Jukka K. Nurminen

How low energy is bluetooth low energy? Comparative measurements with ZigBee/802.15.4

Ultra low power communication mechanisms are essential for future Internet of Things deployments. Bluetooth Low Energy (BLE) is one promising candidate for such deployments. We study the energy consumption of BLE by measuring real devices with a power monitor and derive models of the basic energy consumption behavior observed from the measurement results. We investigate also the overhead of Ipv6-based communication over BLE, which is relevant for future IoT scenarios. We contrast our results by performing similar measurements with ZigBee/802.15.4 devices. Our results show that when compared to ZigBee, BLE is indeed very energy efficient in terms of number of bytes transferred per Joule spent. In addition, IPv6 communication energy overhead remains reasonable. We also point out a few specific limitations with current stack implementations and explain that removing those limitations could improve energy utility significantly.

Energy Efficient Multimedia Streaming to Mobile Devices — A Survey

Energy conservation in battery powered mobile devices that perform wireless multimedia streaming has been a significant research problem since last decade. This is because these mobile devices consume a lot of power while receiving, decoding and ultimately, presenting the multimedia content. What makes things worse is the fact that battery technologies have not evolved enough to keep up with the rapid advancement of mobile devices. This survey examines solutions that have been proposed during the last few years, to improve the energy efficiency of wireless multimedia streaming in mobile hand-held devices. We categorize the research work according to different layers of the Internet protocol stack they utilize. Then, we again regroup these studies based on different traffic scheduling and multimedia content adaptation mechanisms. The traffic scheduling category contains those solutions that optimize the wireless receiving energy without changing the actual multimedia content. The second category on the other hand, specifically modifies the content, in order to reduce the energy consumed by the wireless receiver and to decode and view the content. We compare them and provide evidence of the fact that some of these tactics already exist in modern smaprtphones and provide energy savings with real measurements. In addition, we discuss some relevant literature on the complementary problem of energy-aware multimedia delivery from mobile devices and contrast with our target approaches for multimedia transmission to mobile devices.

Energy- and Cost-Efficiency Analysis of ARM-Based Clusters

General-purpose computing domain has experienced strategy transfer from scale-up to scale-out in the past decade. In this paper, we take a step further to analyze ARM-processor based cluster against Intel X86 workstation, from both energy-efficiency and cost-efficiency perspectives. Three applications are selected and evaluated to represent diversified applications, including Web server throughput, in-memory database, and video transcoding. Through detailed measurements, we make the observations that the energy-efficiency ratio of the ARM cluster against the Intel workstation varies from 2.6-9.5 in in-memory database, to approximately 1.3 in Web server application, and 1.21 in video transcoding. We also find out that for the Intel processor that adopts dynamic voltage and frequency scaling (DVFS) techniques, the power consumption is not linear with the CPU utilization level. The maximum energy saving achievable from DVFS is 20%. Finally, by utilizing a monthly cost model of data centers, we conclude that ARM cluster based data centers are feasible, and are advantageous in computationally lightweight applications, e.g. in-memory database and network-bounded Web applications. The cost advantage of ARM cluster diminishes progressively for computation-intensive applications, i.e. dynamic Web server application and video transcoding, because the number of ARM processors needed to provide comparable performance increases.

Using crowd-sourced viewing statistics to save energy in wireless video streaming

Video streaming on smartphones is one of the most popular but also most energy hungry services today. Using mobile video services results in two contradictory sources of energy waste for smartphones: i) energy waste because of excessively aggressive prefetching of content that the user will not watch because of abandoning the session, and ii) excessive amount of tail energy, which is energy wasted by keeping the wireless interface powered on after receiving a chunk of content; this is caused by prefetching chunks that are too small. To remedy this, we propose a novel download scheduling algorithm based on crowd-sourced video viewing statistics. Our algorithm judiciously evaluates the probability of a user interrupting a video viewing in order to perform the right amount of prefetching. In this way, the algorithm balances the amount of the two above-mentioned kinds of energy waste. By simulations, we show that our scheduler cuts the energy waste to half compared to existing download strategies. We have also developed an Android prototype that implements the download scheduler together with a novel downloader that speeds up the download by exploiting the Fast Start technique. The prototype exhibits the desired properties of the scheduler, and its faster downloading mechanism yields further energy savings of up to 80% compared to the default Android YouTube app.

