This report is the specification for the Trading Agent Competition Supply Chain Management Game - TAC SCM-04, to be held between July 20-22, 2004, in New York in conjunction with AAMAS-04. Based on the experience of the 2003 Trading Agent Competition a few enhancements have been added to the original game: (1)The price function has been modified to better reflect demand; (2) storage costs have been introduced; and (3) customer demand has been segmented into multiple markets.
The Supply Chain Management Game for the 2005 Trading Agent Competition held during IJCAI 2005, in Edinburgh, Scotland. The supplier model has been substantially revised to overcome the "Day Zero" strategic singularity in TAC SCM 2003 and 2004.
Low-power wireless networks are quickly becoming a critical part of our everyday infrastructure. Power consumption is a critical concern, but power measurement and estimation is a challenge. We present Powertrace, which to the best of our knowledge is the first system for network-level power profiling of low-power wireless systems. Powertrace uses power state tracking to estimate system power consumption and a structure called energy capsules to attribute energy consumption to activities such as packet transmissions and receptions. With Powertrace, the power consumption of a system can be broken down into individual activities which allows us to answer questions such as “How much energy is spent forwarding packets for node X?”, “How much energy is spent on control traffic and how much on critical data?”, and “How much energy does application X account for?”. Experiments show that Powertrace is accurate to 94% of the energy consumption of a device. To demonstrate the usefulness of Powertrace, we use it to experimentally analyze the power behavior of the proposed IETF standard IPv6 RPL routing protocol and a sensor network data collection protocol. Through using Powertrace, we find the highest power consumers and are able to reduce the power consumption of data collection with 24%. It is our hope that Powertrace will help the community to make empirical energy evaluation a widely used tool in the low-power wireless research community toolbox.
The Internet of Things requires interoperability and low power consumption, but interoperability and low power consumption have thus far been mutually exclusive. This talk outlines the challenges in attaining low power operation for the IPv6-based Internet of Things, how this affects interoperability, and what must be done to combine the two.
From experience with wireless sensor networks it has become apparent that dynamic reprogramming of the sensor nodes is a useful feature. The resource constraints in terms of energy, memory, and processing power make sensor network reprogramming a challenging task. Many different mechanisms for reprogramming sensor nodes have been developed ranging from full image replacement to virtual machines. We have implemented an in-situ run-time dynamic linker and loader that use the standard ELF object file format. We show that run-time dynamic linking is an effective method for reprogramming even resource constrained wireless sensor nodes. To evaluate our dynamic linking mechanism we have implemented an application-specific virtual machine and a Java virtual machine and compare the energy cost of the different linking and execution models. We measure the energy consumption and execution time overhead on real hardware to quantify the energy costs for dynamic linking. Our results suggest that while in general the overhead of a virtual machine is high, a combination of native code and virtual machine code provide good energy efficiency. Dynamic run-time linking can be used to update the native code, even in heterogeneous networks.
Internet of Things (IoT) is the concept of connecting devices to the Internet. IoT devices can be anything from small temperature sensors to self-driving cars. The devices are typically resource-constrained, connected wirelessly, and often battery-powered. In this thesis, we address energy efficiency and the tools required for estimating power consumption, interoperability between different implementations of IoT protocols, and scalability of the IoT networks in mesh configurations. The contributions are made in the five included research papers addressing these challenges. Firstly, we present and evaluate network-wide energy estimation support in our simulation tool COOJA/MSPSim. Due to the timing accuracy of the simulation and emulation, we get energy consumption estimates very close to hardware-based estimates. The second contribution evaluates the capabilities of simulation tools for interoperability testing. We show that it is possible to set up simulations of networks with multiple implementations of the same open standards (6LoWPAN/RPL) and that it is possible to get results beyond pure interoperability, including power consumption and network quality. Finally, we show that, by carefully managing neighbor updates, it is possible to scale IoT networks even when the IoT devices' memory limitations severely constrain the size of the neighbor table.
