SYSTEM SIMULATIONS ICTS2005 The Proceeding

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

The FIF structure was simulated using the following parameters: • A total of 50 web servers acting as service providers SPs in the FIF. • Each web servers stores between 7 and 10 categories of information out of a total of 50 categories of information at random. • Routers were generated at random using polar coordinates with maximum radius specified as 50 units. A total of 200 routers were created in the simulated information system. 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 143 Server to server costs were found using Djikstra’s algorithm [10]. Then, depending on the field determination strategy, the maximum distance that a push-MA is required to travel was found from the Djikstra costs. It was decided that the FIF of each SP should encompass only 20 of the available network, which amounts to a total of 10 nodes – each server is also a node in the FIF. The results were graphed to determine the effects of the various algorithms. Figures 2 and 3 show the effects of the algorithms on field size. The performance of the algorithms is measured using the ability to create the required field size and the fairness in creating fields for each information provider. This fairness is measured using the standard deviation of field sizes. The data is an average of several simulations runs with differing network setups. It was found, as expected, that the sorting strategy gave the required field size. The other algorithms however failed to do so, creating fields that were smaller than required. Sorting was also the fairest, but among the less processor intensive algorithms, modified averaged step size was the best, with an average field size of 7.82 and the fairest distribution of field sizes with a deviation of 2.38. Figure 2 Average Field Size Figure 3 Standard Deviation of Field Sizes It was decided to incorporate a multiplier into the algorithms to ensure the required field size. Therefore, depending on the strategy, the required field size would be multiplied by a certain number. It was expected that the algorithms would fail to create this new required size, and instead create a field that would be the actual required field size. The results are displayed in Figures 4.3 and 4.4. Figure 4 Average Field Size with Multiplier Figure 5 Standard Deviation Field Sizes with Multiplier No multiplier was used for sorting. The step size, averaged step size and modified averaged step size algorithms required multipliers of 1.16, 1.34 and 1.25 respectively. It was discovered that, not counting the sorting strategy, the modified averaged step size algorithm gave the best result of step size and fairness. Since sorting is processor intensive, the modified averaged step size algorithm was used throughout the rest of the simulation, with a multiplier of 1.25. At this stage, a list of nodes sorted by cost was generated for each provider, to be used in further stages of the simulation.

5. CONCLUSION