Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Computer-Supported Cooperative Work: Introduction to Distributed Applications
Computer-Supported Cooperative Work: Introduction to Distributed Applications
An analog vlsi motion sensor based on the fly visual system
An analog vlsi motion sensor based on the fly visual system
Ant Colony Optimization
The Hitchhiker's Guide to Biomorphic Software
Queue - Surviving Network Attacks
Division of labor in a group of robots inspired by ants' foraging behavior
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Design patterns from biology for distributed computing
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Universality and Emergent Computation in Cellular Neural Networks (World Scientific Series on Nonlinear Science, Series a, 43)
BiSNET: A biologically-inspired middleware architecture for self-managing wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
A biologically-inspired clustering protocol for wireless sensor networks
Computer Communications
Spatial Distribution Patterns, Power Law, and the Agent-based Directed Diffusion Sensor Networks
PERCOM '08 Proceedings of the 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications
Flexible Rollback Recovery in Dynamic Heterogeneous Grid Computing
IEEE Transactions on Dependable and Secure Computing
Advances in Biologically Inspired Information Systems: Models, Methods, and Tools
Advances in Biologically Inspired Information Systems: Models, Methods, and Tools
AICI '09 Proceedings of the International Conference on Artificial Intelligence and Computational Intelligence
The Handicap Principle for Trust in Computer Security, the Semantic Web and Social Networking
WISM '09 Proceedings of the International Conference on Web Information Systems and Mining
A survey on bio-inspired networking
Computer Networks: The International Journal of Computer and Telecommunications Networking
The spatial pheromone signal for ant colony optimisation
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Markovian ants in a queuing system
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
| Hi-index | 0.00 |
Insects are the most successful group of living things in terms of the number of species, the biomass and their distribution. Entomological research has revealed that the insect sensory systems are crucial for their success. Compared to human brains, the insect central nerve systems are extremely primitive and simple, both structurally and functionally, and are of minimal learning ability. Faced with these constraints, insects have evolved a set of extremely effective sensory systems that are structurally simple, functionally versatile and powerful, and highly distributed, as well as noise and fault tolerant. As a result, in recent years insect sensory systems have been inspirational to new communications and computing paradigms, which have lead to significant advances. However, we believe that the potential for insect-inspired solutions for communications and computing is far from being fully recognized. In particular, the contrasting similarity between the ubiquitous existences of insect sensory networks in nature and the idea of pervasive computing has received little attention. For example, the chemosensory communication systems in many of the moth, ant and beetle populations are essentially ''wireless'' sensory networks. The difference between the ''wireless'' network of an insect population and an engineered wireless sensor network is that insects encode messages with semiochemicals (also known as infochemicals) rather than with radio frequencies; in addition, the computing node is the individual insect powered by its brain, sensory and neuromotor systems, rather than a microchip-powered sensor. The objectives of this paper are threefold: (1) to introduce the state-of-the art research in insect sensory systems from entomological perspectives; (2) to propose potential new research problems inspired by insect sensory system with focusing on unexplored fields; and (3) to justify how and why insect sensory systems may inspire novel computing and communications paradigms.