京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第18591号 / 工博第3952号 / 新制||工||1607(附属図書館) / 31491 / 京都大学大学院工学研究科材料工学専攻 / (主査)教授 河合 潤, 教授 酒井 明, 教授 伊藤 秋男 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Low-power wireless networks consist of spatially distributed, resource-constrained devices – also referred to as nodes – that are typically equipped with integrated or external sensors and actuators. Nodes communicate with each other using wireless transceivers, and thus, relay data – e. g., collected sensor values or commands for actuators – cooperatively through the network. This way, low-power wireless networks can support a plethora of different applications, including, e. g., monitoring the air quality in urban areas or controlling the heating, ventilation and cooling of large buildings. The use of wireless communication in such monitoring and actuating applications allows for a higher flexibility and ease of deployment – and thus, overall lower costs – compared to wired solutions. However, wireless communication is notoriously error-prone. Message losses happen often and unpredictably, making it challenging to support applications requiring both high reliability and low latency. Highly reliable, low-latency communication – along with high energy-efficiency – are, however, key requirements to support several important application scenarios and most notably the open-/closed-loop control functions found in e. g., industry and factory automation applications. Communication protocols that rely on synchronous transmissions have been shown to be able to overcome this limitation. These protocols depart from traditional single-link transmissions and do not attempt to avoid concurrent transmissions from different nodes to prevent collisions. On the contrary, they make nodes send the same message at the same time over several paths. Phenomena like constructive interference and capture then ensure that messages are received correctly with high probability. While many approaches relying on synchronous transmissions have been presented in the literature, two important aspects received only little consideration: (i) reliable operation in harsh environments and (ii) support for event-based data traffic. This thesis addresses these two open challenges and proposes novel communication protocols to overcome them.

Post-Silicon validation of a designed ASIC is an essential step in the product development process. During the validation process, all specifications of the ASICs have to be controlled in a lab environment. Serializer/Deserialiser(SerDes) blocks in an ASIC are used to perform high-speed serial data communication between distinct integrated circuits. The goal of the thesis is to validate the power consumption of SerDes IP blocks provided by different vendors in an ASIC. To validate power consumption, current and voltage values are read from power supply lines. Then these values are digitized and stored on a Raspberry Pi. To perform these operations, the initial firmware provided by vendors is improved to control SerDes operations, and software is developed to control the Raspberry Pi. Power measured operation is performed for every possible data rate for each SerDes modules. Power measurement is also performed for different temperature range in industry standards with the highest possible data rate for each SerDes IP block. As a final step, measured power consumption values are compared to vendors’ data. / Validering av en designad ASIC efter kisel är ett viktigt steg i produktutvecklingsprocessen. Under valideringsprocessen måste alla specifikationer för ASIC kontrolleras i en laboratoriemiljö. Serializer / Deserialiser (SerDes) -block i en ASIC används för att utföra höghastighets seriell datakommunikation mellan distinkta integrerade kretsar. Målet med avhandlingen är att validera strömförbrukningen för SerDes IP-block som tillhandahålls av olika leverantörer i en ASIC. För att validera strömförbrukningen läses strömoch spänningsvärden från strömförsörjningsledningarna. Sedan digitaliseras dessa värden och lagras på en Raspberry Pi. För att utföra dessa operationer förbättras den inledande firmware som tillhandahålls av leverantörer för att styra SerDesoperationer och programvara utvecklas för att styra Raspberry Pi. Effektmätt operation utförs för varje möjlig datahastighet för varje SerDes-modul. Mätoperationer utförs också för olika temperaturintervall i branschstandarder med högsta möjliga datahastighet för varje SerDes IP-block. Som ett sista steg jämförs uppmätta energiförbrukningsvärden med leverantörens data.