The experimental systems research that resulted in this thesis also provided significant contributions to the open-source ecosystem around Contiki, an operating system for resource-constrained IoT devices. This software, Contiki and COOJA/MSPSim, has been a cornerstone in our capability to perform sound systems research and has been widely used by other research groups in resource-constrained IoT research in academia and many companies for developing commercial IoT devices.
TAC SCM is a supply chain management game for the Trading Agent Competition (TAC). The purpose of TAC is to spur high quality research into realistic trading agent problems. We discuss TAC and TAC SCM: game and competition design, scientific impact, and lessons learnt.
We present a simple and uniform communication framework for an agent-based market infrastructure, the goal of which is to enable automation of markets with self-interested participants distributed over the Internet.
The Internet of Things poses new requirements for reliable, bi-directional communication in low-power and lossy networks, but these requirements are hard to fulfill since most existing protocols have been designed for data collection. In this paper, we propose standard-compliant mechanisms that make RPL meet these requirements while still scaling to large networks of IoT devices under significant resource constraints. Our aim is to scale far beyond what can be stored in RAM on the nodes of the network. The only node that needs to have storage for all the routing entries is the RPL root node. Based on experimentation with largescale commercial deployments, we suggest two mechanisms to make RPL scale under resource constraints: (1) end-to-end route registration with DAO and (2) a policy for managing the neighbor table. By employing these mechanisms, we show that the bi-directional packet reception rate of RPL networks increases significantly.
The finals of the third annual Trading Agent Competition were held on 28 July 2002, co-located with AAA1-02 in Edmonton, Canada. The actual games took place on the Internet, with the game and auction servers running at SICS in Kista, Sweden. The agents resided at the home locations of the participating research groups.
Privata 5G nätverk – antingen som en del av ett publikt eller som ett helt eget mobilnät erbjuder möjliga lösningar på ett antal av de utmaningar som finns kring WiFi och trådlösa uppkopplingar i logistik och produktion. Tekniken börjar bli väletablerad och antalet leverantörer ökar snabbt samtidigt som priser för infrastrukturen sjunker i pris. Förutom att femte generationens mobilnät löser problem kring mobilitet och uppkoppling så finns ett antal intressanta funktioner såsom positionering och standardiserad edge computing för lokala digitala tjänster. Dessa funktioner bör dock ses som en del av en framtida uppgradering snarare än något som finns tillgängligt idag (dock inte så långt bort in i framtiden). Alla de besökta sågverken hade liknande utmaningar kring trådlös uppkoppling och i vissa fall har även 4G-baserade lösningar börjat användas – med gott resultat.
Tyvärr fick vi inte konkreta priser från de operatörer och leverantörer som dialog fördes med men via vissa leverantörer kan man ändå få en viss indikation (se t ex AWS erbjudande där det för ett privat nät med två radioaccespunkter ligger på ca 140 KSEK / månad totalt).
Power consumption is of utmost concern in sensor networks. Researchers have several ways of measuring the power consumption of a complete sensor network, but they are typically either impractical or inaccurate. To meet the need for practical and scalable measurement of power consumption of sensor networks, we have developed a cycle-accurate simulator, called COOJA/MSPsim, that enables live power estimation of systems running on MSP430 processors. This demonstration shows the ease of use and the power measurement accuracy of COOJA/MSPsim. The demo setup consists of a small sensor network and a laptop. Beside gathering software-based power measurements from the motes, the laptop runs COOJA/MSPsim to simulate the same network. We visualize the power consumption of both the simulated and the real sensor network, and show that the simulator produces matching results.
Various experiments have shown that the performance of wireless sensor networks is very hard to predict. It is also acknowledged that deploying sensor networks in real settings is a difficult and tedious task. To contribute to the understanding of wireless sensor network behavior we report on our experience from two recently deployed sensor networks: one in-door surveillance network in a factory complex and a combined out-door and in-door surveillance network. Both networks use advanced sensor network technology such as ad hoc routing and multi hop networking. Our results highlight the need for self-configuration in wireless sensor networks, especially in cases where fast deployment and dynamic environments are important aspects.
