Agent-based Distance Vector Routing: A Resource Efficient and Scalable approach to Routing in Large Communication Networks Page: 11
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environment from local information available at nodes. To facilitate such a
coordination, our approach exploits the stigmergetic properties of agents. Mo-
bile agents with minimum cognitive capabilities communicate with each other
using pheromones, establishing an infrastructure that assists them in assessing
their environment. Pheromones that aid the agents in population control are
referred to as Node Pheromones to distinguish them from Edge Pheromones
(see Section 3).
Whenever an agent visits a node it deposits a pheromone which is simulated
by timed tokens. The potency of the Node Pheromones is represented as de-
cay functions expressed by the equation e-A(At), where A represents the degree
of volatility of the pheromone and At is the time since the deposition of the
pheromone. Using this equation the agents can extract the value of the Node
Pheromone at a given time and calculate the inter-agent arrival time at that
node. An agent visiting a node nz at time t2 calculates the value of the Node
Pheromone that was deposited at time tl using the equation e-A(t2-tl) (see
Figure 4). If this value is above a certain Termination Threshold (T) and
the agent did not produce any routing update on nz, the agent terminates
itself. However if the Node Pheromone value has decayed below a Cloning
Threshold (Q), the agent clones itself. Before leaving nz, the agent deposits
additional Node Pheromone at time t2. This approach controls the agent pop-
ulation based on the inter-agent arrival time expressed as a function of the
Node Pheromone. If the inter-agent arrival time is small (ex(At) > 4) and
the agent produced no updates in the existing routing table entries, it implies
an excessive number of agents in the system leading to the self termination of
the agent. On the other hand, if the inter-agent arrival time is large (e-x(At)
< Q), it implies there are a sub-optimal number of agents in the system re-
sulting in agent cloning. However if Q < e-A(At) < 4, the agent neither clones
nor terminates. Terminating requires the agent to destroy its instance along
with its code and data segments. Cloning requires the agent to create an-
other instance of itself with same attributes and privileges. The volatility of
Edge Pheromones can be controlled by changing the Degree of Volatility, A
in e-x(At). Pheromones with higher values of A (Degree of Volatility) have a
higher rate of decay.
ADVR implementing a dynamic agent population may start with a single
agent or an arbitrary number of agents. Nevertheless, the agents coordinate
themselves and converge to a particular range of population. This range rep-
resents an optimal population that results in an optimal performance of the
network based on the availability of resources. This range however depends
on the values of 4, Q, and A. An adaptive system should adjust these values
dynamically based on its resource availability.
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Amin, Kaizar A. & Mikler, Armin R. Agent-based Distance Vector Routing: A Resource Efficient and Scalable approach to Routing in Large Communication Networks, article, March 25, 2002; [New York, New York]. (digital.library.unt.edu/ark:/67531/metadc111275/m1/11/: accessed September 25, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.