Energy consumption and speed of execution have long been recognized as conflicting requirements for processor design. In this work, we have developed a low-cost dynamic architecture adaptation scheme to save leakage power in caches. This design uses voltage scaling to implement drowsy caches. The importance of a dynamic scheme for managing drowsy caches, arises from the fact that not only does cache behavior change from one application to the next, but also during different phases of execution within the same application. We discuss various implementations of our scheme that provide a tradeoff between granularity of control and design complexity. We investigate a combination of policies where the cache lines can be turned off completely if they are not accessed, when in the drowsy mode. We also develop a simple dynamic cache-way shutdown mechanism, and propose a combination of our dynamic scheme for drowsy lines, with the cache-way shutdown scheme. Switching off cache ways has the potential of greater energy benefits but provides a very coarse grained control. Combining this with the fine grained scheme of drowsy cache lines allows us to exploit more possibilities for energy benefits without incurring a significant degradation in performance. Keywords: Drowsy Cache, Architecture Adaptation, Low Power, Leakage Reduction, Dynamic Scheme

With the introduction of Internet of Things (IoT) technology in several sectors, wireless, reliable, and energy-saving communication in distributed sensor networks are more important than ever. Thereby, wake-up technologies are becoming increasingly important as they significantly contribute to reducing the energy consumption of wireless sensor nodes. In an indoor environment, the use of wireless sensors, in general, is more challenging due to signal fading and reflections and needs, therefore, to be critically investigated. This paper discusses the performance analysis of wakeup receiver (WuRx) architectures based on two low frequency (LF) amplifier approaches with regard to sensitivity, power consumption, and package error rate (PER). Factors that affect systems were compared and analyzed by analytical modeling, simulation results, and experimental studies with both architectures. The developedWuRx operates in the 868MHz band using on-off-keying (OOK) signals while supporting address detection to wake up only the targeted network node. By using an indoor setup, the signal strength and PER of received signal strength indicator (RSSI) in different rooms and distances were determined to build a wireless sensor network. The results show a wake-up packets (WuPts) detection probability of about 90% for an interior distance of up to 34 m.

This thesis presents four-quadrant CMOS current-mode multiplier architectures based on the bipolar Gilbert cell multiplier architecture. Multipliers are designed using the CMOS subthreshold region to take advantage of the subthreshold exponential I-V relationship that closely matches bipolar modeling. It is discovered that biasing to remove drift current components and to address higher order effects such as ideality factor mismatch, threshold mismatch, body effect, and short channel effects, is important to provide a linear multiplier. It is also shown that distortion caused by device size mismatch and offset input currents can be used to cancel the distortion introduced by drift currents when designing in weak and moderate inversion. This concept allows for linear multiplier designs with larger input currents which results in dramatic improvements in bandwidth over traditional weak inversion circuits. Three multiplier circuits are simulated and fabricated in an AMIS 0.35-um process. Circuits with less than 1 % nonlinear error and distortion (THD) across 100 % dynamic input range and with bandwidths greater than 100 MHz can be built. Also, low power multiplier solutions are presented that consume less than 40 nW of dynamic power.

This thesis demonstrates that the composite cascode differential stage, operating in the subthreshold region, can form the basis of a high gain (113 dB) and low-power op amp (28.1 µW). The circuit can be fabricated without adding a compensation capacitance. The advantages of this architecture include high voltage gain, low bandwidth, low harmonic distortion, low quiescent current and power, and small chip area. These advantages suggest that this design might be well-suited for biomedical applications where low power, low noise bio-signal amplifiers capable of amplifying signals in the millihertz-to-kilohertz range is required.

The Internet of Things (IoT) is leading the world to the Internet of Everything (IoE), where things, people, intelligent machines, data and processes will be connected together. The key to enter the era of the IoE lies in enormous sensor nodes being deployed in the massively expanding wireless sensor networks (WSNs). By the year of 2025, more than 42 billion IoT devices will be connected to the Internet. While the future IoE will bring priceless advantages for the life of mankind, one challenge limiting the nowadays IoT from further development is the ongoing power demand with the dramatically growing number of the wireless sensor nodes. To address the power consumption issue, this dissertation is motivated to investigate low-power wake-up receivers (WuRXs) which will significantly enhance the sustainability of the WSNs and the environmental awareness of the IoT. Two proof-of-concept low-power WuRXs with focuses on two different application scenarios have been proposed. The first WuRX, implemented in a cost-effective 180-nm CMOS semiconductor technology, operates at 401−406-MHz band. It is a good candidate for application scenarios, where both a high sensitivity and an ultra-low power consumption are in demand. Concrete use cases are, for instance, medical implantable applications or long-range communications in rural areas. This WuRX does not rely on a further assisting semiconductor technology, such as MEMS which is widely used in state-of-the-art WuRXs operating at similar frequencies. Thus, this WuRX is a promising solution to low-power low-cost IoT. The second WuRX, implemented in a 45-nm RFSOI CMOS technology, was researched for short-range communication applications, where high-density conventional IoT devices should be installed. By investigation of the WuRX for operation at higher frequency band from 5.5 GHz to 7.5 GHz, the nowadays ever more over-traffic issues that arise at low frequency bands such as 2.4 GHz can be substantially addressed. A systematic, analytical research route has been carried out in realization of the proposed WuRXs. The thesis begins with a thorough study of state-of-the-art WuRX architectures. By examining pros and cons of these architectures, two novel architectures are proposed for the WuRXs in accordance with their specific use cases. Thereon, key WuRX parameters are systematically analyzed and optimized; the performance of relevant circuits is modeled and simulated extensively. The knowledge gained through these investigations builds up a solid theoretical basis for the ongoing WuRX designs. Thereafter, the two WuRXs have been analytically researched, developed and optimized to achieve their highest performance. Proof-of-concept circuits for both the WuRXs have been fabricated and comprehensively characterized under laboratory conditions. Finally, measurement results have verified the feasibility of the design concept and the feasibility of both the WuRXs.

