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Key research themes
1. How can energy-efficient node scheduling schemes extend wireless sensor network lifetime while ensuring QoS requirements like coverage and connectivity?
This research area focuses on designing and analyzing scheduling algorithms that selectively activate subsets of sensor nodes over time to prolong network life by conserving energy, while simultaneously maintaining essential Quality of Service (QoS) parameters such as area coverage, network connectivity, fault tolerance, and security. Node scheduling leverages sensor redundancy to minimize active nodes in each time slot without sacrificing sensing performance and communication reliability, pertinent for remote and hostile deployment environments.
Key finding: The paper proposes an energy management life-cycle model and energy conservation pyramid emphasizing node scheduling as a flexible scheme that identifies multiple disjoint sets of non-redundant sensor nodes to activate in... Read more
Key finding: This paper presents a novel distributed scheduling medium access control (DSMAC) algorithm that leverages a geometric sensor placement strategy optimizing node deployment to achieve full region coverage and network... Read more
Key finding: The authors provide a self-adjusting node scheduling approach that dynamically manages duty cycles in heterogeneous sensor networks to meet differentiated coverage requirements, ensuring adequate coverage levels per network... Read more
Key finding: This work formulates the problem of scheduling sensors with heterogeneous coverage frequency requirements per target and proposes polynomial-time approximation algorithms that minimize the maximum number of concurrently... Read more
2. How can mobile sensor scheduling optimize spatiotemporal detection performance under constraints of limited mobility and energy?
This theme investigates integrating mobile sensors into static wireless sensor networks to dynamically reconfigure sensing coverage and improve detection performance. It addresses the challenges of limited mobile node counts, constrained movement speed and distance due to battery limitations, and efficient collaboration between static and mobile nodes. Key research here develops algorithms to schedule sensor movement that minimize energy-consuming mobility costs while ensuring high detection probability, low false alarms, and bounded detection delay for mission-critical applications.
Key finding: The authors propose a data-fusion-based detection model enabling collaboration between mobile and static sensors, and develop an optimal movement scheduling algorithm that minimizes the total distance mobile sensors must move... Read more
3. What are the trade-offs and algorithmic solutions for time slot allocation and duty cycling to reduce data collisions and latency in high data-load and mobile wireless sensor networks?
This research focuses on mitigating collision-induced data loss, latency, and energy wastage in wireless sensor networks, especially under data-intensive application scenarios and with mobile sensors. It explores MAC layer scheduling approaches that assign time slots in a distributed and scalable manner, addressing mobility, network overhead, and stringent delay constraints, thereby improving throughput and packet delivery while balancing resource usage across static and moving sensor nodes.
Key finding: The paper proposes a distributed scheduling algorithm employing virtual grids and Latin Squares properties for conflict-free time slot allocation without global coordination. The method efficiently handles network mobility... Read more
Key finding: Although primarily focused on coverage, this scheduling approach also reduces the maximum concurrent active sensors, effectively alleviating contention and collisions in dense sensor deployments by controlling duty cycles.... Read more
Key finding: This work introduces a sleep scheduling method designed to reduce broadcasting delay in alarm dissemination in large-scale WSNs monitoring rare critical events. By pre-designing traffic paths and orchestrating level-by-level... Read more