Yuto Lim

Development of a smart community simulator with individual emulation modules for community facilities and houses

A smart community simulator that simulates electricity consumption and thermal energy consumption is being developed by the authors. The simulator is designed to be able to work with modules implemented as individual external emulators of many kinds of facilities and homes. With this simulator, we can change aspects and features of the community and estimate the long-term effects of these changes on the community as a whole. In this paper we introduced the design and implementation of the simulator.

Management architecture for heterogeneous IoT devices in home network

The Internet of Things (IoT) is being hailed as the next industrial revolution and it promises billion of IoT devices connected to the Internet in the near future. Emerging networking and back-end support technologies not only have to anticipate this dramatic increase in connected devices, but also the heterogeneity of devices. To this end, a management architecture which combines current management approaches to manage devices in the home network is presented. By inheriting advantages of these approaches, the proposed architecture is able to support multiple device classes, enables management services for time sensitive devices and sleepy devices, mitigates home gateway bottleneck issues and enables local management in the home network. To validate this architecture, a prototype based on the proposed architecture for managing ECHONET LITE devices and Constrained Application Protocol (CoAP) enabled devices was developed.

Scheduling overload for real-time systems using SMT solver

In a real-time system, tasks are required to be completed before their deadlines. Due to heavy workload, the system may be in overload condition under which some tasks may miss their deadlines. To alleviate the degrees of system performance degradation cased by the missed deadline tasks, the design of scheduling is crucial. Many design objectives can be considered. In this paper, we focus on maximizing the total number of tasks that can be completed before their deadlines. A scheduling method based on satisfiability modulo theories (SMT) is proposed. In the method, the problem of scheduling is treated as a satisfiability problem. The key work is to formalize the satisfiability problem using first-order language. After the formalization, a SMT solver (e.g., Z3, Yices) is employed to solver such a satisfiability problem. An optimal schedule can be generated based on a solution model returned by the SMT solver. The correctness of this method and the optimality of the generated schedule are straightforward. The time efficiency of the proposed method is demonstrated through various simulations. To the best of our knowledge, it is the first time introducing SMT to solve overload problem in real-time scheduling domain.

Factors Affecting Sentiment Prediction of Malay News Headlines Using Machine Learning Approaches

Most sentiment analysis researches are done with the help of supervised machine learning techniques. Analyzing sentiment for these English text reviews is a non-trivial task in order to gauge public perception and acceptance of a particular issue being addressed. Nevertheless, there are not many studies conducted on analyzing sentiment of Malay news headlines due to lack of resources and tools. The Malay news headlines normally consist of a few words and are often written with creativity to attract the readers’ attention. This paper proposes a standard framework that investigates factors affecting sentiment prediction of Malay news headlines using machine learning approaches. It is important to investigate factors (e.g., types of classifiers, proximity measurements and number of Nearest Neighbors, k) that influence the prediction performance of the sentiment analysis as it helps to study and understand the parameters that can be tuned to optimize the prediction performance. Based on the results obtained, Support Vector Machine and Naive Bayes classifiers were capable to obtain higher accuracy compared to the k-Nearest Neighbors (k-NN) classifier. In term of proximity measurement and number of Nearest Neighbors, k, the k-NN classifier achieved higher prediction performance when the Cosine similarity is applied with a small value of k (e.g., 3 and 5), compared to the Euclidean distance because it measures can be affected by the high dimensionality of the data.

SMT-based scheduling for multiprocessor real-time systems

Real-time system is playing an important role in our society. For such a system, sensitivity to timing is the central feature of system behaviors, which means tasks in the system are required to be completed before their deadlines. Currently, almost all the practical real-time systems are equipped within multiple processors, for which the schedule synthesis to make sure that all the tasks can be completed before their deadlines is known to be an NP complete problem. In this paper, to solve the scheduling problem, we propose a scheduling method based on satisfiability modulo theories (SMT). In the method, the problem of scheduling is treated as a satisfiability problem. The key work is to formalize the satisfiability problem using first-order language. After the formalization, a SMT solver (e.g., Z3, Yices) is employed to solve such a satisfiability problem. An optimal schedule can be generated based on a solution model returned by the SMT solver. Moreover, in the SMT-based scheduling method, we define the scheduling constraints as system constraints and target constraints. Such design makes the proposed method apply more widely compared with existing methods.

