An Autonomous Data Gathering Scheme Adaptive to Sensing Requirements for Industrial Environment Monitoring

Review of nature-inspired methods for wake-up scheduling in wireless sensor networks

“…A self-organized approach to adaptive duty-cycling based on a response threshold model and utilizing the concepts of PBO has been proposed in [136]. It aims at systematic energy-efficient environment monitoring in the presence of changing sensing requirements, i.e.…”

“…The main reasons for using bio-inspired methods to solve wake-up scheduling problems have been their optimization capability [143,80,[87][88][89][90]94,20,14,17,105,95,129,104,98,102,100,84,79,58,74,57] that facilitates the discovery of efficient wake-up schedules; distributed nature [113,18,92,80,[87][88][89]94,14,[103][104][105]136,138,17,66,69,74,78,93,57] that well matches the topology of WSNs and allows optimization based on readily available local information; and various self-n properties, that endow the networks with greater autonomy; they include ○ self-organization [ ○ self-assembly (of services and schedules) [138,14], ○ self-healing …”

“…Other often cited attributes of nature-inspired methods important for the wake-up scheduling and synchronization tasks in WSNs are (in alphabetical order) adaptability [18,92,107,127,80,14,103,17,136,66,108,69,19,59], effectiveness [14,20,87,17,97,91,99,85,79,57], fault tolerance [103,138] (also error-tolerance), [122,69] (also delay-tolerance, error-tolerance), [19] (also accuracy-tolerance, delay-tolerance, error-tolerance), flexibility [18,[95][96][97]108,102], interactivity [18,129,19,74,57,78], reliability [14,17,104,79,86], robustness [18,…”

“…The main open issues include concurrent handling of multiple constraints, e.g. energy, network connectivity and routing strategy [84,62], or network lifetime, multi-hop connectivity, and target coverage [100], investigation of parameter sensitivity, interactions, and trade-offs [59,108,99], theoretical and experimental analyses of new scheduling methods [17,91], detailed evaluation of algorithm performance under real-world conditions [92,106,89,143,98,81,72,22], and from an applicationcentric perspective [136,143,129,66,20,22], and further general improvements of the proposed methods including generalization [17,81,19,148,137], specialization [69,106], and efficiency (e.g. parallelization [94,79]).…”

Probabilistic Control of Dynamic Crowds Toward Uniform Spatial-Temporal Coverage

“…Accordingly, the response-threshold model has the potential to solve the above problems. It has already been applied to several distributed systems to achieve self-organized control [25], [26], e.g., assignment of sensing tasks [27], routing [28], and registry service provision [29] to nodes in wireless sensor networks. It has also been used for task allocation in swarm robotic systems [30].…”