Junglok Yu

Adaptive Duty Cycle Control with Queue Management in Wireless Sensor Networks

This paper proposes a control-based approach to the duty cycle adaptation for wireless sensor networks. The proposed method controls the duty cycle through the queue management to achieve high-performance under variable traffic rates. To have energy efficiency while minimizing the delay, we design a feedback controller, which adapts the sleep time to the traffic change dynamically by constraining the queue length at a predetermined value. In addition, we propose an efficient synchronization scheme using an active pattern, which represents the active time slot schedule for synchronization among sensor nodes, without affecting neighboring schedules. Based on the control theory, we analyze the adaptation behavior of the proposed controller and demonstrate system stability. The simulation results show that the proposed method outperforms existing schemes by achieving more power savings while minimizing the delay.

Cellular-Automaton-Based Node Scheduling Control for Wireless Sensor Networks

Wireless sensor networks (WSNs) generally consist of densely deployed sensor nodes that depend on batteries for energy. Having a large number of densely deployed sensor nodes causes energy waste and high redundancy in sensor data transmissions. The problems of power limitation and high redundancy in sensing coverage can be solved by appropriate scheduling of node activity among sensor nodes. In this paper, we propose a cellular automata (CA)-based node scheduling algorithm for prolonging network lifetime with a balance of energy savings among nodes while achieving high coverage quality. Based on a CA framework, we propose a new mathematical model for the node scheduling algorithm. The proposed algorithm uses local interaction based on environmental state signaling for making scheduling decisions. We analyze the system behavior and derive steady states of the proposed system. Simulation results show that the proposed algorithm outperforms existing protocols by providing energy balance with significant energy savings while maintaining sensing coverage quality.

Self-organized node coordination scheme based on a biological inter-cell signaling system for wireless sensor networks

In this paper, we propose an energy efficient and delay guaranteed node coordination scheme inspired by biological systems, which have gained considerable attention as a computing and problem solving technique. With the identification of analogies between biological cellular signaling systems and WSN systems, we formulate a new mathematical model that considers the networking challenges of WSNs. The proposed bio-inspired scheme determines the state of the sensor node, as required by each mission-critical application and as determined by the local environmental conditions. A control analysis and simulation results show that the proposed bio-inspired scheme guarantees the system stability and provides significant energy savings, as well as reliable delay guarantees.

Automatic handover control for distributed load balancing in mobile communication networks

In this paper, we propose an auto-tuning of mobility algorithm in the mobile communication systems as a load balancing self-optimization use case. This paper presents a distributed approach in which the traffic load can be balanced systematically by utilizing the effective load information of neighboring cells. The proposed load balancing scheme detects a load imbalance in the network and resolves the problem automatically by controlling the handover parameter as a nonlinear function of the load difference. Based on control theory, we analyze the adaptive behavior of the proposed controller and derive condition for system stability. Results from asymptotic analysis and simulation indicate that the proposed local controller of each individual cell effectively achieves the global properties, such that the load difference in the network is stabilized globally within a predetermined threshold. Extensive simulation results also show that the proposed scheme outperforms the existing methods by reducing call blocking rate of the overloaded cells.

EDISON Platform: A Software Infrastructure for Application-Domain Neutral Computational Science Simulations

This paper describes the design and implementation details of the EDISON platform for computational science simulations. Along with an overview of the EDISON platform, we provide an in-depth explanation of the Science AppStore framework used to acquire application-domain neutrality and the virtualized computing resources/job management framework that provides user authentication, on-demand resources provisioning, simulation/job lifecycle control, and file input/output services, etc. To evaluate the usefulness and functionality of the EDISON platform, as a pilot study, we have applied the EDISON platform to a nano-physics service environment.

On Development of an Open Platform for High Performance Computing Services: Design of TCAD Meta-Data Schema and Its Application to Computational Nanoelectronics

Modeling researches via simulations with aid of high performance computing services (HCPS) have been intensively performed to solve various applied science and engineering problems. As a result, there has been a huge increase of the needs for HPCS platforms, which can make simulation-based research easier to be accessed by students and researchers. A HPCS platform can be composed by components such as preprocessors, technology computer-aided-design softwares (TCAD SWs), visualization tools, computing resource managers, and job schedulers. As no standardized schema to interoperate these components in HPCS platforms have been proposed so far, most of current HPCS platforms provide functionalities to support particular TCAD SWs in particular scientific areas. Here, we discuss the XML-based design of the meta-data schema that can flexibly handle various TCAD SWs in various areas, and demonstrate one example of its successful applications to science gateways, focusing on the field of computational nanoelectronics.

A Technique for Provisioning Virtual Clusters in Real-time and Improving I/O Performance on Computational-Science Simulation Environments

Computational science simulations have been used to enable discovery in a broad spectrum of application areas, these simulations show irregular demanding characteristics of computing resources from time to time. The adoption of virtualized high performance cloud, rather than CPU-centric computing platform (such as supercomputers), is gaining interest of interests mainly due to its ease-of-use, multi-tenancy and flexibility. Basically, provisioning a virtual cluster, which consists of a lot of virtual machines, in a real-time has a critical impact on the successful deployment of the virtualized HPC clouds for computational science simulations. However, the cost of concurrently creating many virtual machines in constructing a virtual cluster can be as much as two orders of magnitude worse than expected. One of the main factors in this bottleneck is the time spent to create the virtual images for the virtual machines. In this paper, we propose a novel technique to minimize the creation time of virtual machine images and improve I/O performance of the provisioned virtual clusters. We also confirm that our proposed technique outperforms the conventional ones using various sets of experiments.