NDLI: A heuristic evaluation PDS algorithm for energy-efficient delay constrained scheduling over wireless communication

Content Provider	IEEE Xplore Digital Library
Author	Guanjun Xu Hong Jiang Congbin Liu Yong Wang
Copyright Year	2012
Description	Author affiliation: Sichuan electric power corporation Mianyang branch, Mianyang 621010, China (Yong Wang) \|\| Information Institute of Southwest University of Science and Technology, Mianyang 621010, China (Guanjun Xu; Hong Jiang; Congbin Liu)
Abstract	Hard energy constraints impose huge challenges to wireless communication under the constraint of communication delay. In this paper, we consider the problem of energy-efficient point-to-point transmission scheduling of delay sensitive multimedia data over a fading channel. We first formulate the transmission scheduling problem as a Markov Decision Process (MDP) and systematically unravel it by the optimal solution. We then propose a Heuristic Evaluation Post-decision State (HE-PDS) learning algorithm for the problem of energy-efficient scheduling with respect to the communication delay. This algorithm is based on reformulating the value iteration equation by introducing a virtual state called Post-decision State (PDS). The advantages of the proposed algorithm are that: (i) it exploits only part of the information about the system so that less information needs to be learned than when using conventional reinforcement learning algorithms; (ii) it uses the heuristic function and evaluation function to reduce unnecessary action exploration in the whole search space, which severely limits the adaptation speed and runtime performance of conventional reinforcement learning algorithms; (iii) it chooses actions with favorable purpose and efficiency so as to optimize reward function and enhance convergence speed. We compare our algorithm with the traditional Q learning algorithm and PDS learning algorithm in terms of the energy consumption and transmission delay. The simulation results illustrate the performance of the proposed algorithm under various scenarios achieves a better trade-off between energy consumption and delay overhead. Moreover, it can converge in a reasonable number of slots for it to be practically useful with satisfaction of delay constraint.
Starting Page	6013
Ending Page	6017
File Size	171850
Page Count	5
File Format	PDF
ISBN	9781457720529
ISSN	15503607
e-ISBN	9781457720536
e-ISBN	9781457720512
DOI	10.1109/ICC.2012.6364901
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-10
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Delay Wireless communication Energy efficiency Algorithm design and analysis Energy consumption Scheduling Heuristic algorithms reinforcement learning energy-efficient scheduling constrained markov decision process heuristic evaluation algorithm
Content Type	Text
Resource Type	Article

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