In this paper, we present a measurement study of the energy consumption characteristics of three widespread mobile networking technologies: 3G, GSM, and WiFi. We find that 3G and GSM incur a high tail energy overhead because of lingering in high power states after completing a transfer. Based on these measurements, we develop a model for the energy consumed by network activity for each technology.Using this model, we develop TailEnder, a protocol that reduces energy consumption of common mobile applications. For applications that can tolerate a small delay such as e-mail, TailEnder schedules transfers so as to minimize the cumulative energy consumed meeting user-specified deadlines. We show that the TailEnder scheduling algorithm is within a factor 2x of the optimal and show that any online algorithm can at best be within a factor 1.62x of the optimal. For applications like web search that can benefit from prefetching, TailEnder aggressively prefetches several times more data and improves user-specified response times while consuming less energy. We evaluate the benefits of TailEnder for three different case study applications - email, news feeds, and web search - based on real user logs and show significant reduction in energy consumption in each case. Experiments conducted on the mobile phone show that TailEnder can download 60% more news feed updates and download search results for more than 50% of web queries, compared to using the default policy.

https://ciir-publications.cs.umass.edu/getpdf.php?id=904

Energy consumption in mobile phones: a measurement study and implications for network applications

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Art of electronics

https://faculty.ist.psu.edu/vhonavar/Papers/AJPM.pdf

Mobile health technology evaluation: The mHealth evidence workshop

Internet of Things (IoT), also referred to as the Internet of Objects, is envisioned as a transformative approach for providing numerous services. Compact smart devices constitute an essential part of IoT. They range widely in use, size, energy capacity, and computation power. However, the integration of these smart things into the standard Internet introduces several security challenges because the majority of Internet technologies and communication protocols were not designed to support IoT. Moreover, commercialization of IoT has led to public security concerns, including personal privacy issues, threat of cyber attacks, and organized crime. In order to provide a guideline for those who want to investigate IoT security and contribute to its improvement, this survey attempts to provide a comprehensive list of vulnerabilities and countermeasures against them on the edge-side layer of IoT, which consists of three levels: (i) edge nodes, (ii) communication, and (iii) edge computing. To achieve this goal, we first briefly describe three widely-known IoT reference models and define security in the context of IoT. Second, we discuss the possible applications of IoT and potential motivations of the attackers who target this new paradigm. Third, we discuss different attacks and threats. Fourth, we describe possible countermeasures against these attacks. Finally, we introduce two emerging security challenges not yet explained in detail in previous literature.

A Comprehensive Study of Security of Internet-of-Things

Urban sensing, participatory sensing, and user activity recognition can provide rich contextual information for mobile applications such as social networking and location-based services. However, continuously capturing this contextual information on mobile devices consumes huge amount of energy. In this paper, we present a novel design framework for an Energy Efficient Mobile Sensing System (EEMSS). EEMSS uses hierarchical sensor management strategy to recognize user states as well as to detect state transitions. By powering only a minimum set of sensors and using appropriate sensor duty cycles EEMSS significantly improves device battery life. We present the design, implementation, and evaluation of EEMSS that automatically recognizes a set of users' daily activities in real time using sensors on an off-the-shelf high-end smart phone. Evaluation of EEMSS with 10 users over one week shows that our approach increases the device battery life by more than 75% while maintaining both high accuracy and low latency in identifying transitions between end-user activities.

/pdf/a-framework-of-energy-efficient-mobile-sensing-for-automatic-2fstnx2xo8.pdf

A framework of energy efficient mobile sensing for automatic user state recognition

Transiently powered computing devices such as RFID tags, kinetic energy harvesters, and smart cards typically rely on programs that complete a task under tight time constraints before energy starvation leads to complete loss of volatile memory. Mementos is a software system that transforms general-purpose programs into interruptible computations that are protected from frequent power losses by automatic, energy-aware state checkpointing. Mementos comprises a collection of optimization passes for the LLVM compiler infrastructure and a linkable library that exercises hardware support for energy measurement while managing state checkpoints stored in nonvolatile memory. We evaluate Mementos against diverse test cases in a trace-driven simulator of transiently powered RFID-scale devices. Although Mementos's energy checks increase run time when energy is plentiful, they allow Mementos to safely suspend execution when energy dwindles, effectively spreading computation across zero or more power failures. This paper's contributions are: a study of the runtime environment for programs on RFID-scale devices; an energy-aware state checkpointing system for these devices that is implemented for the MSP430 family of microcontrollers; and a trace-driven simulator of transiently powered RFID-scale devices.

