Group-based discovery in low-duty-cycle mobile sensor networks

Abstract

Abstract-Wireless Sensor Networks have been used in many mobile applications such as wildlife tracking and participatory urban sensing. Because of the combination of high mobility and low-duty-cycle operations, it is a challenging issue to reduce discovery delay among mobile nodes, so that mobile nodes can establish connection quickly once they are within each other's vicinity. Existing discovery designs are essentially pair-wise based, in which discovery is passively achieved when two nodes are pre-scheduled to wake-up at the same time. In contrast, for the first time, this work reduces discovery delay significantly by proactively referring wake-up schedules among a group of nodes. Because proactive references incur additional overhead, we introduce a novel selective reference mechanism based on spatiotemporal properties of neighborhood and the mobility of the nodes. Our quantitative analysis indicates that the discovery delay of our group-based mechanism is significantly smaller than that of the pair-wise one. Our testbed experiments using 40 sensor nodes confirm our theoretical analysis, showing one order of magnitude reduction in discovery delay compared with traditional pair-wise methods with only 0.5%∼8.8% increase in energy consumption.

Survivability in Time-Varying Networks

“…Examples of such predictable topology changes include those in a space communication network with known orbits [3], [4], in a mobile social network consisting of students who share fixed class schedules [15], in a low-duty-cycle sensor network with periodic sleep/wake-up patterns [11], [12], in a whitespace network with planned channel reclamation [7], [8], in a mmWave network with scheduled beam steering [10], etc. In contrast, unpredictable topology changes (also referred to as failures in this paper) include those caused by unexpected shadowing, unscheduled channel reclamation, hardware malfunctions, etc.…”

“…2 In a mmWave network with tunable directional antennas, the network topology could vary with the dynamic adjustment of beam directions. tours and schedules; in low-duty-cycle sensor networks [11], [12], the sleep/wake-up pattern is periodic and can be predicted accurately; in whitespace networks, the states of secondary links in the next few hours can be known a prior by using the whitespace database [13]; a recent study [14] also shows that human mobility has 93% potential predictability. In contrast, the other type of interruptions are extrinsic and unpredictable.…”

Service-oriented middleware for large-scale mobile participatory sensing

“…We aim with our approach to limit the participation of mobile devices in participatory sensing tasks, in a manner that does not jeopardize the quality of the measurements. Existing works in the sensing domain have already applied this idea through duty cycling techniques, or device selection techniques where only some devices provide their sensing services while others sleep [14,27]. However, duty cycling techniques are actually complementary to our work as they apply more to the look-up phase since devices are already known to the network.…”

An Eliminating Method to Improve Localization Accuracy

“…Assumption 3. Every node can find its neighbors by utilizing the neighbor discovery algorithm [15,16].…”