Streaming over 3G and LTE: how to save smartphone energy in radio access network-friendly way

Energy consumption of mobile devices is a great concern and streaming applications are among the most power hungry ones. We evaluate the energy saving potential of shaping streaming traffic into bursts before transmitting it over 3G and LTE networks to smartphones. The idea is that in between the bursts, the phone has sufficient time to switch from the high-power active state to low-power states. We investigate the impact of the network parameters, namely inactivity timers and discontinuous reception, on the achievable energy savings and on the radio access network signaling load. The results confirm that traffic shaping is an effective way to save energy, even up to 60% of energy saved when streaming music over LTE. However, we note large differences in the signaling load. LTE with discontinuous reception and long inactivity timer value achieves the energy savings with no extra signaling load, whereas non-standard Fast Dormancy in 3G can multiply the signaling traffic by a factor of ten.

Energy Aspects of Peer Cooperation Measurements with a Mobile DHT System

Distributed Hash Tables (DHTs) are widely studied from the fixed computer point of view, but very little research has been done on the performance of mobile clients. We have implemented a DHT client for mobile phones and carried out energy measurements to analyze the power profile of the application. By connecting to a widely deployed DHT, we were able to observe how mobile clients perform in a million user environment. We show that using a mobile phone as a full-peer is feasible only for a couple of hours due to the high power consumption. We also define the client-only mode that allows mobile nodes to use the services of the DHT with minimal energy consumption.

CloudTorrent - Energy-Efficient BitTorrent Content Sharing for Mobile Devices via Cloud Services

BitTorrent-based file-sharing is already available for mobile phones; however, its energy profile makes it difficult to use it for transferring large amount of data. This paper analyzes an alternative cloud-based solution that uses a remote server to download content via BitTorrent and transfer it to the mobile device in a transparent and energy efficient way. The system is evaluated via measurements carried out on smartphones.

Parallel Connections and their Effect on the Battery Consumption of a Mobile Phone

In this paper, we analyze the end-to-end communication activities of a modern mobile phone, Nokia N95, to understand how much energy different communication alternatives consume. In particular, we investigate the interactions when multiple connections are used in parallel. Parallel connections save energy but the gains vary depending on the technology. TCP downloads during 3G voice calls result into 75%-90% energy savings, TCP downloads during VoIP calls result into 30%-40% savings, and TCP downloads when other TCP streams are active at the same interface result into 0%- 20% savings. The results indicate that there is a significant potential to save energy if applications are engineered to take advantage of this phenomenon.

On the energy efficiency of proxy-based traffic shaping for mobile audio streaming

We study how much energy can be saved by reshaping audio streaming traffic before receiving at the mobile devices. The rationale is the following: Mobile network interfaces (WLAN and 3G) are in active mode when they transmit or receive data, otherwise they are in idle/sleep mode. To save energy, minimum possible time should be spent in active mode and maximum in idle/sleep mode. It is well known that by reshaping the usually constant bit rate multimedia traffic into bursts, it is possible to spend more time in idle/sleep mode leading to impressive energy savings. We propose a proxy-based solution that shapes an audio stream into bursts before relaying the traffic to the mobile device. The novelty of our work is an evaluation of the energy savings using such a proxy with different configurations for both WLAN access with standard 802.11 Power Saving Mode and 3G access. We conclude that for WLAN access, proxy causes power savings of 30%-65% depending on the audio stream rate, location of the proxy and amount of cross traffic. In the case of 3G, the effectiveness of our proxy seems to vary depending on the phone model and operator. In some cases, the energy savings are encouraging, while in other cases the proxy turns out to be ineffective due to abnormal delay variation and TCP flow control behavior.

Energy efficiency of mobile handsets: Measuring user attitudes and behavior

The purpose of this research is to understand the behavior and expectations of mobile handset users towards energy consumption. We analyze mobile handset monitoring traces from subsequent years with N=253 and 105, and questionnaire studies with N=155 and 150. The data allows us to study both the actual behavior of the users and their explicit attitudes, expectations, and experiences. Additional difference to prior work is the use of longitudinal data from multiple years and a user sample that is much larger than in earlier studies. We present hypotheses drawn both from literature and from our own experience, and use the datasets to support or refute them. Our results indicate that mobile device users need more detailed and clearer information of the battery status and energy consumption. Moreover, users want to understand how different applications and services affect the energy consumption and to learn what they can do to control it.