Interest in millimeter (mm-) wave frequencies covering the spectrum of 30-300 GHz has been steadily increasing. Advantages such as larger absolute bandwidth and smaller form-factor have made this frequency region attractive for numerous applications, including high-speed wireless communication, sensing, material science, health, automotive radar, and space exploration. Continuous development of silicon-germanium heterojunction bipolar transistor (SiGe HBT) and associated BiCMOS technology has achieved transistors with fT/fmax of 505/720 GHz and integration with 55 nm CMOS. Such accomplishment and predictions of beyond THz performance have made SiGe BiCMOS technology the most competitive candidate for addressing the aforementioned applications. Especially for mobile applications, a critical demand for future mm-wave applications will be low DC power consumption (Pdc), which requires a substantial reduction of supply voltage and current. Conventionally, reducing the supply voltage will lead to HBTs operating close to or in the saturation region, which is typically avoided in mm-wave circuits due to expectated performance degradation and often inaccurate models. However, due to only moderate speed reduction at the forward-biased base-collector voltage (VBC) up to 0.5 V and the accuracy of the compact model HICUM/L2 also in saturation, low-power mm-wave circuits with SiGe HBTs operating in saturation offer intriguing benefits, which have been explored in this thesis based on 130 nm SiGe BiCMOS technologies: • Different low-power mm-wave circuit blocks are discussed in detail, including low-noise amplifiers (LNAs), down-conversion mixers, and various frequency multipliers covering a wide frequency range from V-band (50-75 GHz) to G-band (140-220 GHz). • Aiming at realizing a better trade-off between Pdc and RF performance, a drastic decrease in supply voltage is realized with forward-biased VBC, forcing transistors of the circuits to operate in saturation. • Discussions contain the theoretical analysis of the key figure of merits (FoMs), topology and bias selection, device sizing, and performance enhancement techniques. • A 173-207 GHz low-power amplifier with 23 dB gain and 3.2 mW Pdc, and a 72-108 GHz low-power tunable amplifier with 10-23 dB gain and 4-21 mW Pdc were designed. • A 97 GHz low-power down-conversion mixer was presented with 9.6 dB conversion gain (CG) and 12 mW Pdc. • For multipliers, a 56-66 GHz low-power frequency quadrupler with -3.6 dB peak CG and 12 mW Pdc, and a 172-201 GHz low-power frequency tripler with -4 dB peak CG and 10.5 mW Pdc were realized. By cascading these two circuits, also a 176-193 GHz low-power ×12 multiplier was designed, achieving -11 dBm output power with only 26 mW Pdc. • An integrated 190 GHz low-power receiver was designed as one receiving channel of a G-band frequency extender specifically for a VNA-based measurement system. Another goal of this receiver is to explore the lowest possible Pdc while keeping its highly competitive RF performance for general applications requiring a wide LO tuning range. Apart from the low-power design method of circuit blocks, the careful analysis and distribution of the receiver FoMs are also applied for further reduction of the overall Pdc. Along this line, this receiver achieved a peak CG of 49 dB with a 14 dB tunning range, consuming only 29 mW static Pdc for the core part and 171 mW overall Pdc, including the LO chain. • All designs presented in this thesis were fabricated and characterized on-wafer. Thanks to the accurate compact model HICUM/L2, first-pass access was achieved for all circuits, and simulation results show excellent agreement with measurements. • Compared with recently published work, most of the designs in this thesis show extremely low Pdc with highly competitive key FoMs regarding gain, bandwidth, and noise figure. • The observed excellent measurement-simulation agreement enables the sensitivity analysis of each design for obtaining a deeper insight into the impact of transistor-related physical effects on critical circuit performance parameters. Such studies provide meaningful feedback for process improvement and modeling development.:Table of Contents Kurzfassung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv Table of Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii 1 Introduction 1 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 List of symbols and acronyms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2 Technology 7 2.1 Fabrication Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1.1 SiGe HBT performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1.2 B11HFC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.1.3 SG13G2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.1.4 SG13D7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.2 Commonly Used Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.2.1 Grounded-sidewall-shielded microstrip line . . . . . . . . . . . . . . . . . . 12 2.2.2 Zero-impedance Transmission Line . . . . . . . . . . . . . . . . . . . . . . 