Despite sensor network protocols being self-configuring, sensor network deployments continue to fail. We report our experience from two recently deployed IP-based multi-hop sensor networks: one in-door surveillance network in a factory complex and a combined out-door and in-door surveillance network. Our experiences highlight that adaptive protocols alone are not sufficient, but that an approach to self-monitoring and self-configuration that covers more aspects than protocol adaptation is needed. Based on our experiences, we design and implement an architecture for self-monitoring of sensor nodes. We show that the self-monitoring architecture detects and prevents the problems with false alarms encountered in our deployments. The architecture also detects software bugs by monitoring actual and expected duty-cycle of key components of the sensor node. We show that the energy-monitoring architecture detects bugs that cause the radio chip to be active longer than expected.
Many sensor network protocols are self-configuring, but independent self-configuration at different layers often results in suboptimal performance. We present Chi, a full-system configuration architecture that separates system logic from system configuration. Drawing from concepts in artificial intelligence, Chi allows full-system configuration that meets both changing application demands and changing environmental conditions. We show that configuration policies using Chi can improve throughput and energy efficiency without adding dependencies between layers. Our results show that sensornet systems can use Chi to adapt to changing conditions at all layers of the system, thus meeting the requirements of heterogeneous and continuously changing system conditions.
Wireless low-power, multi-hop networks are exposed to numerous attacks also due to their resource-constraints. While there has been a lot of work on intrusion detection systems for such networks, most of these studies have considered only a few topologies, scenarios and attacks. One of the reasons for this shortcoming is the lack of sufficient data traces that are required to train many machine learning algorithms. In contrast to other wireless networks, multi-hop networks do not contain one entity that can capture all the traffic which makes it more difficult to acquire such traces. In this paper we present Multi-Trace. Multi-Trace extends the Cooja simulator with multi-level tracing facilities that enable data logging at different levels while maintaining a global time. We discuss the opportunities that traces generated by Multi-Trace enable for researchers interested in input for their machine learning algorithms. We present experiments that show the efficiency with which Multi-Trace generates traces. We expect Multi-Trace to be a useful tool for the research community.
Standard protocols for wireless Internet of Things (IoT) communication must be energy-efficient in order to prolong the lifetimes of IoT devices. Two energy-saving strategies for wireless communication are prevalent within the IoT domain: 1) sleepy devices and 2) radio duty cycling. In this paper, we conduct a comprehensive evaluation as to what types of application scenarios benefit the most from either type of energy-saving strategy. We select the lightweight machine to machine (LwM2M) protocol for this purpose because it operates atop the standard constrained application protocol, and has support for sleepy devices through its Queue Mode. We implement the Queue Mode at both the server side and client side, and design enhancements of Queue Mode to further improve the performance. In our experimental evaluation, we compare the performance and characteristics of Queue Mode with that of running LwM2M in a network stack with the standard time-slotted channel hopping as the duty cycling medium access control protocol. By analyzing the results with the support of an empirical model, we find that each energy-saving strategy has different advantages and disadvantages depending on the scenario and traffic pattern. Hence, we also produce guidelines that can help developers to select the appropriate energy-saving strategy based on the application scenario.
Wireless sensor networks for building automation and energy management has made great progress in recent years, but the inherent indoor radio range limitations can make communication unpredictable and system deployments difficult. Low-power radio can be combined with low-power Power-Line Communication (PLC) to extend the range and predictability of indoor communication for building management and automation systems. We take the first steps towards exploring the system implications for integration of low-power wireless and PLC in the same network. We leverage IPv6, which allow networks to exist over multiple physical communication media as well as the RPL routing protocol for low-power lossy networks.
Low-power wireless networks transmit at low output power and are hence susceptible to cross-technology interference. The latter may cause packet loss which may waste scarce energy resources by requiring the retransmission of packets. Jamming attacks are even more harmful than cross-technology interference in that they may totally prevent packet reception and hence disturb or even disrupt applications. Therefore, it is important to recognize such jamming attacks. In this paper, we present JamSense. JamSense extends SpeckSense, a system that is able to detect multiple sources of interference, with the ability to classify jamming attacks. As SpeckSense, JamSense runs on resource-constrained nodes. Our experimental evaluation on real hardware shows that JamSense is able to identify jamming attacks with high accuracy while not classifying Bluetooth or WiFi interference as jamming attacks.
