東華大學圖書館 |

Energy Harvesting Communication Networks: Online Policies, Temperature Considerations, and Age of Information.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Energy Harvesting Communication Networks: Online Policies, Temperature Considerations, and Age of Information./
作者:	Baknina, Abdulrahman.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:	310 p.
附註:	Source: Dissertations Abstracts International, Volume: 80-04, Section: B.
Contained By:	Dissertations Abstracts International80-04B.
標題:	Computer Engineering. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10822438
ISBN:	9780438426849

Energy Harvesting Communication Networks: Online Policies, Temperature Considerations, and Age of Information.
Baknina, Abdulrahman.

Energy Harvesting Communication Networks: Online Policies, Temperature Considerations, and Age of Information. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 310 p.

Source: Dissertations Abstracts International, Volume: 80-04, Section: B.

Thesis (Ph.D.)--University of Maryland, College Park, 2018.

This item must not be sold to any third party vendors.

This dissertation focuses on characterizing energy management policies for energy harvesting communication networks in the presence of stochastic energy arrivals and temperature constraints. When the energy arrivals are stochastic and are known only causally at the transmitter, we study two performance metrics: throughput and age of information (AoI). When the energy harvesting system performance is affected by the change of the temperature, we consider the throughput metric. When the energy arrivals are stochastic, we study the throughput maximization problem for several network settings. We first consider an energy harvesting broadcast channel where a transmitter serves data to two receivers on the downlink. The battery at the transmitter in which the harvested energy is stored is of finite size. We focus on online transmission schemes where the transmitter knows the energy arrivals only causally as they happen. We consider the case of general independent and identically distributed (i.i.d.) energy arrivals, and propose a near-optimal strategy coined fractional power constant cut-off (FPCC) policy. We show that the FPCC policy is near-optimal in that it yields rates that are within a constant gap from the optimal rate region, for all system parameters. Next, we study online transmission policies for a two-user multiple access channel where both users harvest energy from nature. The energy harvests are i.i.d. over time, but can be arbitrarily correlated between the two users. The transmitters are equipped with arbitrary but finite-sized batteries. We propose a distributed fractional power (DFP) policy, which users implement distributedly with no knowledge of the other user's energy arrival or battery state. We show that the proposed DFP is near-optimal as in the broadcast channel case. Then, we consider online power scheduling for energy harvesting channels in which the users incur processing cost per unit time that they are on. The presence of processing costs forces the users to operate in a bursty mode. We consider the single-user and two-way channels. For the single-user case, we consider the case of the general i.i.d.∼energy arrivals. We propose a near-optimal online policy for this case. We then extend our analysis to the case of two-way energy harvesting channels with processing costs; in this case, the users incur processing costs for being on for transmitting or receiving data. Our proposed policy is distributed, which users can apply independently with no need for cooperation or coordination between them. Next, we consider a single-user channel in which the transmitter is equipped with finite-sized data and energy buffers. The transmitter receives energy and data packets randomly and intermittently over time and stores them in the finite-sized buffers. The arrival amounts are known only causally as they happen. We focus on the special case when the energy and data arrivals are fully-correlated. We propose a structured policy and bound its performance by a multiplicative gap from the optimal. We then show that this policy is optimal when the energy arrivals dominate the data arrivals, and is near-optimal when the data arrivals dominate the energy arrivals. Then, we consider another performance metric which captures the freshness of data, i.e., AoI. For this metric, we first consider an energy harvesting transmitter sending status updates to a receiver over an erasure channel. The energy arrivals and the channel erasures are i.i.d. and Bernoulli distributed in each slot. In order to combat the effects of the erasures in the channel and the uncertainty in the energy arrivals, we use channel coding to encode the status update symbols. We consider two types of channel coding: maximum distance separable (MDS) codes and rateless erasure codes. For each of these models, we study two achievable schemes: best-effort and save-and-transmit. We analyze the average AoI under each of these policies. We show that rateless coding with save-and-transmit outperforms all other schemes. Next, we consider a scenario where the transmitter harvests i.i.d. Bernoulli energy arrivals and status updates carry information about an independent message. The transmitter encodes this message into the timings of the status updates. The receiver needs to extract this encoded information, as well as update the status of the observed phenomenon. The timings of the status updates, therefore, determine both the AoI and the message rate (rate). We study the trade-off between the achievable message rate and the achievable average AoI. We propose several achievable schemes and compare their rate-AoI performances. (Abstract shortened by ProQuest.).

