Performance and Power Characterization of Cellular Networks and Mobile Application Optimizations.

Smartphones with cellular data access have become increasingly popular with the wide variety of mobile applications. However, the performance and power footprint of these mobile applications are not well-understood, and due to the unawareness of the cellular specific characteristics, many of these applications are causing inefficient radio resource and device energy usage. In this dissertation, we aim at providing a suite of systematic methodology and tools to better understand the performance and power characteristics of cellular networks (3G and the new LTE 4G networks) and the mobile applications relying upon, and to optimize the mobile application design based on this understanding. We have built the MobiPerf tool to understand the characteristics of cellular networks. With this knowledge, we make detailed analysis on smartphone application performance via controlled experiments and via a large-scale data set from one major U.S. cellular carrier. To understand the power footprint of mobile applications, we have derived comprehensive power models for different network types and characterize radio energy usage of various smartphone applications via both controlled experiments and 7-month-long traces collected from 20 real users. Specifically, we characterize the radio and energy impact of the network traffic generated when the phone screen is off and propose the screen-aware traffic optimization. In addition to shedding light to the mobile application design throughout our characterization analysis, we further design and implement a real optimization system RadioProphet, which uses historical traffic features to make predictions and intelligently deallocate radio resource for improved radio and energy efficiency.PhDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/99905/1/hjx_1.pd

Context-aware Background Application Scheduling in Interactive Mobile Systems

Department of Computer Science and EngineeringEach individual's usage behavior on mobile devices depend on a variety of factors such as time, location, and previous actions. Hence, context-awareness provides great opportunities to make the networking and the computing capabilities of mobile systems to be more personalized and more efficient in managing their resources. To this end, we first reveal new findings from our own Android user experiment: (i) the launching probabilities of applications follow Zipf's law, and (ii) inter-running and running times of applications conform to log-normal distributions. We also find contextual dependencies between application usage patterns, for which we classify contexts autonomously with unsupervised learning methods. Using the knowledge acquired, we develop a context-aware application scheduling framework, CAS that adaptively unloads and preloads background applications for a joint optimization in which the energy saving is maximized and the user discomfort from the scheduling is minimized. Our trace-driven simulations with 96 user traces demonstrate that the context-aware design of CAS enables it to outperform existing process scheduling algorithms. Our implementation of CAS over Android platforms and its end-to-end evaluations verify that its human involved design indeed provides substantial user-experience gains in both energy and application launching latency.ope

MDSA, MULTI DECISION SCHEDULING ALGORITHM FOR UE ENERGY POWER SAVING ON MOBILE NETWORKS

Nowadays general different kind of recurrent network applications on mobile phones are like: news feed, podcast and e-mail which mostly run in the background and are a significant source of power consumption on battery limited mobile phones. Theory of scheduling such applications by prioritizing and evaluating step by step based on many conditions (or even parameters, timers) like radio network parameters, timeout values, coverage conditions or RSSI, switching between 2G and 3G on packet data, etc is our main focus on this paper. Cellular network providers typically try to control these timeout values, though some mobile devices use a technique called fast dormancy in order to reduce the time out duration which mostly results in huge power consumption for end user. The duration of this timeout, which ranges from a few seconds to ten seconds or more, is chosen to balance the cost of signaling for resource allocation to move a radio into active state (and the resulting latency and energy costs on the device) and the wasted resources due to maintaining a radio unnecessarily in active state. We also illustrate the significant energy savings that can be achieved via scheduling of recurrent mobile phone applications considering some network parameters, conditions and also user activity time (clock time) and phone battery condition as an add. These kinds of applications such as email syncing, facebook or photo uploads can defer communication, up to a point, without sacrificing service and user perception. Other applications such as on-demand streaming can prefetch content in anticipation of future need and this will not be considered for now on our study. The other very common service for mobile users is voice and by transmitting data when a call is active brings an extension on mobile phones battery life

Systems and Methods for Measuring and Improving End-User Application Performance on Mobile Devices

In today's rapidly growing smartphone society, the time users are spending on their smartphones is continuing to grow and mobile applications are becoming the primary medium for providing services and content to users. With such fast paced growth in smart-phone usage, cellular carriers and internet service providers continuously upgrade their infrastructure to the latest technologies and expand their capacities to improve the performance and reliability of their network and to satisfy exploding user demand for mobile data. On the other side of the spectrum, content providers and e-commerce companies adopt the latest protocols and techniques to provide smooth and feature-rich user experiences on their applications. To ensure a good quality of experience, monitoring how applications perform on users' devices is necessary. Often, network and content providers lack such visibility into the end-user application performance. In this dissertation, we demonstrate that having visibility into the end-user perceived performance, through system design for efficient and coordinated active and passive measurements of end-user application and network performance, is crucial for detecting, diagnosing, and addressing performance problems on mobile devices. My dissertation consists of three projects to support this statement. First, to provide such continuous monitoring on smartphones with constrained resources that operate in such a highly dynamic mobile environment, we devise efficient, adaptive, and coordinated systems, as a platform, for active and passive measurements of end-user performance. Second, using this platform and other passive data collection techniques, we conduct an in-depth user trial of mobile multipath to understand how Multipath TCP (MPTCP) performs in practice. Our measurement study reveals several limitations of MPTCP. Based on the insights gained from our measurement study, we propose two different schemes to address the identified limitations of MPTCP. Last, we show how to provide visibility into the end- user application performance for internet providers and in particular home WiFi routers by passively monitoring users' traffic and utilizing per-app models mapping various network quality of service (QoS) metrics to the application performance.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146014/1/ashnik_1.pd

