Sangho Yi

PEACH: Power-efficient and adaptive clustering hierarchy protocol for wireless sensor networks

The main goal of this research is concerning clustering protocols to minimize the energy consumption of each node, and maximize the network lifetime of wireless sensor networks. However, most existing clustering protocols consume large amounts of energy, incurred by cluster formation overhead and fixed-level clustering, particularly when sensor nodes are densely deployed in wireless sensor networks. In this paper, we propose PEACH protocol, which is a power-efficient and adaptive clustering hierarchy protocol for wireless sensor networks. By using overhearing characteristics of wireless communication, PEACH forms clusters without additional overhead and supports adaptive multi-level clustering. In addition, PEACH can be used for both location-unaware and location-aware wireless sensor networks. The simulation results demonstrate that PEACH significantly minimizes energy consumption of each node and extends the network lifetime, compared with existing clustering protocols. The performance of PEACH is less affected by the distribution of sensor nodes than other clustering protocols.

Adaptive page-level incremental checkpointing based on expected recovery time

Incremental checkpointing, which is intended to minimize checkpointing overhead, saves only the modified pages of a process. This means that in incremental checkpointing, the time consumed for checkpointing varies according to the amount of modified pages. Thus, an efficient interval of checkpointing have to be determined on run-time of a process. In this paper, we present an efficient and adaptive page-level incremental checkpointing facility that is based on the interval determination mechanism for minimizing the expected execution time. Our simulation results show that the expected execution time was significantly reduced compared with existing periodic page-level incremental checkpointing.

Space-efficient page-level incremental checkpointing

Incremental checkpointing, which is intended to minimize checkpointing overhead, saves only the modified pages of a process. However, the cumulative size of incremental checkpoints increases at a steady rate over time because many updated values may be saved for the same page. In this paper, we present a comprehensive overview of Pickpt, which is a page-level incremental checkpointing facility. Pickpt provides space-efficient techniques for minimizing the use of disk space. For our experiments, the results show that the use of disk space of Pickpt was significantly reduced compared with existing incremental checkpointing.

SensorMaker: A Wireless Sensor Network Simulator for Scalable and Fine-Grained Instrumentation

Nowadays, wireless sensor networks have drawn great attention as a new and important research area. These sensor networks typically consist of hundreds or even thousands of sensor nodes deployed in a geographical region to sense events. Therefore, using actual sensor networks in case of developing a new scheme or experimenting functionalities may consume too much time and cost. In this paper, we present a SensorMaker, which is a simulator for wireless sensor networks. It supports scalable and fine-grained instrumentation of the entire sensor networks. We also present the actual simulation results of the various existing routing and clustering algorithms, and network management schemes.

Energy aware routing with dynamic probability scaling

The goal of energy aware routing algorithms is to increase the lifetime and long-term connectivity of the wireless sensor networks. However, most of those algorithms do not use the newest states of nodes for retrieving routing information. In this paper, we propose an efficient energy-aware routing algorithm for wireless sensor networks. In our algorithm, the energy drain rate and residual energy of each sensor node are used for selecting candidate routes. Information is retrieved with energy awareness per almost every communication. Simulation results show that our approach outperforms the previous works with respect to long term connectivity by as much as 30%.

Adaptive mobile checkpointing facility for wireless sensor networks

In wireless sensor networks, many kinds of failures may arise on sensor nodes because the nodes can be deployed and used even in harsh environments. Therefore, fault-tolerance mechanisms are needed for the wireless sensor networks have to maintain stability and normal operation of the networks. In this paper, we propose an adaptive mobile checkpointing mechanism for wireless sensor networks that gives fault-tolerance for the networks. It is a yet another checkpointing mechanism based on the diskless checkpointing which does not use stable storage but uses the redundant memory space of neighboring nodes. Our experimental results show that the lifetime and stability of sensor networks was dramatically increased compared with the case when the proposed mechanism was used or not.

EAR-RT: energy aware routing with real-time guarantee for wireless sensor networks

Most energy aware routing algorithms focus on the increasing the lifetime and long-term connectivity of the wireless sensor networks. But energy efficiency sacrifices the communication delay between source and sink node. Therefore, many researchers have mentioned of energy and delay trade-offs. But the delay was not the main concern. In this paper we propose EAR-RT, an real-time guaranteed routing protocol for wireless sensor networks without harming energy awareness. Simulation results show that our real-time routing algorithm provides real-time guaranteed delivery while network is stable.

An efficient dynamic memory allocator for sensor operating systems

Dynamic memory allocation mechanism is important aspect of operating system, because an efficient dynamic memory allocator improves the performance of operating systems. In wireless sensor networks, sensor nodes have miniature computing device, small memory space and very limited battery power. Therefore, sensor operating systems should be able to operate efficiently in terms of energy consumption and resource management. And the role of dynamic memory allocator in sensor operating system is more important than one of general operating system. In this pager, we propose new dynamic memory allocation scheme that solves problems of existing dynamic memory allocators. We implement our scheme on Nano-Qplus which is a sensor operating system base on multi-threading. Our experimental results show our scheme performs efficiently in both time and space compared with existing memory allocation mechanism.

Adaptive Multilevel Code Update Protocol for Real-Time Sensor Operating Systems

In wireless sensor networks each sensor node has very limited resources, and it is very difficult to find and collect them. For this reason, updating or adding programs in sensor nodes must be performed via a communication channel at run-time. Many code update protocols have been developed for sensor networks, ranging from function-level update to full-image replacement. However, they provide only a fixed level of code update protocols. These protocols require manual selection of an appropriate protocol because they do not consider a cost analysis of the update protocols. In addition, they do not consider real-time response while updating codes. In this paper, we present an adaptive multilevel code update protocol (AMCUP) for real-time sensor operating systems. AMCUP enables energy-efficient code update via support for multilevel protocols (i.e., full-image, module-level, function-level, and instruction-level). It adaptively selects a protocol which meets deadline of applications and consumes less energy based on a cost analysis of several protocols. Our simulation and experimental results show that AMCUP can reduce energy consumption and execution time compared with existing single-level code update protocols while meeting deadline of the running applications.

Molecule: An adaptive dynamic reconfiguration scheme for sensor operating systems

In wireless sensor networks, sensor nodes are located on remote-site and thus it is very difficult to re-gather them. To update or add a program at run-time of the sensor nodes, sensor operating system must support a dynamic reconfiguration. Many kinds of different mechanisms for reconfiguring sensor nodes have been developed ranging from full image replacement to virtual machines. In previous schemes, dynamic linker supports only indirect linking between modules, and the linking is performed on the sensor nodes. Those may increase overhead of the execution time and energy consumption. In this paper, we present an adaptive and dynamic reconfiguration scheme called Molecule for sensor nodes. In Molecule, applications, kernel features, and device drivers are managed as a form of module. By using the cost analysis of the expected execution time of each module, Molecule selects an appropriate method between direct and indirect linking to link modules. It also supports remote linker to exclude the linking overhead from the sensor nodes. Our experimental results show that Molecule performs efficiently in terms of the energy consumption and execution time compared with the existing dynamic reconfiguration schemes.