ISBN: 9780438426849Subjects--Topical Terms:

1567821
Computer Engineering.
Subjects--Index Terms:

distributed fractional power

Energy Harvesting Communication Networks: Online Policies, Temperature Considerations, and Age of Information.
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500 $a Source: Dissertations Abstracts International, Volume: 80-04, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Ulukus, Sennur.
502 $a Thesis (Ph.D.)--University of Maryland, College Park, 2018.
506 $a This item must not be sold to any third party vendors.
520 $a This dissertation focuses on characterizing energy management policies for energy harvesting communication networks in the presence of stochastic energy arrivals and temperature constraints. When the energy arrivals are stochastic and are known only causally at the transmitter, we study two performance metrics: throughput and age of information (AoI). When the energy harvesting system performance is affected by the change of the temperature, we consider the throughput metric. When the energy arrivals are stochastic, we study the throughput maximization problem for several network settings. We first consider an energy harvesting broadcast channel where a transmitter serves data to two receivers on the downlink. The battery at the transmitter in which the harvested energy is stored is of finite size. We focus on online transmission schemes where the transmitter knows the energy arrivals only causally as they happen. We consider the case of general independent and identically distributed (i.i.d.) energy arrivals, and propose a near-optimal strategy coined fractional power constant cut-off (FPCC) policy. We show that the FPCC policy is near-optimal in that it yields rates that are within a constant gap from the optimal rate region, for all system parameters. Next, we study online transmission policies for a two-user multiple access channel where both users harvest energy from nature. The energy harvests are i.i.d. over time, but can be arbitrarily correlated between the two users. The transmitters are equipped with arbitrary but finite-sized batteries. We propose a distributed fractional power (DFP) policy, which users implement distributedly with no knowledge of the other user's energy arrival or battery state. We show that the proposed DFP is near-optimal as in the broadcast channel case. Then, we consider online power scheduling for energy harvesting channels in which the users incur processing cost per unit time that they are on. The presence of processing costs forces the users to operate in a bursty mode. We consider the single-user and two-way channels. For the single-user case, we consider the case of the general i.i.d.∼energy arrivals. We propose a near-optimal online policy for this case. We then extend our analysis to the case of two-way energy harvesting channels with processing costs; in this case, the users incur processing costs for being on for transmitting or receiving data. Our proposed policy is distributed, which users can apply independently with no need for cooperation or coordination between them. Next, we consider a single-user channel in which the transmitter is equipped with finite-sized data and energy buffers. The transmitter receives energy and data packets randomly and intermittently over time and stores them in the finite-sized buffers. The arrival amounts are known only causally as they happen. We focus on the special case when the energy and data arrivals are fully-correlated. We propose a structured policy and bound its performance by a multiplicative gap from the optimal. We then show that this policy is optimal when the energy arrivals dominate the data arrivals, and is near-optimal when the data arrivals dominate the energy arrivals. Then, we consider another performance metric which captures the freshness of data, i.e., AoI. For this metric, we first consider an energy harvesting transmitter sending status updates to a receiver over an erasure channel. The energy arrivals and the channel erasures are i.i.d. and Bernoulli distributed in each slot. In order to combat the effects of the erasures in the channel and the uncertainty in the energy arrivals, we use channel coding to encode the status update symbols. We consider two types of channel coding: maximum distance separable (MDS) codes and rateless erasure codes. For each of these models, we study two achievable schemes: best-effort and save-and-transmit. We analyze the average AoI under each of these policies. We show that rateless coding with save-and-transmit outperforms all other schemes. Next, we consider a scenario where the transmitter harvests i.i.d. Bernoulli energy arrivals and status updates carry information about an independent message. The transmitter encodes this message into the timings of the status updates. The receiver needs to extract this encoded information, as well as update the status of the observed phenomenon. The timings of the status updates, therefore, determine both the AoI and the message rate (rate). We study the trade-off between the achievable message rate and the achievable average AoI. We propose several achievable schemes and compare their rate-AoI performances. (Abstract shortened by ProQuest.).
590 $a School code: 0117.
650 4 $a Computer Engineering. $3 1567821
650 4 $a Electrical engineering. $3 649834
650 4 $a Information science. $3 554358
650 4 $a Computer science. $3 523869
653 $a distributed fractional power
653 $a energy management policies
653 $a fractional power constant cut-off
653 $a rateless coding
653 $a stochastic energy arrivals
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710 2 $a University of Maryland, College Park. $b Electrical Engineering. $3 1018746
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793 $a English
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