Biologically Inspired Self-Governance and Self-Organisation for Autonomic Networks

Abstract

The current complexity of network management has crucial requirements towards achieving autonomic capabilities helped drive the need for autonomic capabilities. The vision of are self-knowledge, self-organisation and self-governance. autonomic network management provides the ability for network Self-knowledge provides the ability to learn from experience devices to cooperatively self-organise and self-govern in the and reason when confronted with choice; self-organisation support of high level business goals. These principles are inspired enables extensibility by combining simple, manageable by biological systems. In this paper, we propose key selfcomponents into more complex collections; self-governance organisation and self-governance techniques that are drawn from ensures that business goals drive networks and services principles of molecular biology including (i) blood glucose supplied at any given time. The approach we have taken is to homeostasis, (ii) reaction diffusion like principles, (iii) microorans moilt usn chmtai tehius an.v employ a number of biological analogies and principles that organism mobility using chemotaxis techniques, and (iv) can use these three capabilities to collectively support the hormone signaling. Preliminary simulation results have also been can uthese systeInpparti culletive sedpon presented to validate our model. vision of autonomic systems. In particular we have focused on the principles from micro-biology [3], which includes (i) the use of blood glucose homeostasis techniques to achieve overall

On Swarm Intelligence Inspired Self-Organized Networking: Its Bionic Mechanisms, Designing Principles and Optimization Approaches

“…Enormous security mechanisms have already been studied in various systems to combat malicious attack, node failure, and other kinds of threats [86]. Among those techniques, the most well-known bio-inspired approaches are AIS and intercellular information exchange (e.g., Molecular biology) [87].…”

“…An application of AIS based distributed node and rate selection in sensor networks has been proposed in [93], in which sensor networks and their capabilities (e.g., their transmission rate) are modelled as antigens and antibodies. AIS has also shown brilliant results for misbehavior detection and helps in designing and implementing the security framework in WSNs [87]. Furthermore, a bio-inspired secure autonomous routing mechanism called "BIOSARP", which is based on ACO routing algorithm, has also been proposed for WSNs to treat the attack issues successfully [94].…”

Model Checking the Ant Colony Optimisation

“…In [14], the authors present bio-inspired techniques for selforganisation and self-governance for autonomic networks. Simulation is used to analyse properties like traffic-and node-load and the amount of bandwidth in each route in the network (self-management of resources).…”

Notice of Violation of IEEE Publication Principles - An efficient Adaptive multi-hop routing protocol to avoid congestion for Wireless Sensor Networks

“…Towards this vision, it is observed that various biological principles are capable to overcome the adaptability problems. The area of bio-inspired network engineering has the most well known approaches which are swarm intelligence (ANT Colony, Particle swarm), AIS and intercellular information exchange (Molecular biology) [2][3][4][5]. WSN routing algorithms 978-1-4244-7968-9/10/$26.00 ©2010 IEEE 315 based on ACO have been presented in last few years, such as [6], Sensor-driven Cost aware Ant Routing (SC), the Flooded Forward Ant Routing (FF) algorithm, and the Flooded Piggybacked Ant Routing (FP) algorithm [7], Adaptive ant based Dynamic Routing (ADR) [8], Adaptive Routing (AR) algorithm and Improved Adaptive Routing (IAR) algorithm [9], E&D ANTS [10].…”

“…It is not clear whether they can be directly applied to WSNs with 316 multipath routing enabled. Moreover, most of the protocols deal with homogeneous traffic [2]. Earlier routing schemes for sensor networks involve direct communication protocols which facilitate direct communication between the source node and the base station [6].…”