The impact on battery life has become a key design criteria for mobile device applications (apps). Poor user perceptions about an app's energy use can now quickly lead to negative social media reviews and the resulting adverse impact son the app's marketability. Traditionally, assessments of an app's energy use have been done by simply measuring the total current draw experienced by the device while the app is on. Such approaches have become insufficient within modern devices due to the prevalence of energy management features within their hardware and operating systems (OSes) and the increased complexity of modern apps. This leads to: (i) non-stationary time domain current signals, due to the devices' dynamics power management, and (ii) different operational "modes" within an app having distinct energy use profiles. Within this work, an approach based on matched filters is developed to allow per-mode energy profiles to be correctly identified and characterized under(i) and (ii). This approach is then applied to quantitatively assess the energy use profile for a dual-mode multi-platform commercial Android quality of experience (QoE) assessment app across a number of mobile devices and OS variants, where it is shown that such differences can lead to significant differences in the app-level energy profiles that are produced.

Telecommunication networks are under stress due to rapid traffic increase. Since most of this traffic increase is due to large file transfers, this paper proposes a cross-layer transport protocol specifically designed to efficiently handle large transactions. Traffic generated from large transactions is shaped into a periodic succession of fixed-size data frames. Each transaction is then scheduled for transmission using a two-way reservation protocol. Simulation results show that the proposed approach is capable of significantly improving goodput and end-to-end delay relative to TCP, improving efficiency of bandwidth utilization by over 40%.

In high-dynamic-range (HDR) imaging, a radiance map of a HDR scene can be constructed by capturing the scene multiple times with a digital camera at different exposure settings and then digitally combining the images. As we show in this paper, the signal-to-noise ratio (SNR) of the resulting HDR radiance map depends strongly on the number of images that are captured. We present an analytical model for computing SNR as a function of the set of exposure settings used in image capture and the physical noise parameters of the digital camera. We find that the average dynamic range of the HDR image varies as the inverse of the square-root of the inter-exposure spacing. We also find that using a denser exposure set can significantly reduce the inter-pixel variability and spatial variability of SNR in the final HDR radiance map.

This paper considers the problem of high-dynamic-range (HDR) image capture using low-dynamic-range (LDR) cameras. We present three different minimal-bracketing algorithms for computing minimum-sized exposure sets bracketing of HDR scenes. Each algorithm is applicable to a different HDR-imaging scenario depending on the amount of target-scene-irradiance information and real-time image processing available at the time of image acquisition. We prove the optimality of each algorithm with respect to its ability to obtain a theoretically minimum-size bracketing set of exposures. We also provide closed-form expressions for computing minimal-bracketing exposure sets for two common types of HDR-imaging systems, those with geometrically varying and arithmetically varying exposure settings. We experimentally demonstrate the advantages of the proposed methods by capturing and processing multiple HDR scenes using minimal-bracketing and 1-stop bracketing methods. The results show that minimal-bracketing can be used to produce high-quality HDR images, while requiring only one third as many LDR images be acquired compared to 1-stop bracketing. We also perform a detailed SNR analysis that quantifies the tradeoff between signal-to-noise ratio and image-bracketing-set size.

In this study, we examine control-plane throughput in optical burst switching (OBS) networks with electronic header processing. In a large-scale OBS network, headers arrive to the burst scheduler at a very high rate. This can potentially cause overloading of the core-node control-processor and lead to data loss if headers are not processed in a timely manner. In this work, we examine the effect of control-plane congestion on the overall loss performance of OBS networks. We present preliminary results that show how this congestion can become the primary source of loss and can ultimately limit the throughput and the scalability of the OBS system if not properly accounted for when designing the OBS network.

Broadband analog transport facilities using fiber or fiber/coax cable can play a significant role in the evolution of the network infrastructure for personal communications services (PCSs). Low-power PCS systems require a dense grid of radio ports to provide connectivity to the telephone network. Analog transport has a number of important advantages over digital transmission facilities, including the flexibility to support a variety of air interface formats, shared infrastructure cost with other services such as video distribution, and centralized call processing allowing the use of low cost and simple radio ports. A simulcast technique can be used in such systems to permit low rates of handoff (no handoff within each simulcast area) and sharing of hardware resources among multiple radio ports. This paper provides a detailed model and a simulation analysis of the cochannel interference and noise performance as well as the resource sharing benefit of a simulcast PCS system. Several potential PCS air interfaces are considered, including time division multiple access (TDMA) and code division multiple access (CDMA) techniques. Our investigation shows that the impact of multiple antenna noise in a simulcast system is offset by the improved signal-to-interference (SIR) ratio brought about by distributed antennas. Even with distributed antennas, multiple antenna noise places a limit on the maximum number of radio ports that can be assigned to each simulcast group. This limit, however, is shown to have little impact on the achievable resource sharing benefit of simulcasting (i.e., grouping beyond this limit has diminishing returns). A saving of 40% to 60%, in terms of the required central hardware resources, is typical for both TDMA and CDMA systems in suburban environments.

Applications for subcarrier multiplexing include a variety of analog and digital lightwave transmission systems. An overview of the requirements and capabilities of these systems is presented by describing specific examples of the most popular system types. These examples include multiuser interactive local area networks and multichannel digital, FM, and AM-VSB (vestigal sideband) video distribution systems. Limitations imposed on each by the linearity of directly or externally modulated sources, receiver noise, and relative-intensity noise are discussed.>