15 2.2.3 Balun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.2.3.1 Active Balun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.2.3.2 Passive Balun . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 3 Low-power Low-noise Amplifiers 25 3.1 173-207 GHz Ultra-low-power Amplifier . . . . . . . . . . . . . . . . . . . . . . . 25 3.1.1 Topology Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3.1.2 Bias Dependency of the Small-signal Performance . . . . . . . . . . . . . 27 3.1.2.1 Bias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 3.1.2.2 Bias vs Gain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.1.2.3 Bias vs Noise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.1.2.4 Bias vs Stability . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.1.3 Bias selection and Device sizing . . . . . . . . . . . . . . . . . . . . . . . . 36 3.1.3.1 Bias Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 3.1.3.2 Device Sizing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 3.1.4 Performance Enhancement Technologies . . . . . . . . . . . . . . . . . . . 41 3.1.4.1 Gm-boosting Inductors . . . . . . . . . . . . . . . . . . . . . . . 41 3.1.4.2 Stability Enhancement . . . . . . . . . . . . . . . . . . . . . . . 43 3.1.4.3 Noise Improvement . . . . . . . . . . . . . . . . . . . . . . . . . 45 3.1.5 Circuit Realization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3.1.5.1 Layout Scheme . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3.1.5.2 Inductors Design . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 3.1.5.3 Dual-band Matching Network . . . . . . . . . . . . . . . . . . . 48 3.1.5.4 Circuit Implementation . . . . . . . . . . . . . . . . . . . . . . . 50 3.1.6 Results and Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 3.1.6.1 Measurement Setup . . . . . . . . . . . . . . . . . . . . . . . . . 51 3.1.6.2 Measurement Results . . . . . . . . . . . . . . . . . . . . . . . . 51 3.1.6.3 Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 3.2 72-108 GHz Low-Power Tunable Amplifier . . . . . . . . . . . . . . . . . . . . . . 55 3.2.1 Configuration, Sizing, and Bias Tuning Range . . . . . . . . . . . . . . . . 55 3.2.2 Regional Matching Network . . . . . . . . . . . . . . . . . . . . . . . . . . 57 3.2.2.1 Impedance Variation . . . . . . . . . . . . . . . . . . . . . . . . . 57 3.2.2.2 Regional Matching Network Design . . . . . . . . . . . . . . . . 60 3.2.3 Circuit Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 3.2.4 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 3.2.4.1 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 3.2.4.2 Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 3.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 4 Low-power Down-conversion Mixers 73 4.1 97 GHz Low-power Down-conversion Mixer . . . . . . . . . . . . . . . . . . . . . 74 4.1.1 Mixer Design and Implementation . . . . . . . . . . . . . . . . . . . . . . 74 4.1.1.1 Mixer Topology . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 4.1.1.2 Bias Selection and Device Sizing . . . . . . . . . . . . . . . . . . 77 4.1.1.3 Mixer Implementation . . . . . . . . . . . . . . . . . . . . . . . . 79 4.1.2 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 4.1.2.1 Measurement Results . . . . . . . . . . . . . . . . . . . . . . . . 80 4.1.2.2 Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 4.2 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 5 Low-power Multipliers 87 5.1 General Design Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 5.2 56-66 GHz Low-power Frequency Quadrupler . . . . . . . . . . . . . . . . . . . . 89 5.3 172-201 GHz Low-power Frequency Tripler . . . . . . . . . . . . . . . . . . . . . 93 5.4 176-193 GHz Low-power ×12 Frequency Multiplier . . . . . . . . . . . . . . . . . 96 5.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 6 Low-power Receivers 101 6.1 Receiver Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 6.2 LO Chain (×12) Integrated 190 GHz Low-Power Receiver . . . . . . . . . . . . . 104 6.2.1 Receiver Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 6.2.2 Low-power Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 6.2.3 Building Blocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 6.2.3.1 LNA and LO DA . . . . . . . . . . . . . . . . . . . . . . . . . . 108 6.2.3.2 Tunable Mixer and IF BA . . . . . . . . . . . . . . . . . . . . . 111 6.2.3.3 65 GHz (V-band) Quadrupler . . . . . . . . . . . . . . . . . . . 116 6.2.3.4 G-band Tripler . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 6.2.4 Receiver Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . 123 6.2.5 Measurement Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 6.2.6 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 6.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 7 Conclusions 133 7.1 Summaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 7.2 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 Bibliography 135 List of Figures 149 List of Tables 157 A Derivation of the Gm 159 A.1 Gm of standard cascode stage . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 A.2 Gm of cascode stage with Lcas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 A.3 Gm of cascode stage with Lb . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 B Derivation of Yin in the stability analysis 163 C Derivation of Zin and Zout 165 C.1 Zin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 C.2 Zout . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 D Derivation of the cascaded oP1dB 169 E Table of element values for the designed circuits 171

