MEERA: Cross-Layer Methodology for Energy Efficient Resource Allocation in Wireless Networks

In many portable devices, wireless network interfaces consume upwards of 30% of scarce system energy. Reducing the transceiver’s power consumption to extend the system lifetime has therefore become a design goal. Our work is targated at this goal and is based on the following two observations. First, conventional energy management approaches have focused independently on minimizing the fixed energy cost (by shutdown) and on scalable energy costs (by leveraging, for example, the modulation, code-rate and transmission power). These two energy management approaches present a tradeoff. For example, lower modulation rates and transmission power minimize the variable energy component, but this shortens the sleep duration thereby increasing fixed energy consumption. Second, in order to meet the Quality of Service (QoS) timeliness requirements for multiple users, we need to determine to what extent each system in the network may sleep and scale. Therefore, we propose a two-phase methodology that resolves the sleep-scaling tradeoff across the physical, communications and link layers at design time and schedules nodes at runtime with near optimal energy-efficient configurations in the solution space. As a result, we are able to achieve very low run-time overheads. Our methodology is applied to a case study on delivering a guaranteed QoS for multiple users with MPEG-4 video over a slow-fading channel. By exploiting runtime controllable parameters of actual RF components and a modified 802.11 Medium Access Controller, system lifetime is increased by a factor of 3-to-10 in comparison with conventional techniques

User-centric Networks Selection with Adaptive Data Compression for Smart Health

The increasing demand for intelligent and sustainable healthcare services has prompted the development of smart health systems. Rapid advances in wireless access technologies and in-network data reduction techniques can significantly assist in implementing such smart systems through providing seamless integration of heterogeneous wireless networks, medical devices, and ubiquitous access to data. Utilization of the spectrum across diverse radio technologies is expected to significantly enhance network capacity and quality of service (QoS) for emerging applications such as remote monitoring over mobile-health (m-health) systems. However, this imposes an essential need to develop innovative networks selection mechanisms that account for energy efficiency while meeting application quality requirements. In this context, this paper proposes an efficient networks selection mechanism with adaptive compression for improving medical data delivery over heterogeneous m-health systems. We consider different performance aspects, as well as networks characteristics and application requirements, so as to obtain an efficient solution that grasps the conflicting nature of the various users’ objectives and addresses their inherent tradeoffs. The proposed methodology advocates a user-centric approach towards leveraging heterogeneous wireless networks to enhance the performance of m-health systems. Simulation results show that our solution significantly outperforms state-of-the-art techniques

Novel Processing and Transmission Techniques Leveraging Edge Computing for Smart Health Systems

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Multi-View Video Packet Scheduling

In multiview applications, multiple cameras acquire the same scene from different viewpoints and generally produce correlated video streams. This results in large amounts of highly redundant data. In order to save resources, it is critical to handle properly this correlation during encoding and transmission of the multiview data. In this work, we propose a correlation-aware packet scheduling algorithm for multi-camera networks, where information from all cameras are transmitted over a bottleneck channel to clients that reconstruct the multiview images. The scheduling algorithm relies on a new rate-distortion model that captures the importance of each view in the scene reconstruction. We propose a problem formulation for the optimization of the packet scheduling policies, which adapt to variations in the scene content. Then, we design a low complexity scheduling algorithm based on a trellis search that selects the subset of candidate packets to be transmitted towards effective multiview reconstruction at clients. Extensive simulation results confirm the gain of our scheduling algorithm when inter-source correlation information is used in the scheduler, compared to scheduling policies with no information about the correlation or non-adaptive scheduling policies. We finally show that increasing the optimization horizon in the packet scheduling algorithm improves the transmission performance, especially in scenarios where the level of correlation rapidly varies with time

Energy Consumption Of Visual Sensor Networks: Impact Of Spatio-Temporal Coverage

Wireless visual sensor networks (VSNs) are expected to play a major role in future IEEE 802.15.4 personal area networks (PAN) under recently-established collision-free medium access control (MAC) protocols, such as the IEEE 802.15.4e-2012 MAC. In such environments, the VSN energy consumption is affected by the number of camera sensors deployed (spatial coverage), as well as the number of captured video frames out of which each node processes and transmits data (temporal coverage). In this paper, we explore this aspect for uniformly-formed VSNs, i.e., networks comprising identical wireless visual sensor nodes connected to a collection node via a balanced cluster-tree topology, with each node producing independent identically-distributed bitstream sizes after processing the video frames captured within each network activation interval. We derive analytic results for the energy-optimal spatio-temporal coverage parameters of such VSNs under a-priori known bounds for the number of frames to process per sensor and the number of nodes to deploy within each tier of the VSN. Our results are parametric to the probability density function characterizing the bitstream size produced by each node and the energy consumption rates of the system of interest. Experimental results reveal that our analytic results are always within 7% of the energy consumption measurements for a wide range of settings. In addition, results obtained via a multimedia subsystem show that the optimal spatio-temporal settings derived by the proposed framework allow for substantial reduction of energy consumption in comparison to ad-hoc settings. As such, our analytic modeling is useful for early-stage studies of possible VSN deployments under collision-free MAC protocols prior to costly and time-consuming experiments in the field.Comment: to appear in IEEE Transactions on Circuits and Systems for Video Technology, 201

Optimal Fixed and Scalable Energy Management for Wireless Networks

In many devices, wireless network interfaces consume upwards of 30% of scarce portable system energy. Extending the system lifetime by minimizing communication power consumption has therefore become a priority. Conventional energy management techniques focus independently on minimizing the fixed energy consumption of the transceiver circuit or on scalable transmission control. Fixed energy consumption is reduced by maximizing the transceiver shutdown interval. In contrast, variable transmission rate, coding and power can be leveraged to minimize energy costs. These two energy management approaches present a tradeoff in minimizing the overall system energy. For example, variable energy costs are minimized by transmitting at a lower modulation rate and transmission power, but this also shortens the sleep duration thereby increasing fixed energy consumption. We present a methodology for energy-efficient resource allocation across the physical layer, communications layer and link layer. Our methodology is aimed at providing QoS for multiple users with bursty MPEG-4 video over a time-varying channel. We evaluate our scheme by exploiting control knobs of actual RF components over a modified IEEE 802.11 MAC. Our results indicate that the system lifetime is increased by a factor of 2 to 5 compared to the gains of conventional techniques

Design and analysis of a beacon-less routing protocol for large volume content dissemination in vehicular ad hoc networks

Largevolumecontentdisseminationispursuedbythegrowingnumberofhighquality applications for Vehicular Ad hoc NETworks(VANETs), e.g., the live road surveillance service and the video-based overtaking assistant service. For the highly dynamical vehicular network topology, beacon-less routing protocols have been proven to be efficient in achieving a balance between the system performance and the control overhead. However, to the authors’ best knowledge, the routing design for large volume content has not been well considered in the previous work, which will introduce new challenges, e.g., the enhanced connectivity requirement for a radio link. In this paper, a link Lifetime-aware Beacon-less Routing Protocol (LBRP) is designed for large volume content delivery in VANETs. Each vehicle makes the forwarding decision based on the message header information and its current state, including the speed and position information. A semi-Markov process analytical model is proposed to evaluate the expected delay in constructing one routing path for LBRP. Simulations show that the proposed LBRP scheme outperforms the traditional dissemination protocols in providing a low end-to-end delay. The analytical model is shown to exhibit a good match on the delay estimation with Monte Carlo simulations, as well