Yunseong Lee

User-friendly demand side management for smart grid networks

Demand side management (DSM) is an important technique for demand response (DR) system in smart grid networks. The DSM techniques traditionally have focused on minimizing electricity bill or peak load. More recent work reveals that users wish to reduce their electricity bills without sacrificing user convenience. Hence, waiting time has been introduced to reflect the user comfort for the DSM. Residents usually preferred that finish their work as soon as possible than less waiting time. These techniques have not taken previous usage pattern consideration, thus have been limited for use in home appliances. In this paper, we propose a system architecture and an algorithm for DSM referred to as user-friendly DSM (UDSM) using ICT. The UDSM is based on time-varying price information considering the following three-fold factors: electricity bill, usage pattern, and rebound peak load. Our proposed algorithm is divided into two steps. In the first step, we formulate the objective function based on electricity bill and usage pattern, and we minimize the electricity bill and maximize the usage similarity. Then, as the second step, we apply a load balancing algorithm to avoid blackout and to minimize rebound peak load. Our algorithm is tested in a real data from Jeju Islands smart grid test site, and experimental results validate the proposed DSM scheme shifts the operation to off-peak times and consequently leads to significant electricity bill saving and user satisfaction ratio.

RETE-ADH: An Improvement to RETE for Composite Context-Aware Service

We propose a new pattern matching algorithm for composite context-aware services. The new algorithm, RETE-ADH, extends RETE to enhance systems that are based on the composite context-aware service architecture. RETE-ADH increases the speed of matching by searching only a subset of the rules that can be matched. In addition, RETE-ADH is scalable and suitable for parallelization. We describe the design of the proposed algorithm and present experimental results from a simulated smart office environment to compare the proposed algorithm with other pattern matching algorithms, showing that the proposed algorithm outperforms original RETE by 85%.

Fully-distributed multicast routing protocol for IEEE 802.15.8 peer-aware communications

IEEE 802.15 task group 8 (IEEE 802.15.8) has been recently chartered to define PHY and MAC mechanism for wireless personal area networks (WPAN) peer aware communications (PAC) optimized for peer to peer and infrastructureless communications with fully distributed coordination. The most promising services created by IEEE 802.15.8 would be multicast communication with simultaneous membership in multiple groups, typically up to 10, in dense network topology. Most existing multicast techniques in mobile ad hoc networks (MANET) have relied upon a central coordinator to manage its multicast group and thus cannot be used for fully-distributed PAC networks. In this paper, we propose a graph-based multicast routing protocol referred to as fully-distributed multicast routing protocol (FDMRP) for IEEE 802.15.8 PAC networks. The FDMRP minimizes routing table entries and thus reduces control message overhead for its multicast group management. To balance the control message, all nodes in the network have a similar number of routing entries to manage nodes in a same multicast group. To measure the effectiveness of the proposed FDMRP against the ODMRP [10], we evaluated performance by OPNET simulator. Performance evaluation shows that the FDMRP shows less control message overhead and multicast group join latency than the ODMRP.

Pattern-Identified Online Task Scheduling in Multitier Edge Computing for Industrial IoT Services

In smart manufacturing, production machinery and auxiliary devices, referred to as industrial Internet of things (IIoT), are connected to a unified networking infrastructure for management and command deliveries in a precise production process. However, providing autonomous, reliable, and real-time offloaded services for such a production is an open challenge since these IIoT devices are assumed lightweight embedded platforms with limited computing performance. In this paper, we propose a pattern-identified online task scheduling (PIOTS) mechanism for the networking infrastructure, where multitier edge computing is provided, in order to handle the offloaded tasks in real time. First, historical IIoT task patterns in every timeslot are used to train a self-organizing map (SOM), which represents the features of the task patterns within defined dimensions. Consequently, offline task scheduling among edge computing-enabled entities is performed on the set of all SOM neurons using the Hungarian method to determine the expected optimal task assignments. In real-time context, whenever a task arrives at the infrastructure, the expected optimal assignment for the task is scheduled to the appropriate edge computing-enabled entity. Numerical simulation results show that the proposed PIOTS mechanism overcomes existing solutions in terms of computation performance and service capability.

Fully distributed multicast routing protocol for IEEE 802.15.8 peer-aware communication

The IEEE 802.15.8 provides peer-aware communication (PAC) protocol for peer-to-peer infrastructureless service with fully distributed coordination. One of the most promising services in IEEE 802.15.8 is group multicast communication with simultaneous membership in multiple groups, typically up to 10 groups, in a dense network topology. Most of the existing multicast techniques in mobile ad hoc networks (MANET) have significant overhead for managing the multicast group and thus cannot be used for fully distributed PAC networks. In this paper, we propose a light-weight multicast routing protocol referred to as a fully distributed multicast routing protocol (FDMRP). The FDMRP minimizes routing table entries and thus reduces control message overhead for its multicast group management. To balance the control message, all nodes in the network have a similar number of routing entries to manage nodes in the same multicast group. To measure the effectiveness of the proposed FDMRP against the existing schemes, we evaluated performance by OPNET simulator. Performance evaluation shows that the FDMRP can reduce the number of routing entries and control message overhead by up to 85% and 95%, respectively, when the number of nodes is more than 500.

Coexistence scheme of licensed-assisted access using long-term evolution and wireless local area network for wireless sensor networks:

Wireless sensor networks have continuously evolved to provide better services and satisfy user demands. Through this, the number of wireless sensors and the amount of mobile traffic are exponentially growing every year. Long-term evolution technology can effectively resolve the problems caused by traffic growth; however, there are still limitations. Licensed-assisted access using long-term evolution technology has greatly improved the performance of existing long-term evolution heterogeneous networks with carrier aggregation. However, the existing wireless local area network sensor nodes remain a challenge. The licensed-assisted access using long-term evolution access point should efficiently handle the problem of monopolizing spectrum resources used by existing wireless local area network sensor nodes. In this article, we investigate an optimized time slot allocation technique for the coexistence of wireless local area network and licensed-assisted access using long-term evolution sensor nodes. In order to maximize the throughput of each wireless local area network and licensed-assisted access using long-term evolution sensor node in the proposed algorithm, we designed an objective function based on the number of wireless local area network/licensed-assisted access using long-term evolution sensor nodes and the queue size of each sensor, after which we developed the optimal parameters using Karush–Kuhn–Tucker conditions. Through extensive simulations, we show that the proposed scheme can significantly outperform the other existing techniques with respect to the throughput, channel utilization, delay, and transmission fairness.

Dynamic decision-making for fine-grained energy-efficient control in millimeter-wave access platforms

This paper proposes a dynamic decision-making algorithm that controls power allocation for minimizing time-average energy expenditure in millimeter-wave (mmWave) modular antenna array (MAA) networking platforms. In the reference networking system, multiple MAA modules exist and each MAA module consists of multiple elements; and the proposed algorithm dynamically allocates powers to the elements in MAA depending on the queue-backlog sizes in terms of the joint optimization of time-average energy-efficiency and queue stability.