Interoperability is essential for the commercial adoption of wireless sensor networks. However, existing sensor network architectures have been developed in isolation and thus interoperability has not been a concern. Recently, IP has been proposed as a solution to the interoperability problem of low-power and lossy networks (LLNs), considering its open and standards-based architecture at the network, transport, and application layers. We present two complete and interoperable implementations of the IPv6 protocol stack for LLNs, one for Contiki and one for TinyOS, and show that the cost of interoperability is low: their performance and overhead is on par with state-of-the-art protocol stacks custom built for the two platforms. At the same time, extensive testbed results show that the ensemble performance of a mixed network with nodes running the two interoperable stacks depends heavily on implementation decisions and parameters set at multiple protocol layers. In turn, these results argue that the current industry practice of interoperability testing does not cover the crucial topic of the performance and motivate the need for generic techniques that quantify the performance of such networks and configure their run-time behavior.
Interoperability is key to widespread adoption of sensor network technology, but interoperable systems have traditionally been difficult to develop and test. We demonstrate an interoperable system development and performance diagnosis environment in which different systems, different software, and different hardware can be simulated in a single network configuration. This allows both development, verification, and performance diagnosis of interoperable systems. Estimating the performance is important since even when systems interoperate, the performance can be sub-optimal, as shown in our companion paper that has been conditionally accepted for SenSys 2011.
—This demo presents SicsthSense, our open cloud platform for the Internet of Things. SicsthSense enables low power devices such as sensor nodes and smartphones to easily store their generated data streams in the cloud. This allows the data streams, and their history, to be made permanently available to users for visualisation, processing and sharing. Moving sensor data computation and monitoring into the cloud is a promising avenue to enable centralisation of control and redistribution of collected data. We showcase SicsthSense running with real sensor nodes collecting environmental data and posting it to our datastore. This live data is then visualised and made available for sharing between users of the platform. Our Android App will also be distributed to enable participants to stream their phone sensors into the system, demonstrating how simple it can be to start machine-to-machine interactions with SicsthSense.
A wide gap exists between the state of the art in developing Wireless Sensor Network (WSN) software and current practices concerning the design, execution, and maintenance of business processes. WSN software is most often developed based on low-level OS abstractions, whereas business process development leverages high-level languages and tools. This state of affairs places WSNs at the fringe of industry. The makeSense system addresses this problem by simplifying the integration of WSNs into business processes. Developers use BPMN models extended with WSN-specific constructs to specify the application behavior across both traditional business process execution environments and the WSN itself, which is to be equipped with application-specific software. We compile these models into a high-level intermediate language-Also directly usable by WSN developers-And then into OS-specific deployment-ready binaries. Key to this process is the notion of meta-Abstraction, which we define to capture fundamental patterns of interaction with and within the WSN. The concrete realization of meta-Abstractions is application-specific; developers tailor the system configuration by selecting concrete abstractions out of the existing codebase or by providing their own. Our evaluation of makeSense shows that i) users perceive our approach as a significant advance over the state of the art, providing evidence of the increased developer productivity when using makeSense; ii) in large-scale simulations, our prototype exhibits an acceptable system overhead and good scaling properties, demonstrating the general applicability of makeSense; and, iii) our prototype-including the complete tool-chain and underlying system support-sustains a real-world deployment where estimates by domain specialists indicate the potential for drastic reductions in the total cost of ownership compared to wired and conventional WSN-based solutions.
