SMDP-Based Resource Allocation for Wireless Networks with Energy Harvesting Constraints

Baljon, Mohammed; Li, Mushu; Liang, Hongbin; Zhao, Lian

doi:10.1109/vtcfall.2017.8288138

Cited by 5 publications

(5 citation statements)

References 9 publications

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“…A discounted reward is adopted in their system model, based on which, the authors further proposed a value iteration method to derive the optimal policy. In [11], SMDP is first applied to energy harvesting wireless networks. For problem-solving, the authors adopted a model-based policy…”

Section: Event-driven Smdpmentioning

confidence: 99%

Adaptive Processor Frequency Adjustment for Mobile-Edge Computing With Intermittent Energy Supply

Huang

Lin

Hong

et al. 2022

IEEE Internet Things J.

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With astonishing speed, bandwidth, and scale, Mobile Edge Computing (MEC) has played an increasingly important role in the next generation of connectivity and service delivery. Yet, along with the massive deployment of MEC servers, the ensuing energy issue is now on an increasingly urgent agenda. In the current context, the large scale deployment of renewable-energy-supplied MEC servers is perhaps the most promising solution for the incoming energy issue. Nonetheless, as a result of the intermittent nature of their power sources, these special design MEC server must be more cautious about their energy usage, in a bid to maintain their service sustainability as well as service standard. Targeting optimization on a single-server MEC scenario, we in this paper propose NAFA, an adaptive processor frequency adjustment solution, to enable an effective plan of the server's energy usage. By learning from the historical data revealing request arrival and energy harvest pattern, the deep reinforcement learning-based solution is capable of making intelligent schedules on the server's processor frequency, so as to strike a good balance between service sustainability and service quality. The superior performance of NAFA is substantiated by real-data-based experiments, wherein NAFA demonstrates up to 20% increase in average request acceptance ratio and up to 50% reduction in average request processing time.

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Section: Event-driven Smdpmentioning

confidence: 99%

Adaptive Processor Frequency Adjustment for Mobile-Edge Computing With Intermittent Energy Supply

Huang

Lin

Hong

et al. 2022

IEEE Internet Things J.

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“…Various optimization tools could be employed in load balancing problem for possible solutions, such as Semi-Markov Decision Process (SMDP). The flexible applications of SMDP are explored in the published works [47,48].…”

Section: Contributionsmentioning

confidence: 99%

Load balancing for smart grid: centralized and distributed approaches

Li¹,

Zhao²

2022

Preprint

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As one of the greatest concerns in the context of smart grid, the load balancing problem is addressed by improving the electrical power efficiency and stability via scheduling power loads, thereby shaping the power demand into the desired pattern. The research explores the load balancing strategies to reduce the demand fluctuations in the smart grid systems. Centralized and decentralized load balancing methodologies are discussed. For centralized approaches, offline and online exact power allocation methods are investigated by utilizing the geometric water-filling (GWF) approach. Furthermore, decentralized load balancing problem is discussed at power distribution sub-network level. Electrical vehicle (EV) fleeting among the neighbouring charging stations is considered. Load balancing for the whole grid is achieved by local optimization processes via Proximal Jacobian Alternating Direction Method of Multipliers (ADMM) technique. Overall, facilitated by our proposed strategies, the reliability of the electric grid can be enhanced.

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“…Our previous work [88], proposed a resource allocation framework of a point-to-point wireless communication system with EH constraints based on SMDP approach that maximizes the network throughput by considering channel adaptation only. Since the assignment of constellation only depends on the channel gain, this scheme may give an upper bound of the achievable physical layer performance by considering two assumptions: the buffer is infinite, and has data all the time to transmit with any chosen constellation.…”

Section: Chapter 5 Cross-layer Adaptive Transmission Techniques For Eh Systems Over Fading Channelsmentioning

confidence: 99%

“…The system reward is derived by taking into account both income and cost of the proposed system as well as the variability feature of the resources. In [88], CHAPTER 5. CROSS-LAYER ADAPTIVE TRANSMISSION TECHNIQUES FOR EH SYSTEMS OVER FADING CHANNELS a novel framework based on SMDP approach is formulated for a point-to-point wireless communication with EH constraints.…”

Section: Chapter 5 Cross-layer Adaptive Transmission Techniques For Eh Systems Over Fading Channelsmentioning

confidence: 99%

“…Wireless communication powered by Energy Harvesting (EH) is a promising approach to prolong the lifetimes of wireless networks by eliminating the need for manual battery replacement while clean and renewable energy is approved. Moreover, it has become more desirable to reduce the world's energy consumption.Parts of Chapter 4 are presented and published at the IEEE Vehicular Technology Conference (VTC) in Toronto, Canada[88].…”

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confidence: 99%

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Resource Allocation for Energy Harvesting Communication Systems over Fading Channels

Baljon¹

2021

Preprint

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Energy Harvesting (EH) is an emerging communications paradigm to defeat the limitation of network longevity by recharging the nodes by harvesting energy from the environment. The Energy Harvesting Network (EHN) requires a stable and efficient power control scheme like other conventional communication systems. It is more complicated than conventional communication networks, in that it should not only consider the quality of service requirements of the network but also adapt to the randomness of the energy arrival. In this thesis, several optimal offline and online resource allocation strategies for point-to-point and two-hop EH communication networks over wireless fading channels are investigated. As a first step, the RGWF (Recursive Geometric Water-filling) algorithm is introduced, which provides an optimal offline transmission policy for a point-to-point EH communication system. Next, a network composed of a source, a relay, and a destination, where the source is an EH node is considered. Joint time scheduling and power allocation problems are formulated to maximize the network throughput by considering conventional and bufferaided link adaptive relaying protocols. Based on the modified RGWF algorithm, the joint power allocation and transmission time scheduling problem are decoupled, and efficient offline schemes are proposed for a two-hop wireless network for delay-tolerant and delay sensitive applications. In the second part, the aim is to obtain the optimal transmission policy that maximizes the average total throughput of a point-to-point EH communication system with low and high data arrival rate in an online manner. The solution is obtained using dynamic programming by casting the proposed problem as a semi-Markov decision process (SMDP). In a delay-tolerant approach with high data rate, a cross-layer adaptation is considered, where the proposed policy chooses modulation constellation for EH networks dynamically, depending on battery state, data buffer state in addition to channel state. The proposed SMDP-based dynamic programming approach has proven to be dynamically adaptive to the change of the channel and/or buffer states that optimally satisfy the BER requirements at the physical layer, and the overflow requirements at the data-link layer.

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SMDP-Based Resource Allocation for Wireless Networks with Energy Harvesting Constraints

Cited by 5 publications

References 9 publications

Adaptive Processor Frequency Adjustment for Mobile-Edge Computing With Intermittent Energy Supply

Adaptive Processor Frequency Adjustment for Mobile-Edge Computing With Intermittent Energy Supply

Load balancing for smart grid: centralized and distributed approaches

Resource Allocation for Energy Harvesting Communication Systems over Fading Channels

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