Efficient Matching of Multi-Modal Sensing Nodes for Collaborative Sense Optimization of Composite Events

Abstract

Composite events are sense maximizes collaboration through multiple sensors. Efficient matching of multi-modal sensing nodes in multi-composite events is always a thorny problem. In this paper, the composite event sensing model is first proposed, and then the collaborative-sense problem of multi-modal sensing nodes is translated into a binary matching problem. For these multi-class sensors and multi-class compound events scene, a pruning-grafting and parallel strategy be adopted, which can speed up the traversal speed and find the maximum matching edge quickly. For multi-nodes selection, the distance of the composite event constraints into binarily weighted matching. A collaborative-sense intelligent matching algorithm is suggested. It takes collaborative in various kinds of nodes matching combining with the distribution of the composite event itself around the nodes. Combined with the random distribution of various sensor nodes and composite events, the matching rate of some sensor nodes is sacrificed for the overall event efficiency. Compare to parallel algorithms, it has another effect on perceived efficiency. Finally, by comparing with other algorithms, CSSMA and other proposed algorithms have a certain advantage in the inclusive sense efficiency. In terms of composite events collaborative-sense, this work has nice theoretical significance and practical value.

Dynamic Load Balancing Algorithm Based on Optimal Matching of Weighted Bipartite Graph

“…The optimal matching of weighted bipartite graph means that each edge in the bipartite graph has a weight value, and finding a set of edges that maximizes the total weight value while ensuring that each vertex is connected to a unique edge. It is often used to solve problems such as optimal assignment of tasks [16]- [18], resource allocation [19], [20], chemical interactions [21], [22], video information summary extraction [23], data matching [24] and collaborative sense optimization of composite events [25]. The work in [22] in order to solve the alignment problem of protein-protein interaction in biological systems, the initial alignment was created using a weighted bipartite graph matching technique to calculate the similarity scores and extended to obtain the final alignment, thus obtaining more similar regions.…”

Genetic algorithm‐based partial charging schedule of rechargeable sensor networks

“…The advent of Internet of Things (IoT)‐based devices had enhanced the wide applicability of wireless sensor networks (WSNs) 1,2 apart from many applications like health monitoring systems and military and security services. The general WSN consists of a set sensors equipped with battery that may not last long enough to keep up the perpetual operation of the network.…”