Grid Computing: A Desirable Tool for Electronic Governance

This paper explained how Government at different levels can apply Information and Communication Technology (ICT) to achieve efficiency, effectiveness, transparency and accountability in Government to Government (G2G), Government to Employee (G2E), Government to Citizen (G2C) and Government to Business (G2B).    This application is referred to as Electronic Governance (e-Governance).   The system enables citizens to make best use of automated administration processes that are accessible on-line.   Grid computing is an ideal solution to this type of administrative processes.  This paper therefore presents how Grid computing can be used to effectively and efficiently meet the yearnings of citizenry. In this paper, we demonstrated the creation of a virtual environment by using Grid technologies to a specific e-governance application on distributed resources.  We presented a framework for the adoption of grid computing for e-governance management using Electronic Bill server (EB server), Comprehensive Welfare and Social Services server (CWSS server) and Corporation sever (C server).  Experiments were run with the Grid environment and without Grid environment by considering the number of jobs completed and the period to complete various jobs submitted for processing using MATLAB. The number of jobs completed by EB server by using Grid: are 20, 40, 60, 80,100 and 120 while 15, 25, 33, 60, 72 and 90 were completed without Grid under the same condition.  The numbers of jobs completed by CWSS server with Grid are: 30,50,70,90,120 and 130 while 22.5, 37.5, 52.5, 67.5 90 and 97.5 were completed without Grid.   The numbers of jobs completed by Corporation server under Grid are: 30,50,70,90,120 and 130 while 24, 40,56,72,96 and 104 were completed without Grid.   The period to complete various jobs submitted for processing by the EB serve under Grid are: 18,30, 42,54,72 and 88minutes while 30,50,70,90,120 and 130minutes were required without Grid.     For CWSS server, the period to complete various jobs submitted for processing under Grid are: 6.5.19.5,32.5,45.5,58.5,78 and 84.5 minutes while 10, 30,50,70,90,120 and 130minutes  were required without Grid.  For Corporation server, the period to complete various jobs submitted for processing under Grid are:  6.4,19.2,32,44.8,57.6, 76.8 and 82.2minutes while 10,30,50,70,90 120, and 130minutes were required without Grid. The result of simulation revealed that implementing an e-Governance solution was cost effective, efficient, consistent and reduced job processing time with high quality of result and providing better services to citizens. Key words: E-Governance, Grid Applications, Grid Computing, Grid environment, Grid Infrastructure and Grid Resource Broke

Computational Numerical Solution for Traveling Salesman Problem

This paper examined and analysed the desire of Traveling Salesman Problem (TSP) to find the cheapest way of visiting all given set of cities and returning to the starting point.     We presented a unique decomposition approach model for TSP in which the requirements and features of practical application in communication network, road transportation and supply chains are put into consideration.  We used a Mathematical Modeling solution with the application of Ant Colony Search Algorithm (ACSA) approach for result computation. In our approach, different Agents were created for difference purposes.   Information agent gathered information about best tour and detected the solution agent that arrived at a given point with information message containing details of where the solution agent has come from as well as best tour cost.  The place ant performs local pheromone decay on the relevant links.   This help to avoid random visit to irrelevant edges and allows the place ant to calculate the cost of tour of all place ants including the latest pheromone level on the links to each of the place ants. The solution agent uses available information to decide  which node to visit next and informs the place ant of  its decision to move to a given destination and update better tour  previously sampled while information about where to go next also obtained.       The place ant updates its pheromone value for that link using the equivalent of the algorithm for local pheromone update.    The cycle continues until solution agent arrives at its destination. The main advantage of our approach is that it permits the use of mixed integer programming and combinatorial optimization techniques to compute real optimal routing path, solving the problem in practice by returning actual shortest route with its numerical value and not the best effort result as provided by some previous models and analytical methods. The implementation was carried out using C# programming language.  Data used were generated and the performance evaluation of the model was carried out through simulation using Matlab 7.0.  The result shows that by considering all possible paths between a node as the source and another as the destination, all possible routes for a particular journey with shortest route in each case were generated. Keywords: Ant Colony, Combinatorial Optimization, Mixed Integer Programming, Pheromone, Search Algorithm and Traveling Salesman