Design and evaluation of hybrid temperature control for cyber-physical home systems

The design of control systems is crucial for improving the comfort level of the home environment. Cyber-physical systems (CPSs) can offer numerous opportunities to design highly efficient control systems. In this paper, we focus on the design and evaluation of temperature control systems. By using the idea of CPS, a hybrid temperature control (HTC) system is proposed. Through an energy efficient temperature control (EETC) algorithm, the HTC system maintains the room temperature in the desired interval. In the tight integration of physical and cyber worlds, the sensing accuracy of the physical platform has significant impact on the performance of the HTC system. Through simulations and field experiments, the relationship between control performance and sensing accuracy is captured. A fitting function method is proposed to improve the sensing accuracy without increasing the monetary cost of the system implementation. By using this method, the performance of the HTC system can be increased significantly.

Bridging between universAAL and ECHONET for smart home environment

Ambient Assisted Living (AAL) pursues the issues of how information and communication technology (ICT) is used to support the quality of life of the elderly and disabled people in smart home environment. Among the many AAL solutions, universAAL is one of the most open platforms that provides a holistic and standardized approach for an easy and economic development of AAL services. However, the compatibility with smart home networking systems that are based on ECHONET standard is not supported. Thus, this paper elucidates the bridging in between the universAAL and the ECHONET standard and thereby enable the attainment of novel AAL applications and services for ECHONET-based smart home automation systems.

Balanced Cooperative Linear Data Exchange with Physical Layer Network Coding

In this paper, we consider a group of nearby wireless end devices such as mobile phones cooperating to exchange their received packets from a common base station in order to fulfill the lost packets in other members. This problem can be solved by the linear coding in which each client transmits linear combinations of the received packets to minimize total number of transmissions. As the end devices have the limited energy resources, fairness should be a desirable property for each of them to support each other until all members in the group satisfy their needs. We introduce a cooperative algorithm that will maintain the fairness among nodes by distributing the number of transmissions they make. In this algorithm, each client changes the role of transmitter and receiver based on the information they keep in each round of data transmission. Moreover, we also incorporate physical layer network coding into this problem domain in order to further reduce the required transmission time slots and accomplish the data exchange process as quickly as possible.

Marginal Contribution-Based Distributed Subchannel Allocation in Small Cell Networks

The paper presents a game theoretic solution for distributed subchannel allocation problem in small cell networks (SCNs) analyzed under the physical interference model. The objective is to find a distributed solution that maximizes the welfare of the SCNs, defined as the total system capacity. Although the problem can be addressed through best-response (BR) dynamics, the existence of a steady-state solution, i.e., a pure strategy Nash equilibrium (NE), cannot be guaranteed. Potential games (PGs) ensure convergence to a pure strategy NE when players rationally play according to some specified learning rules. However, such a performance guarantee comes at the expense of complete knowledge of the SCNs. To overcome such requirements, properties of PGs are exploited for scalable implementations, where we utilize the concept of marginal contribution (MC) as a tool to design learning rules of players’ utility and propose the marginal contribution-based best-response (MCBR) algorithm of low computational complexity for the distributed subchannel allocation problem. Finally, we validate and evaluate the proposed scheme through simulations for various performance metrics.

A Design of Overlapped Chunked Code over Compute-and-Forward for Multi-Source Multi-Relay Networks

A physical-layer network coding approach, compute-and- forward based on nested lattice code (NLC), is considered for multi-source multi-relay networks. This paper proposes a design of overlapped chunked code (OCC) which is applied before NLC, which we call OCC/CF. Random linear network coding is applied within each chunk. Only the transmissions from the sources to the relays are considered. The design is based on the empirical rank distribution and the empirical probability distributions of the participation factor of all sources. A consecutive OCC is employed with the proposed design to investigate the performance of OCC/CF. From the numerical results, the design overhead of OCC/CF is low when the probability distribution of the participation factor is dense at chunk size for each source.