Evaluation of Information Distribution Algorithms of a Mobile Agent-Based Demand-Oriented Information Service System – I. Ahmed, M.J. Sadiq
ISSN 1858-1633 2005 ICTS 141
2. FADED INFORMATION FIELD ARCHITECTURE
Faded Information Field FIF Architecture has been proposed recently to optimize the service
provision parameters on the network [5]. The details of this technology can be found elsewhere; only
essential features will be reviewed here. The goal of FIF is the effective provision of information in a
network. This architecture is based on demand- oriented replication of information service to assure
service availability and utilization. In a FIF system, the information is distributed on a number of nodes in
the network rather than a localized node. The FIF architecture is depicted in Figure1. The service
providers sense the demand trend of information and the most accessed segment of that information is
allocated to a storing node. From the storing node the information service is further distributed to adjacent
nodes, however, with less information content. The process continues in a recursive fashion and the
information contents are distributed to more storing nodes away from the service provider SP. The so
called information field created by this pruning process has the following key characteristics:
• The information content stored on a node is
inversely proportional to the distance of storing node from the SP.
• Information update frequency on a storing node is inversely proportional to the distance of storing
node from the SP. Thus nodes adjacent to the SP are easily and frequently updated compared to the
nodes farther away from the SP.
Figure 1. The layout of a Faded Information Field Architecture
By allocating the most frequently accessed information to the nodes and by concentrating the
majority of the information closer to the SP, the cost of service utilization user access time and cost of
service provision information update are balanced.
The system essentially consists of logically connected nodes through which users and service
providers correspond. Mobile agents are used by both parties to acquire and provide information
respectively, under evolvingchanging situations. The mobile agents MA generated by service providers
are termed as push mobile agents Push MAs. Push MAs carry out the function of autonomous
coordination and negotiation with other nodes for information fading according to network situation and
the level of importance attached to the information. The level of importance of particular information
content is based on its popularity, determined from a high hit rate of query. The pull mobile agents Pull
MA are generated by users and they autonomously navigate in search of the required information on the
network nodes in a step by step fashion. Once the required information is located, these agents report
back to the source. The push and pull MAs have no direct correspondence with each other.
The third important subsystem of a FIF is the node itself. It is a platform for both storage of information
and program execution. It monitors the local information-based system conditions and
autonomously makes decisions for allocation requests by the SP. Each subsystem is autonomous in terms of
control to execute its operations and coordination with other nodes under evolving network conditions.
3. ALGORITHMS TO CHOOSE NODES TO CREATE THE FADED
INFORMATION FIELD
In a system with multiple faded information fields in a shared network, it is necessary to determine which
nodes in the shared network would be used by each information provider for its faded information field.
The information provider will restrict itself to these nodes. This is to avoid congestion in the network,
which would occur if each information provider were to send its push-MAs to all nodes. Also, the further the
information is from its source, the less likely it is to be updated when it becomes obsolete, resulting in less
reliability. Furthermore, if localization is determined to be advantageous, the information is more useful if it
resides near the information provider for the benefit of those users near to the provider.
It is therefore a requirement for the information provider to establish the boundary of its FIF and the
nodes therein for the distribution of information. At the same time, it must be ensured that the field of one
provider is not significantly larger than another; otherwise it would be unfair to the provider with the
smaller field, since the smaller the field, the less likely the information is to be discovered by users.
Therefore, there must be a standard field size that needs to be established. It is possible to have a central
authority restricting the field of each SP to a standard size. However, this would be against the decentralized
nature of FIFs. So, each provider must choose its own nodes, and this must be done in a fair manner.
The initial requirement is therefore that there is a standard field size, and each provider is aware of this
requirement. Among the ways of achieving this
Information Volume
FIF
SP
Network Nod
e
Information Fading Push
MA Pull MA
Information field outer
boundary
Information Gradient
Information and Communication Technology Seminar, Vol. 1 No. 1, August 2005
ISSN 1858-1633 2005 ICTS 142
standardization is to include in push-MAs a few bytes for standardization fields so that all providers, if they
desire, can find out what the others are doing. In doing so, it would regulate fairness in the faded information
field.
Therefore, some algorithms are required to choose nodes for the faded information field. In all the
following algorithms, it is assumed that the service provider is aware of all the nodes in the field, in
addition to the costs to travel to these nodes. This can be achieved by simply sending a message to any node
in the field asking for the latest information about the field. The costs are used as a measure of the distance
to the node for the purpose of creating a localized faded information field.
• Sorting – The available nodes in the field are sorted in an order by a certain cost, such as delay by
each service provider. For a field size of S nodes, it will choose the first S nodes that are closest to it in the
sorted list. It can thus determine the delay to the furthest node it requires, and imposes a travel
restriction on its push-MAs based on this delay. The push-MAs will be required to keep updating the nodes
in the field until they reach the travel restriction set by the SP. This could be in the form of travel time, or
time to live after which the MAs cease to exist. Alternatively the push-MAs can be multicast to the
required nodes in the field. The sorting technique is inherently resource intensive and it must be re-
employed to account for cost updates in the network as and when it occurs. However, the advantage is that
all the SPs are expected to have the same number of nodes in the field, since each selects the same number
of nodes from the sorted lists. • Step Size – In this case, the service provider
determines the distances of the closest and furthest nodes, and then divides that distance by the number of
nodes to get the average inter-nodal ‘hop’ distance of a push-MA. The equation for the algorithms i as
follows:
D = maxd – mind N – 1 S + mind Where D
= step
distance
d = distance from SP to node N = number of nodes
S = required field size The SP will now send push-MAs that only travel the
required distance in the field. Alternatively, the server would determine which nodes fall in the required
distance and multicast the push-MAs to those nodes. The step size must be recomputed every time there is
an update in the system; however, finding the maximum and minimum distances in the field is the
major computation, and is much faster than sorting. • Averaged Step Size – The inter-nodal distances
are likely to be skewed towards the high end in a random simulation run. In order to account for this
skewing an average distance is computed that is used to determine the step size instead. In this method, the
determination of the maximum distance is replaced by finding the total distance to all the nodes from the SP.
D = ∑d N – 1 – mind N – 1 2
S + mind Depending on geographical circumstances, an SP can
be far away from the rest of the nodes in the FIF. In this case, the computation gives an unbalanced result
because the initial distance is large. So the minimum distance is subtracted from the average to find the
inter-nodal step distance, and then added again at the end to account for the time from the SP to the first
node
• Modified Averaged Step Size – The averaged step size algorithm still gets affected by the skewing
of nodes. The algorithm was modified by computing the average step size of all the costs excluding the
minimum and maximum costs. In this method, the total distance has to be computed and the maximum
and minimum distance from the SP has to be determined. The maximum and minimum are
subtracted from the total as shown below:
D = ∑d – Nmin mind – Nmax maxd
N – 1 – Nmin – Nmax – min2d N – 1 – Nmin – Nmax 2
S – Nmin + min2d where
Nmin = number of nodes at the minimum distance
Nmax = number of nodes at the maximum distance
min2d = distance of the second closest node As mentioned in the Averaged Step Size algorithm, it
is possible that a node is very far away from the rest of the field. In order to remove this initial distance, the
minimum distance should be subtracted. However, in the Modified Averaged Step Size algorithm, the
minimum distance is not included in the computation; so instead, the distance that is second from minimum
is subtracted instead.
4. SYSTEM SIMULATIONS