Energy optimization through traffic aggregation in wireless networks

Abstract—Cellular networks can provide pervasive data ac-cess for smartphones, but also consume lots of energy, because the cellular interface has to stay in high power state for a long time (called long tail problem) after a data transmission. In this paper, we propose to reduce the tail energy by aggregating the data traffic of multiple nodes using their P2P interfaces. This traffic aggregation problem is formalized as finding the best task schedule to minimize energy. We first propose an A search algorithm, which can reduce the search space for finding the optimal schedule offline, and then introduce an online traffic aggregation algorithm. We have implemented the online traffic aggregation algorithm on Android smartphones, and have built a small testbed. Trace-driven simulations and Experimental results show that our traffic aggregation algorithm can significantly reduce the energy and delay. I

Traffic-aware techniques to reduce 3G/LTE wireless energy consumption

The 3G/LTE wireless interface is a significant contributor to battery drain on mobile devices. A large portion of the energy is consumed by unnecessarily keeping the mobile device's radio in its "Active" mode even when there is no traffic. This paper describes the design of methods to reduce this portion of energy consumption by learning the traffic patterns and predicting when a burst of traffic will start or end. We develop a technique to determine when to change the radio's state from Active to Idle, and another to change the radio's state from Idle to Active. In evaluating the methods on real usage data from 9 users over 28 total days on four different carriers, we find that the energy savings range between 51% and 66% across the carriers for 3G, and is 67% on the Verizon LTE network. When allowing for delays of a few seconds (acceptable for background applications), the energy savings increase to between 62% and 75% for 3G, and 71% for LTE. The increased delays reduce the number of state switches to be the same as in current networks with existing inactivity timers.National Science Foundation (U.S.) (Grant CNS-0931550

Arbitrating Traffic Contention for Power Saving with Multiple PSM Clients

Data transmission over WiFi quickly drains the batteries of mobile devices. Although the IEEE 802.11 standards provide power save mode (PSM) to help mobile devices conserve energy, PSM fails to bring expected benefits in many real scenarios. In particular, when multiple PSM mobile devices associate to a single access point (AP), PSM does not work well under transmission contention. Optimizing power saving of multiple PSM clients is a challenging task, because each PSM client expects to complete data transmission early so that it can turn to low power mode. In this paper, we define an energy conserving model to describe the general PSM traffic contention problem. We prove that the optimization of energy saving for multiple PSM clients under constraint is an NPcomplete problem. Following this direction, we propose a solution called harmonious power saving mechanism (HPSM) to address one specific case, in which multiple PSM clients associate to a single AP. In HPSM, we first use a basic sociological concept to define the richness of a PSM client based on the link resource it consumes. Then, we separate these poor PSM clients from rich PSM clients in terms of link resource consumption and favor the former to save power when they face PSM transmission contention. We implement prototypes of HPSM based on the open source projects Mad-wifi and NS-2. Our evaluations show that HPSM can help the poor PSM clients effectively save power while only slightly degrading the rich PSM clients\u27 performance in comparison with the existing PSM solutions

Planning and dynamic spectrum management in heterogeneous mobile networks with QoE optimization

The radio and network planning and optimisation are continuous processes that do not end after the network has been launched. To achieve the best trade-offs, especially between quality and costs, operators make use of several coverage and capacity enhancement methods. The research from this thesis proposes methods such as the implementation of cell zooming and Relay Stations (RSs) with dynamic sleep modes and Carrier Aggregation (CA) for coverage and capacity enhancements. Initially, a survey is presented on ubiquitous mesh networks implementation scenarios and an updated characterization of requirements for services and applications is proposed. The performance targets for the key parameters, delay, delay variation, information loss and throughput have been addressed for all types of services. Furthermore, with the increased competition, mobile operator’s success does not only depend on how good the offered Quality of Service (QoS) is, but also if it meets the end user’s expectations, i.e., Quality of Experience (QoE). In this context, a model for the mapping between QoS parameters and QoE has been proposed for multimedia traffic. The planning and optimization of fixed Worldwide Interoperability for Microwave Access (WiMAX) networks with RSs in conjunction with cell zooming has been addressed. The challenging case of a propagation measurement-based scenario in the hilly region of Covilhã has been considered. A cost/revenue function has been developed by taking into account the cost of building and maintaining the infrastructure with the use of RSs. This part of the work also investigates the energy efficiency and economic implications of the use of power saving modes for RSs in conjunction with cell zooming. Assuming that the RSs can be switched-off or zoomed out to zero in periods when the traffic exchange is low, such as nights and weekends, it has been shown that energy consumption may be reduced whereas cellular coverage and capacity, as well as economic performance may be improved. An integrated Common Radio Resource Management (iCRRM) entity is proposed that implements inter-band CA by performing scheduling between two Long Term Evolution – Advanced (LTE-A) Component Carriers (CCs). Considering the bandwidths available in Portugal, the 800 MHz and 2.6 GHz CCs have been considered whilst mobile video traffic is addressed. Through extensive simulations it has been found that the proposed multi-band schedulers overcome the capacity of LTE systems without CA. Result shown a clear improvement of the QoS, QoE and economic trade-off with CA