Boncheol Gu

Shared-stack cooperative threads

Multithreaded sensor operating systems provide the paradigm of threads which enables programmers to program and maintain their applications more easily. However, a lot of memory space can be wasted due to the fact that a fixed-size stack is allocated for each thread. In this paper, we propose the shared-stack cooperative threads which can combine the simplicity of the multithreaded programming with the performance and scalability of event-driven systems. Our experimental results show that shared-stack cooperative threads utilize memory space more efficiently with some affordable context switching overhead for threading while providing programmers with the ease of multithreaded programming.

Energy efficient program updating for sensor nodes with flash memory

Updating sensor node programs is an essential task for maintaining stability and modifying the characteristics of wireless sensor networks. The updating mechanism must consider energy and memory efficiency, because of resource constraints of sensor nodes. In this paper, we propose a novel program updating mechanism, which considers resource constraints of sensor nodes. The proposed mechanism was designed for sensor nodes with the NOR flash memory. This is generally used to store program image. It was designed to minimize the number of flash write/erase operations, which consume a great deal of energy, and to provide wear-leveling for the NOR flash memory. We set a function as the basic unit of program updating, and partition a function into fixed-sized blocks that can be separately relocated in memory. Experimental results show that the proposed mechanism outperforms other mechanisms in terms of energy, memory and wear-leveling for flash memory.

Adaptive load balancing mechanism for server cluster

Server cluster provides high availability, scalability, and reliability by gathering server nodes into a group. Client requests need to be distributed to each server node fairly to maximize the performance of server cluster. In this paper, we propose an adaptive and efficient load balancing algorithm for the server cluster. The proposed algorithm computes the load of server nodes with the usages of computer resources and their weights. These weights are determined dynamically based on the statistics of the usages. The experimental result shows that the proposed algorithm can prevent the bottleneck of server cluster efficiently compared with existing algorithms. This guarantees its adaptability even though there are changes to the characteristic of service.

SWICOM: An SDR-Based Wireless Communication Gateway for Vehicles

A wide range of emerging and promising wireless communication protocols are rapidly being introduced into vehicles. They are commonly used for in-car infotainment, telematics, and safety applications. However, adopting new wireless communications into vehicles requires them to be equipped with the corresponding hardware devices. This hardware dependency incurs extra costs to customers to deploy and maintain wireless services in vehicles. To alleviate this problem, this paper proposes a novel wireless communication gateway for vehicles that is called the software-defined radio (SDR)-based wireless communication gateway (SWICOM). It exploits the SDR technology that uses software running on a generic hardware platform to perform signal processing instead of dedicated hardware. The SWICOM can thus integrate multiple wireless hardware devices into a single generic wireless gateway device, which improves flexibility, adaptability, and connectivity of wireless communications. We built its prototype implementation and performed measurements to quantify its run-time performance. The worst-case execution time (WCET) analysis is also given using synchronous data flow (SDF) graphs. All entire results clearly show the viability of the SWICOM.

An SDR-Based Wireless Communication Gateway for Vehicle Networks

As telematics and infotainment services are becoming more and more prevalent on the roadway, modern vehicles need to be equipped to support various wireless communication standards. The conventional ways for implementing those standards are dependent on their dedicated hardware chips, and thus in order to add a new standard or change an obsolete standard, a new dedicated hardware chip should be installed. Software defined radio (SDR) technology enables software components running on a generic hardware platform to perform signal processing instead of hardware chips. Thus, it is possible to support multi-standard, multi-band and multi-mode solutions and easy to enhance and reconfigure wireless communication. In this paper, we propose an SDR-based wireless communication gateway for vehicle networks. It integrates multiple wireless devices into one single wireless gateway reducing maintenance costs of hardware chips and improving flexibility, adaptability and connectivity of wireless communication. In order to provide the proof of concept, we present its application to digital multimedia broadcasting service.

Performance analysis of task schedulers in operating systems for wireless sensor networks

In wireless sensor networks, power is a critical resource in battery powered sensor nodes. In this respect, as it is important to efficiently utilize the limited battery power, it would be desirable to make such nodes as energy efficient as possible. Many researchers who develop operating systems of wireless sensor networks have been trying to find a way to enhance energy efficiency of sensor nodes. In this paper, we present an overview of sensor node operating systems and some of its functionalities, and then present a performance analysis of task schedulers and task-related kernel routines of existing sensor node operating systems. The results of performance analysis show some advantages and disadvantages of the existing operating systems, and based on these information, we present some possible improvements for increasing the efficiency of sensor node operating systems.

An Efficient Stack Management for Sensor Operating Systems

Operating systems for sensor networks must provide energy and memory-space efficient execution environments for applications because of the resource constraints of the sensor nodes. The shared-stack cooperative threads have been proposed to conserve stack memory-space and to minimize the possibility of stack overflow in the sensor operating systems. However, stack switching brings about external fragmentations in the stack space. Compaction may remove the fragmentation but the compaction overhead could degrade the performance. In this paper, we propose an efficient scheme to determine the compaction time of a shared-stack to reduce the number of compactions. For determining the time of a compaction, we evaluated the expected stack overflow time according to our stack model, which is based on the continuous time Markov chain. Our simulation results show that the number of compactions is greatly reduced and the lifetime of the sensor networks is increased with using our proposed scheme.

XMAS: An eXtraordinary Memory Allocation Scheme for Resource-Constrained Sensor Operating Systems

The wireless sensor networks are sensing, computing and communication infrastructures that allow us to monitor, instrument, observe, and respond to phenomena in the harsh environment. Sensor operating systems that run on tiny sensor nodes are the key to the performance of the distributed computing environment for the wireless sensor networks. Therefore, sensor operating systems should be able to operate efficiently in terms of energy consumption and resource management. In this paper, we present XMAS to improve the time and space efficiency of memory management for the sensor operating systems. XMAS was implemented on Nano-Qplus which is a multi-threading sensor operating system. Our experimental results show that the XMAS performs efficiently in both time and space compared with existing memory allocation mechanisms.

Energy Efficient Power Management for Multi-Mode Wireless Network Devices

In this paper, we analyze the network status of multi-mode wireless network devices with two different network communication modules using the Markov process. Power management is very important in wireless network devices with multiple network communication modules. We analyze the energy consumption rate of network devices according to the variation of network detection interval. We derive the optimal network detection interval by using the probabilistic analysis according to the state transition rate of networks and the energy consumption rate of network modules. We propose a heuristic network detection scheme that dynamically adjusts the network detection interval. We evaluated our scheme via simulation. The simulation results show that the energy consumption of our scheme is almost the same as that consumed in the optimal case under certain conditions.

Linked Stack Buffer Management for Shared-Stacks

Severe memory constraint of wireless sensor networks (WSN) causes lots of problems such as irrecoverable stack overflow and out-of-memory failure. These problems motivated to develop efficient memory management schemes for WSNs. A shared-stack is the memory-efficient thread stack, designed for memory-constrained environments such as WSNs. However, stack switching of shared-stacks makes external memory fragmentation, which induces memory space overhead, or CPU overhead to eliminate it. In this paper, we propose a novel stack buffer management scheme for shared-stacks, called linked stack buffer management. It manages context of threads as multiple linked stack buffers. The simulation results demonstrate that the proposed scheme alleviates external fragmentation of shared-stacks efficiently.