Biologically inspired self-governance and self-organisation for autonomic networks

Policy-constrained bio-inspired processes for autonomic route management

“…Examples of quorum sensing include the behavior of colonies of the bacterium Pseudomonas aeruginosa [35], which is responsible for urinary tract infections in the human body and colonies of the bacterium Vibrio fischeri, which is responsible for production of light within a squid. In computer science, quorum sensing based algorithms have been proposed for various applications, including agents in mobile ad hoc networks [36] and underwater sensor networks [37].…”

“…As each node n receives the H d , it de- (0, 1)) is calculated for each node on the path to the destination. Details of the normalized value calculation can be found in [37,44]. In the event that a node detects its load changing by an amount greater than or equal to the load threshold (TH U,n ), it transmits its new load value to its neighbouring nodes.…”

“…This process mimics the reaction-diffusion process that cells use to self-organise. The calculation for the load node is based on the total ratio of used and free capacity on each connected link, as specified in [37]. Based on the neighbour's normalized hop count value, the load of the link to neighbour's node, as well as its own load, each node calculates the gradient value G n,d,i?j for a link with respect to a specific destination d. (e.g.…”

A biologically inspired policy based management system for survivability in autonomic networks

“…Since the functionalities in each layer is transparent to neighboring layers, we integrate the different biological principles described in section 3 into various layers of the continuum. Our previous work has identified and applied a number of biological principles for self-management of network resources as well as QoS based route discovery [3] [4]. This paper will extend our initial mapping of biological principle to the policy continuum [10], and apply this towards network survivability.…”

Self-optimized autonomous routing protocol for wireless sensor networks with cross layer architecture

“…The area of bio-inspired network engineering has the most well known approaches as swarm intelligence (ACO, PSO), AIS and intercellular information exchange [1][2][3][4]. WSN routing algorithms based on ACO have been presented in last few years, such as [5], Sensor-driven Cost-aware Ant Routing (SC), the Flooded Forward Ant Routing (FF) algorithm, and the Flooded Piggybacked Ant Routing (FP) algorithm [6], Adaptive ant-based Dynamic Routing (ADR) [7], Adaptive Routing (AR) algorithm and Improved Adaptive Routing (IAR) algorithm [8], E&D ANTS [9].…”