6,938 research outputs found
Towards self-powered wireless sensor networks
Ubiquitous computing aims at creating smart environments in which computational and communication capabilities permeate the word at all scales, improving the human experience and quality of life in a totally unobtrusive yet completely reliable manner. According to this vision, an huge variety of smart devices and products (e.g., wireless sensor nodes, mobile phones, cameras, sensors, home appliances and industrial machines) are interconnected to realize a network of distributed agents that continuously collect, process, share and transport information. The impact of such technologies in our everyday life is expected to be massive, as it will enable innovative applications that will profoundly change the world around us. Remotely monitoring the conditions of patients and elderly people inside hospitals and at home, preventing catastrophic failures of buildings and critical structures, realizing smart cities with sustainable management of traffic and automatic monitoring of pollution levels, early detecting earthquake and forest fires, monitoring water quality and detecting water leakages, preventing landslides and avalanches are just some examples of life-enhancing applications made possible by smart ubiquitous computing systems.
To turn this vision into a reality, however, new raising challenges have to be addressed, overcoming the limits that currently prevent the pervasive deployment of smart devices that are long lasting, trusted, and fully autonomous. In particular, the most critical factor currently limiting the realization of ubiquitous computing is energy provisioning. In fact, embedded devices are typically powered by short-lived batteries that severely affect their lifespan and reliability, often requiring expensive and invasive maintenance.
In this PhD thesis, we investigate the use of energy-harvesting techniques to overcome the energy bottleneck problem suffered by embedded devices, particularly focusing on Wireless Sensor Networks (WSNs), which are one of the key enablers of pervasive computing systems. Energy harvesting allows to use energy readily available from the environment (e.g., from solar light, wind, body movements, etc.) to significantly extend the typical lifetime of low-power devices, enabling ubiquitous computing systems that can last virtually forever. However, the design challenges posed both at the hardware and at the software levels by the design of energy-autonomous devices are many. This thesis addresses some of the most challenging problems of this emerging research area, such as devising mechanisms for energy prediction and management, improving the efficiency of the energy scavenging process, developing protocols for harvesting-aware resource allocation, and providing solutions that enable robust and reliable security support. %, including the design of mechanisms for energy prediction and management, improving the efficiency of the energy harvesting process, the develop of protocols for harvesting-aware resource allocation, and providing solutions that enable robust and reliable security support
Energy Efficient User Association and Power Allocation in Millimeter Wave Based Ultra Dense Networks with Energy Harvesting Base Stations
Millimeter wave (mmWave) communication technologies have recently emerged as
an attractive solution to meet the exponentially increasing demand on mobile
data traffic. Moreover, ultra dense networks (UDNs) combined with mmWave
technology are expected to increase both energy efficiency and spectral
efficiency. In this paper, user association and power allocation in mmWave
based UDNs is considered with attention to load balance constraints, energy
harvesting by base stations, user quality of service requirements, energy
efficiency, and cross-tier interference limits. The joint user association and
power optimization problem is modeled as a mixed-integer programming problem,
which is then transformed into a convex optimization problem by relaxing the
user association indicator and solved by Lagrangian dual decomposition. An
iterative gradient user association and power allocation algorithm is proposed
and shown to converge rapidly to an optimal point. The complexity of the
proposed algorithm is analyzed and the effectiveness of the proposed scheme
compared with existing methods is verified by simulations.Comment: to appear, IEEE Journal on Selected Areas in Communications, 201
Resource Allocation in Wireless Networks with RF Energy Harvesting and Transfer
Radio frequency (RF) energy harvesting and transfer techniques have recently
become alternative methods to power the next generation of wireless networks.
As this emerging technology enables proactive replenishment of wireless
devices, it is advantageous in supporting applications with quality-of-service
(QoS) requirement. This article focuses on the resource allocation issues in
wireless networks with RF energy harvesting capability, referred to as RF
energy harvesting networks (RF-EHNs). First, we present an overview of the
RF-EHNs, followed by a review of a variety of issues regarding resource
allocation. Then, we present a case study of designing in the receiver
operation policy, which is of paramount importance in the RF-EHNs. We focus on
QoS support and service differentiation, which have not been addressed by
previous literatures. Furthermore, we outline some open research directions.Comment: To appear in IEEE Networ
Cost-Aware Green Cellular Networks with Energy and Communication Cooperation
Energy cost of cellular networks is ever-increasing to match the surge of
wireless data traffic, and the saving of this cost is important to reduce the
operational expenditure (OPEX) of wireless operators in future. The recent
advancements of renewable energy integration and two-way energy flow in smart
grid provide potential new solutions to save the cost. However, they also
impose challenges, especially on how to use the stochastically and spatially
distributed renewable energy harvested at cellular base stations (BSs) to
reliably supply time- and space-varying wireless traffic over cellular
networks. To overcome these challenges, in this article we present three
approaches, namely, {\emph{energy cooperation, communication cooperation, and
joint energy and communication cooperation}}, in which different BSs
bidirectionally trade or share energy via the aggregator in smart grid, and/or
share wireless resources and shift loads with each other to reduce the total
energy cost.Comment: Submitted for possible publicatio
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