A Robust and Space-Efficient Stack Management Method for Wireless Sensor Network OS with Scarce Hardware Resources

Abstract

Due to such requirements as low power consumption and low cost, sensor nodes commonly do not include advanced H/W features. The absence of the features such as the memory management unit enforces several tasks to share a memory address domain on a small data memory space (1∼16 KB). It exposes each task to the stack overflow causing the corruption of other memory areas. In this paper, we propose a robust and efficient stack memory management method (RESM) that dynamically assigns and releases a preestimated amount of stack memory to each function call at runtime. RESM maintains the stack memory usage with the similar amount of the stack usage that the system actually requires, and the stack memory area of each task is individually protected from corruption by the stack overflow. RESM can also anticipate a saturated condition in data memory at runtime. When the memory state is unsafe from the saturated condition, it conditionally allows function calls to operate tasks without any memory fault by using the proposed function call deferring algorithm. From the analytical and experiment results, it is proven that the performance of RESM outperforms the other mechanisms and RESM can provide more robust stack operation environment.

Towards Efficient Stabilizing Code Dissemination in Wireless Sensor Networks

“…Some of these faults lead to transient memory corruptions [41]. There have been several works done that are tolerant to transient memory faults or present memory protection mechanisms from some actions that lead to this type of faults [42,43,44,45]. Recently, as reported in [9], transient faults have occurred with a probability of approximately 0.1% in a large scale deployment and such transient faults severely impact on the efficiency of the protocols.…”

Design Considerations of Self-Adaptive Wireless M2M Network Communication Architecture

“…In the traditional methods, the paper [22] proposed using a two-dimensional Markov chain model for modeling wireless network. By the steady-state calculation of Markov chain model, transmission probability of nodes and transmit data collision probability were obtained in any slot, which lead to major system performance indicators: saturation throughput.…”

“…Saturated and unsaturated conditions network experiments have been designed in a part of system test [22]. The simulation experiments show that the adaptive network architecture can be well mapped to traditional wireless M2M network protocols, including packet distribution, packet collection, and mesh routing.…”

An Overview of Memory Provisioning in Real-Time Wireless Sensor Networks

“…In Kim et al (Kim, Kim, & Eom, 2012) an efficient stack memory management method (RESM) is proposed which releases a preestimated amount of stack memory to each function call at runtime. As a priority of an OS is to deliver reliable execution of applications on motes that usually operate unattended for long periods of time, RESM is proposed to be in a position to maintain the stack memory usage as well as the required stack memory of an executing application.…”

“…For example three tasks simultaneously called i.e. in a multi-threaded application then three stack box allocations will be delivered (Kim, Kim, & Eom, 2012).…”