Communication Reliability Analysis of Wireless Sensor Networks Using Phased‐Mission Model

Abstract

Communication reliability of wireless sensor networks (WSNs) is essential to ensure the correct and reliable operation of the network. Two distinct communication paradigms exist in WSNs: infrastructure communication and application communication, and a practical communication task typically involves both types of communications. To the best of our knowledge, no reliability studies on WSNs have been dedicated to combining the two communication paradigms. In this paper, we advance the state-of-the-art by proposing a phased-mission framework to analyze the communication reliability of WSNs considering both infrastructure communication and application communication, as well as K-coverage requirements. WSNs containing two types of sensor nodes (energy harvesting sensor nodes and battery-powered sensor nodes) are modeled. Corresponding to the two types of sensor nodes, two different link reliability models are first presented. Binary decision diagram (BDD) based algorithms are then developed for the phased-mission communication reliability analysis of WSNs. Case studies are given to illustrate the application of the proposed algorithms. W ireless sensor networks (WSNs) have a wide range of application areas such as military surveillance, home security, manufacturing automation, and medical care. 1-4 All of these applications are safety-critical or life-critical which typically require a certain high level of reliability to operate effectively. Consider an application of WSNs in health care: a patient carries a set of health monitoring sensors which constitute a body WSN. These sensors collect health-related data such as temperature, heart rate, and blood pressure, and then transmit the data to the caregiver or doctor who will take prompt action depending on the patient's situation. Such life-critical WSNs are designed to monitor and handle emergency cases such as heart attack or elderly fall, where any unreliable data acquisition or transmission could result in severe consequences. To ensure reliable network operation, communication reliability analysis is necessary and essential.There are two communication paradigms of WSNs: (i) infrastructure communication which relates to the delivery of configuration and maintenance messages such as network setup, query, path discovery and etc. from the base station to the sensor nodes; (ii) application communication which relates to both acquisition of data from the physical environment and the delivery of sensed data from the sensor nodes to the base station. 5 Some research efforts have been dedicated to infrastructure communication reliability (ICR) or application communication reliability (ACR). For example, reliability metrics were proposed for infrastructure communication of WSN with hierarchical clustered topology and tree topology. 6-8 Reference 9 investigated the relationships between ICR and network properties including connectivity, average path length, and average degree. Application communication reliability of WSN was studied in. [10][11][12] However, in practice a c...

A hierarchical combinatorial reliability model for smart home systems

“…PMSs involve multiple tasks or phases during the mission, which abound in many practical applications such as aerospace, airborne weapon systems, sensor networks, and military units . A PMS often has to accomplish a different task and may be subject to different dependability requirements and environment conditions during each phase.…”

“…PMSs involve multiple tasks or phases during the mission, which abound in many practical applications such as aerospace, airborne weapon systems, sensor networks, and military units. [8][9][10] A PMS often has to accomplish a different task and may be subject to different dependability requirements and environment conditions during each phase. Thus, the system configuration, failure or success criteria, and component failure behavior can be dynamic from phase to phase, which makes the reliability analysis of PMSs difficult.…”

Efficient Mincuts Identification for Phased-Mission Systems

“…Thus, the system configuration, failure criterion, and/or component failure behavior can change from phase to phase. Many practical systems are actually PMSs, for example, aircrafts [3], wireless sensor networks [4], unmanned aerial vehicles [5], series systems with standby components [6], etc.…”

Fault Prediction Method for Wireless Sensor Network Based on Evidential Reasoning and Belief-Rule-Base

“…As an essential part of the Internet of Things, WSN is widely used in environmental monitoring, disaster warning, medical health, space exploration, and intelligent agriculture [2]. However, a large number of abnormal data are generated by WSN faults, which seriously affects the validity of the WSN data fusion [3].…”