| Title | (Invited Paper) Challenges and Opportunities of Internet of Things |
| Author | *Yen-Kuang Chen (Intel Corporation, U.S.A.) |
| Page | pp. 383 - 388 |
| Keyword | internet |
| Abstract | To date, most Internet applications focus on providing information, interaction, and entertainment for humans. However, with the widespread deployment of networked, intelligent sensor technologies, an Internet of Things (IoT) is steadily evolving, much like the Internet decades ago. In the future, hundreds of billions of smart sensors and devices will interact with one another without human intervention, on a Machine-to-Machine (M2M) basis. They will generate an enormous amount of data at an unprecedented scale and resolution, providing humans with information and control of events and objects even in remote physical environments. The scale of the M2M Internet will be several orders of magnitude larger than the existing Internet, posing serious research challenges. This paper will provide an overview of challenges and opportunities presented by this new paradigm. |
| Title | (Invited Paper) Application Specific Sensor Node Architecture Optimization --- Experiences from Field Deployments |
| Author | *Wei Liu, Xiaotian Fei, Tao Tang, Pengjun Wang, Hong Luo, Beixing Deng, Huazhong Yang (Department of Electronic Engineering, Tsinghua University, China) |
| Page | pp. 389 - 394 |
| Keyword | sensor node architecture |
| Abstract | The Mote architecture is the most popular platform used in wireless sensor network applications. In this architecture, microcontroller is responsible for all jobs, such as scheduling, sampling, computing, and communication. In the past one year, two practical applications: bridge structural health monitoring system and rare animal monitoring system are developed and deployed in Wuxi and Beijing, China. It is found that Mote architecture faces many problems in these applications. First, sampling, computing, and communication conflicts with each other if they are not carefully scheduled; second, some jobs are very difficult even impossible to be implemented in the microcontroller; third, low power, one of the most fundamental design principles in wireless sensor networks, is sometimes violated with all jobs implemented in the microcontroller. Software optimization is attempted to solve these problems. However, the effect is very limited. Application specific sensor node architecture is necessary for implementing these applications efficiently. In this paper, we propose new application specific sensor node architecture and corresponding design principles and then applied them in the field deployments. Experimental and field tests show that these architectures are more efficient than Mote architecture in these applications. |
| Title | (Invited Paper) System-Wide Profiling and Optimization with Virtual Machines |
| Author | *Shih-Hao Hung, Tei-Wei Kuo, Chi-Sheng Shih (Graduate Institute of Networking and Multimedia and Department of Computer Science and Information Engineering, National Taiwan University, Taiwan), Chia-Heng Tu (Graduate Institute of Networking and Multimedia, Taiwan) |
| Page | pp. 395 - 400 |
| Keyword | profiling, virtual machines |
| Abstract | Simulation is a common approach for assisting system design and optimization. For system-wide optimization, energy and computational resources are often the two most critical limitations. Modeling energy-states of each hardware component and time spent in each state is needed for accurate energy and performance prediction. Tracking software execution in a realistic operating environment with properly modeled input/output is key to accurate prediction. However, the conventional approaches can have difficulties in practice. First, for a complex system such as an Android smartphone, building a cycle-accurate simulation environment is no easy task. Secondly, for I/O-intensive applications, a slow simulation would significantly alter the application behavior and change its performance profile. Thirdly, conventional software profiling tools generally do not work on simulators, which makes it difficult for performance analysis of complicated software, e.g., Java applications executed by the Dalvik virtual machine. Recently, virtual machine technologies are widely used to emulate a variety of computer systems. While virtual machines do not model the hardware components in the emulated system, we can ease the effort of building a simulation environment by leveraging the infrastructure of virtual machines and adding performance and power models. Moreover, multiple sets of the performance and energy models can be selectively used to verify if the speed of the simulated system impacts the software behavior. Finally, performance monitoring facilities can be integrated to work with profiling tools. We believe this approach should help overcome the aforementioned difficulties. We have prototyped a framework and our case studies showed that the information provided by our tools are useful for software optimization and system design for Android smartphones. |
| Title | (Invited Paper) Power Optimization of Wireless Video Sensor Nodes in M2M Networks |
| Author | *Shao-Yi Chien, Teng-Yuan Cheng, Chieh-Chuan Chiu, Pei-Kuei Tsung (Graduate Institute of Electronics Engineering and Department of Electrical Engineering, National Taiwan University, Taiwan), Chia-han Lee (Research Center for Information Technology Innovation, Academia Sinica, Taiwan), V. Srinivasa Somayazulu, Yen-Kuang Chen (Intel Corporation, U.S.A.) |
| Page | pp. 401 - 405 |
| Keyword | M2M network |
| Abstract | Low-power wireless video sensor nodes play important roles for applications in machine-to-machine (M2M) network. Several design issues to optimize the power consumption of a video sensor node are addressed in this paper. For the video coding engine selection, the comparison between conventional video coding system and distributed video coding (DVC) system shows that although the rate-distortion performance of existing DVC codec still has room to improve, it can provide lower power consumption with a noisy transmission channel. Furthermore, it also demonstrated that video analysis unit can help to filter out video contents without event-of-interest to reduce transmission power. Finally, several future research directions are addressed, and the trade-off between the video analysis unit, video coding unit, and data transmission should be further studied to design wireless video sensors with optimized power consumption. |