Securing Fresh Data in Wireless Monitoring Networks: Age-of-Information Sensitive Coverage Perspective

Abstract

With the development of IoT, the sensor usage has been elevated to a new level, and it becomes more crucial to maintain reliable sensor networks. In this paper, we provide how to efficiently and reliably manage the sensor monitoring system for securing fresh data at the data center (DC). A sensor transmits its sensing information regularly to the DC, and the freshness of the information at the DC is characterized by the age of information (AoI) that quantifies the timeliness of information. By considering the effect of the AoI and the spatial distance from the sensor on the information error at the DC, we newly define an error-tolerable sensing (ETS) coverage as the area that the estimated information is with smaller error than the target value. We then derive the average AoI and the AoI violation probability of the sensor monitoring system, and finally present the η-coverage probability, which is the probability that the ETS coverage is greater than η ratio of the maximum sensor coverage. We also provide the optimal transmission power of the sensor, which minimizes the average energy consumption while guaranteeing certain level of the η-coverage probability. Numerical results validate the theoretical analysis and show the tendency of the optimal transmission power according to the maximum number of retransmissions. This paper can pave the way to efficient design of the AoI-sensitive sensor networks for IoT.

Efficient Sensor Scheduling Strategy Based on Spatio-Temporal Scope Information Model

“…• ∆t. The area distribution of D that can be obtained from Equation (25) is shown in the shaded part of Figure 2a. The remaining blank areas are where new information increments can be obtained, that is, the set D .…”

“…In [ 22 , 23 ], a mutual-information based Value of Information (VoI) framework is formalised to characterise how valuable the status updates are for Hidden Markov Models. An error-tolerable sensing (ETS) coverage, as the area where the estimated information is and with a smaller error than the target value, is defined in [ 24 , 25 ]. The performance of state updates is studied in [ 26 , 27 ], where the status is modeled as a time-varying Gauss–Markov Random Field (GMRF), and the estimation error is analyzed.…”