OMA’s Lightweight Machine to Machine (LwM2M) is an application protocol for device management in the Internet of Things (IoT) that has been recently published and widely adopted in a lot of projects. The protocol is designed to operate in sensor networks and machine-to-machine environments, where one of the main constraints is the energy consumption since the nodes are usually battery powered. Different strategies to achieve high energy efficiency in IoT networks have been developed, but there is no deep knowledge about the performance of LwM2M operating with them. Moreover, the specification of this protocol includes one strategy, called the Queue Mode, which could be more efficient than the usual ones because it has been specified for this particular protocol. This project aims to implement this Queue Mode at both sides of the communication, and then evaluate its performance by comparing it with TSCH, which is the standard MAC protocol used in IEEE 802.15.4 that defines a way of radio duty cycling. It has been proven to achieve a high energy efficiency, and that is the main reason why it is selected. The comparison is performed according to several metrics to have a comprehensive evaluation, and in different kind of scenarios, with different numbers of IoT devices and different parameters in the communication. The implementation was done inside the Contiki-NG OS for the client side, which is an operating systems designed for constrained devices. For the server side it has been carried out inside the Eclipse Leshan code, which is a LwM2M implementation in Java made by the Eclipse Foundation. As a result of the evaluation, it shown that both implementations operate correctly. This thesis contributes as a guideline for making decisions about which low power strategy is better to use depending on the IoT scenario and the type of application. It shows that for many use cases Queue Mode is a better option than TSCH because it achieves a higher energy efficiency and the rest of the metrics used in the evaluation have also improved values. TSCH has a better performance only in demanding scenarios or in cases where the communication is not produced at fixed time instants. The thesis was developed in cooperation with RISE SICS AB, Networked Embedded Systems Group. / OMA:s Lightweight Machine to Machine (LwM2M) är ett applikationsprotokoll för enhetshantering i Sakernas Internet (IoT) som nyligen har publicerats och börjat användas i många projekt. Protokollet är utformat för att fungera i sensornätverk och maskin-till-maskin miljöer, där en av de viktigaste begränsningarna är energiförbrukningen eftersom noderna vanligtvis är batteridrivna. Olika strategier för att uppnå hög energieffektivitet i sensornätverk har utvecklats, men det finns ingen djup kunskap om hur LwM2M fungerar med dem. Dessutom innehåller specifikationen av LwM2M en strategi kallad Queue Mode (köläge) som kan vara effektivare än de vanliga strategierna eftersom den har utvecklats direkt för det här protokollet.Detta examensarbete syftar till att implementera detta köläge på båda sidor av kommunikationen och sedan utvärdera prestandan genom att jämföra det med TSCH, vilket är ett MAC-protokoll specificerat i IEEE 802.15.4-standarden. Tidigare arbeten har visat att TSCH kan uppnå en låg energiförbrukning, vilket är den främsta anledningen till att detta protokoll väljs ut för att jämföra mot LwM2M:s köläge. Jämförelsen inkluderar flera olika typer av mätvärden och scenarier för att få en omfattande utvärdering, samt med flera olika antal sensor noder och parametrar.Implementationen gjordes för Contiki-NG OS på klientsidan, vilket är ett operativsystem för resursbegränsade IoT-enheter. På serversidan har implementationen gjorts för Eclipse Leshan, vilken är en LwM2M-implementation skriven i Java och publicerad av Eclipse Foundation. Som en följd av utvärderingen har det visat sig att båda implementationerna fungerar korrekt.Detta examensarbete bidrar med riktlinjer för att fatta beslut om vilken energibesparingsstrategi som är bättre att använda beroende på IoT-scenariot och typen av applikation. Utvärderingen visar hur Queue Mode i många användningsfall är ett bättre alternativ än TSCH eftersom det uppnår en högre energieffektivitet utan att de andra typerna av mätvärden påverkas av det. I vissa fall uppnås dessutom förbättrade resultat även i de andra typerna av mätvärden. TSCH har endast bättre prestanda i krävande scenarier eller i fall där kommunikationen inte genereras vid bestämda tillfällen.Examensarbetet har genomförts hos Networked Embedded Systems-gruppen på RISE SICS AB.