Contiki-NG (Next Generation) is an open source, cross-platform operating system for severely constrained wireless embedded devices. It focuses on dependable (reliable and secure) low-power communications and standardised protocols, such as 6LoWPAN, IPv6, 6TiSCH, RPL, and CoAP. Its primary aims are to (i) facilitate rapid prototyping and evaluation of Internet of Things research ideas, (ii) reduce time-to-market for Internet of Things applications, and (iii) provide an easy-to-use platform for teaching embedded systems-related courses in higher education. Contiki-NG started as a fork of the Contiki OS and retains many of its original features. In this paper, we discuss the motivation behind the creation of Contiki-NG, present the most recent version (v4.7), and highlight the impact of Contiki-NG through specific examples. © 2022 The Authors
Contiki-NG (Next Generation) is an open source, cross-platform operating system for severely constrained wireless embedded devices. It focuses on dependable (reliable and secure) low-power communications and standardised protocols, such as 6LoWPAN, IPv6, 6TiSCH, RPL, and CoAP. Its primary aims are to (i) facilitate rapid prototyping and evaluation of Internet of Things research ideas, (ii) reduce time-to-market for Internet of Things applications, and (iii) provide an easy-to-use platform for teaching embedded systems-related courses in higher education. Contiki-NG started as a fork of the Contiki OS and retains many of its original features. In this paper, we discuss the motivation behind the creation of Contiki-NG, present the most recent version (v4.7), and highlight the impact of Contiki-NG through specific examples.
Two-way time of flight (ToF) ranging is one of the most interesting approaches for localization in wireless sensor networking since previous ToF ranging approaches using commercial off-the-shelf (COTS) devices have achieved good accuracy. The COTS-based approaches were, however, evaluated only in line-of-sight conditions. In this paper, we extend ToF ranging using multiple IEEE 802.15.4 channels. Our results demonstrate that with multiple channels we can achieve good accuracy even in non line-of-sight conditions. Furthermore, our measurements suggest that the variance between different channels serves as a good estimate of the accuracy of the measurements, which can be valuable information for applications that require localization information.
The Internet of Things (IoT) is the interconnection of everyday physical objects with the Internet and their representation in the digital world. Due to the connectivity of physical objects with the untrusted Internet, security has become an important pillar for the success of IoT-based services. Things in the IoT are resource-constrained devices with limited processing and storage capabilities. Often, these things are battery powered and connected through lossy wireless links. Therefore, lightweight and efficient ways of providing secure communication in the IoT are needed. In this context, Elliptic Curve Cryptography (ECC) is considered as a strong candidate to provide security in the IoT while being able to function in constrained environments. In this paper we present a lightweight implementation and evaluation of ECC for the Contiki OS. For fast, secure and cost-effective mass development of IoT-based services by different vendors, it is important that the IoT protocols are implemented and released as open source and open licensed. To the best of our knowledge our ECC is the first lightweight BSD-licensed ECC for the IoT devices. We show the feasibility of our implementation by a thorough performance analysis using several implementations and optimization algorithms. Moreover, we evaluate it on a real IoT hardware platform.
Security has arisen as an important issue for the Internet of Things (IoT). Efficient ways to provide secure communication between devices and sensors is crucial for the IoT devices, which are becoming more and more used and spread in a variety of fields. In this context, Elliptic Curve Cryptography (ECC) is considered as a strong candidate to provide security while being able to be functional in an environment with strong requirements and limitations such as wireless sensor networks (WSN). Furthermore, it is a valid candidate to be used in industry solutions.
In this demo we show a real use case of Elliptic Curve Cryptography for key establishment in combination with symmetric AES encryption. The demo will show the use of a BSD-licensed ECC library for the Contiki OS running on Yanzi Networks Contiki-based nodes that will securely communicate with a Yanzi Gateway.
The Trading Agent Competition (TAC) has now become an annual fixture since its inception in 2000. The competition was conceived with the objective of studying automated trading strategies by focusing the research community on the development of competing solutions to a common trading scenario. The success of past TAC events has motivated broadening the scope of the competition beyond the context of the travel agent scenario used thus far. For the fourth edition of this competition, TAC-03, to be held in August 2003, the authors have created a novel supply-chain trading game with the aim of investigating automated agents in the context of dynamic supply-chain management.
Low-power networked devices, such as sensors and actuators, are becoming a vital part of our everyday infrastructure. Being networked, the continued development of these systems needs involvement of the networking community. We present a framework for simulation, experimentation, and evaluation of routing mechanisms for low-power IPv6 networking. The framework provides a detailed simulation environment for low-power routing mechanisms and allows the system to be directly uploaded to a physical testbed for experimental measurements.