Name
Title | ||
|---|---|---|
Delay-Sensitive Energy-Harvesting Wireless Sensors: Optimal Scheduling, Structural Properties, and Approximation Analysis |
Abstract | ||
|---|---|---|
We consider an energy harvesting sensor transmitting latency-sensitive data over a fading channel. We aim to find the optimal transmission scheduling policy that minimizes the packet queuing delay given the available harvested energy. We formulate the problem as a Markov decision process (MDP) over a state-space spanned by the transmitter’s buffer, battery, and channel states, and analyze the structural properties of the resulting optimal value function, which quantifies the long-run performance of the optimal scheduling policy. We show that the optimal value function (i) is non-decreasing and has increasing differences in the queue backlog; (ii) is non-increasing and has increasing differences in the battery state; and (iii) is submodular in the buffer and battery states. Taking advantage of these structural properties, we derive an approximate value iteration algorithm that provides a controllable tradeoff between approximation accuracy, computational complexity, and memory, and we prove that it converges to a near-optimal value function and policy. Our numerical results confirm these properties and demonstrate that the resulting scheduling policies outperform a greedy policy in terms of queuing delay, buffer overflows, energy efficiency, and sensor outages. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TCOMM.2019.2956510 | IEEE Transactions on Communications |
Keywords | DocType | Volume |
Sensors,Batteries,Scheduling,Energy harvesting,Optimal scheduling,Approximation algorithms,Wireless sensor networks | Journal | 68 |
Issue | ISSN | Citations |
4 | 0090-6778 | 2 |
PageRank | References | Authors |
0.36 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nikhilesh Sharma | 1 | 5 | 2.42 |
| Nicholas Mastronarde | 2 | 240 | 26.93 |
| Jacob Chakareski | 3 | 532 | 58.87 |