/pdf/mementos-system-support-for-long-running-computation-on-rfid-44fepid0kj.pdf

Mementos: system support for long-running computation on RFID-scale devices

Embedded systems can operate perpetually without being connected to a power source by harvesting environmental energy from motion, the sun, wind, or heat differentials. However, programming these perpetual systems is challenging. In response to changing energy levels, programmers can adjust the execution frequency of energy-intensive tasks, or provide higher service levels when energy is plentiful and lower service levels when energy is scarce. However, it is often difficult for programmers to predict the energy consumption resulting from these adjustments. Worse, explicit energy management can tie a program to a particular hardware platform, limiting portability.This paper introduces Eon, a programming language and runtime system designed to support the development of perpetual systems. To our knowledge, Eon is the first energy-aware programming language. Eon is a declarative coordination language that lets programmers compose programs from components written in C or nesC. Paths through the program ("flows") may be annotated with different energy states. Eon's automatic energy management then dynamically adapts these states to current and predicted energy levels. It chooses flows to execute and adjusts their rates of execution, maximizing the quality of service under available energy constraints.We demonstrate the utility and portability of Eon by deploying two perpetual applications on widely different hardware platforms: a GPS-based location tracking sensor deployed on a threatened species of turtle and on automobiles, and a solar-powered camera sensor for remote, ad-hoc deployments. We also evaluate the simplicity and effectiveness of Eon with a user study, in which novice Eon programmers produced more efficient efficient energy-adaptive systems in substantially less time than experienced C programmers.

/pdf/eon-a-language-and-runtime-system-for-perpetual-systems-2vw5ktw95t.pdf

Eon: a language and runtime system for perpetual systems

Maintaining optimal consistency in a distributed system requires that nodes be always-on to synchronize information Unfortunately, mobile devices such as laptops do not have adequate battery capacity for constant processing and communication Even by powering off unnecessary components, such as the screen and disk, current laptops only have a lifetime of a few hours Although PDAs and sensors are similarly limited in lifetime, a PDA's power requirement is an order-of-magnitude smaller than a laptop's, and a sensor's is an order-of-magnitude smaller than a PDA's By combining these diverse platforms into a single integrated laptop, we can reduce the power cost of always-on operation This paper presents the design, implementation, and evaluation of Turducken, a Hierarchical Power Management architecture for mobile systems We focus on a particular instantiation of HPM, which provides high levels of consistency in a laptop by integrating two additional low power processors We demonstrate that a Turducken system can provide battery lifetimes of up to ten times that of a standard laptop for always-on operation and three times for a system that periodically sleeps

/pdf/turducken-hierarchical-power-management-for-mobile-devices-4qau4f44i5.pdf

Turducken: hierarchical power management for mobile devices

Tiny intermittently powered computers can monitor objects in hard to reach places maintenance free for decades by leaving batteries behind and surviving off energy harvested from the environment--- avoiding the cost of replacing and disposing of billions or trillions of dead batteries. However, creating programs for these sensors is difficult. Energy harvesting is inconsistent, energy storage is scarce, and batteryless sensors can lose power at any point in time--- causing volatile memory, execution progress, and time to reset. In response to these disruptions, developers must write unwieldy programs attempting to protect against failures, instead of focusing on sensing goals, defining tasks, and generating useful data in a timely manner. To address these shortcomings, we have designed Mayfly, a language and runtime for timely execution of sensing tasks on tiny, intermittently-powered, energy harvesting sensing devices. Mayfly is a coordination language and runtime built on top of Embedded-C that combines intermittent execution fragments to form coherent sensing schedules---maintaining forward progress, data consistency, data freshness, and data utility across multiple power failures. Mayfly makes the passing of time explicit, binding data to the time it was gathered, and keeping track of data and time through power failures. We evaluated Mayfly against state-of-the art systems, conducted a user study, and implemented multiple real world applications across application domains in inventory tracking, and wearables.

https://dl.acm.org/doi/pdf/10.1145/3131672.3131673

Timely Execution on Intermittently Powered Batteryless Sensors

Sensing has been obsessed with delivering on the "smart dust" vision outlined decades ago, where trillions of tiny invisible computers support daily life, infrastructure, and humanity in general. Batteries are the single greatest threat to this vision of a sustainable Internet of Things. They are expensive, bulky, hazardous, and wear out after a few years (even rechargeables). Replacing and disposing of billions or trillions of dead batteries per year would be expensive and irresponsible. By leaving the batteries behind and surviving off energy harvested from the environment, tiny intermittently powered computers can monitor objects in hard to reach places maintenance free for decades. The intermittent execution, constrained compute and energy resources, and unreliability of these devices creates new challenges for the sensing and embedded systems community. However, the rewards and potential impact across many fields are worth it, enabling currently impractical applications in health services and patient care, commercial and consumer applications, wildlife conservation, industrial and infrastructure management, even space exploration. This paper highlights major research questions and establishes new directions for the community to embrace and investigate.

https://dl.acm.org/doi/pdf/10.1145/3131672.3131699

Jacob Sorber

Papers

Mementos: system support for long-running computation on RFID-scale devices

Eon: a language and runtime system for perpetual systems

Turducken: hierarchical power management for mobile devices

Timely Execution on Intermittently Powered Batteryless Sensors

The Future of Sensing is Batteryless, Intermittent, and Awesome