order
to further reduce the feedback required, we propose a time-dilated version of
the online policy. As the time dilation gets large, this policy does not
require any feedback and achieves the upper bound asymptotically in the battery
size. Inspired by this, we also propose a near-optimal fully uncoordinated
policy. We use Monte Carlo simulations to validate our theoretical results and
illustrate the performance of the proposed policies.Comment: 8 page
Universally Near Optimal Online Power Control for Energy Harvesting Nodes
We consider online power control for an energy harvesting system with random
i.i.d. energy arrivals and a finite size battery. We propose a simple online
power control policy for this channel that requires minimal information
regarding the distribution of the energy arrivals and prove that it is
universally near-optimal for all parameter values. In particular, the policy
depends on the distribution of the energy arrival process only through its mean
and it achieves the optimal long-term average throughput of the channel within
both constant additive and multiplicative gaps. Existing heuristics for online
power control fail to achieve such universal performance. This result also
allows us to approximate the long-term average throughput of the system with a
simple formula, which sheds some light on the qualitative behavior of the
throughput, namely how it depends on the distribution of the energy arrivals
and the size of the battery.Comment: the proposed scheme is shown to be optimal both within constant
additive and multiplicative gaps; submitted to Journal on Selected Areas in
Communications - Series on Green Communications and Networking (Issue 3);
revised following reviewers' comment
Energy Harvesting Wireless Sensor Networks: Delay Analysis Considering Energy Costs of Sensing and Transmission
Energy harvesting (EH) provides a means of greatly enhancing the lifetime of
wireless sensor nodes. However, the randomness inherent in the EH process may
cause significant delay for performing sensing operation and transmitting the
sensed information to the sink. Unlike most existing studies on the delay
performance of EH sensor networks, where only the energy consumption of
transmission is considered, we consider the energy costs of both sensing and
transmission. Specifically, we consider an EH sensor that monitors some status
environmental property and adopts a harvest-then-use protocol to perform
sensing and transmission. To comprehensively study the delay performance, we
consider two complementary metrics and analytically derive their statistics:
(i) update age - measuring the time taken from when information is obtained by
the sensor to when the sensed information is successfully transmitted to the
sink, i.e., how timely the updated information at the sink is, and (ii) update
cycle - measuring the time duration between two consecutive successful
transmissions, i.e., how frequently the information at the sink is updated. Our
results show that the consideration of sensing energy cost leads to an
important tradeoff between the two metrics: more frequent updates result in
less timely information available at the sink.Comment: submitted for possible journal publicatio