Design and Implementation of Mobile Map Application for Finding Shortest Direction between Two Pair Locations Using Shortest Path Algorithm: A Case Study

Int. J. Advanced Networking and Applications
Volume: 09 Issue: 01 Pages: 3300-3305 (2017) ISSN: 0975-0290
3300
Design and Implementation of Mobile Map
Application for Finding Shortest Direction
between Two Pair Locations Using Shortest Path
Algorithm: A Case Study1
Akinwol Agnes Kikelomo., 2
Yekini Nureni Asafe., 3
Adelokun Paul., 4
Lawal Olawale N
1,3,4
Department of Computer Technology, Yaba College of Technology, Yaba.
2
Department of Computer Engineering, Yaba College of Technology, Yaba.
-------------------------------------------------------------------ABSTRACT---------------------------------------------------------------
The shortest path problem is an approach towards finding the shortest and quickest path or route from a starting
point to a final destination, four major algorithms are peculiar to solving the shortest path problem. The
algorithms include Dijkstra’s Algorithm, Floyd-Warshall Algorithm, Bellman-Ford Algorithm and Alternative
Path Algorithm. This research work is focused on the design of mobile map application for finding the shortest
route from one location to another within Yaba College of Technology and its environ. The design was focused on
Dijkstra’s algorithm that source node as a first permanent node, and assign it 0 cost and check all neighbor nodes
from the previous permanent node and calculate the cumulative cost of each neighbor nodes and make them
temporary, then chooses the node with the smallest cumulative cost, and make it as a permanent node. The
different nodes that lead to a particular destination were identified, the distance and time from a source to a
destination is calculated using the Google map. The application then recommends the shortest and quickest route
to the destination.
Keywords: Map, Mobile map, Dijkstra’s Algorithm, Floyd-Warshall Algorithm, Bellman-Ford Algorithm, Alternative
Path Algorithm, Shortest path problem
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Date of Submission: July 19, 2017 Date of Acceptance: July 26, 2017
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1. INTRODUCTION
A map is a visual representation of an entire area or
a part of an area, typically represented on a flat surface.
The work of a map is to illustrate specific and detailed
features of a particular area, most frequently used to
illustrate geography. There are many kinds of maps; static,
two-dimensional, three-dimensional, dynamic and even
interactive. Maps attempt to represent various things, like
political boundaries, physical features, roads, topography,
population, climates, natural resources and economic
activities [1].A map is useful for both a layman and an
intelligent person, as maps contain loads of information. It
is up to an individual how he makes use of it. Maps are
generally used for: Analysis; Confirmation,
Communication, Decoration, Collection, Investment,
Exploration, Hypothesis Stimulation Navigation, Control
& Planning, Map Reading, Storage of Information,
Historical perspective [2].
Some maps are created with very specific goals in
mind. The focus of this research work is to create a map
for to determine shortest path between two locations on a
map. The study is to use the graph theory to develop
mobile map for Yaba College of Technology campus
using shortest path algorithm to determine the shortest and
fastest route from source to destination. In Yaba College
of Technology, there is no provision of map used for
locating buildings within the school campus. The school
only provide the map to specify route that leads to various
buildings in the college. The process is manual which is
time consuming and sometime lead to frustration for first
time visitors and others. Different route can lead to a
particular location within the college. This route has
different distance that they cover and can be difficult to
choose the exact route if one is not familiar with the
school environment. The research work is to achieve the
following objectives: to discover the shortest route from a
particular source to a destination, and to design a model
for shortest path and implement the model designed.
2. LITERATURE REVIEW
2.1. Graph and its Application
Graph is a diagram (as a series of one or more points,
lines, lines segments, curves, or areas) that represents the
variation of a variable in comparison with that of one or
more other variables. It is also the collection of all points
whose coordinates satisfy a given relation (as a function).
Graph is a collection of vertices and edges that pairs of
vertices [3].
2.2. Types of Graph
There are various types of graphs depending upon the
number of vertices, number of edges, interconnectivity,
and their overall structure. Graph types can fall into any of
the following types: Null Graph: A graph having no edges;
Trivial Graph: A graph with only one vertex;Non-Directed
Graph: A non-directed graph contains edges but the edges
are not directed ones;Directed Graph: In a directed graph,

3301
each edge has a direction;Simple Graph: A graph with no
loops and no parallel edges; Connected Graph: A graph G
is said to be connected if there exists a path between every
pair of vertices; Disconnected Graph: A graph G is
disconnected, if it does not contain at least two connected
vertices;Regular Graph: A graph G is said to be regular, if
all its vertices have the same degree. In a graph, if the
degree of each vertex is ‘k’;Complete Graph: if a vertex is
connected to all other vertices in a graph;Cycle Graph: If
the degree of each vertex in the graph is two;Cyclic
Graph: A graph with at least one cycle;Acyclic Graph: A
graph with no cycles;Bipartite Graph: A simple graph G =
(V, E) with vertex partition V = {V1, V2} is called a
bipartite graph if every edge of E joins a vertex in V1 to a
vertex in V2;Complete Bipartite Graph: A bipartite graph
‘G’, G = (V, E) with partition V = {V1, V2} is said to be a
complete bipartite graph if every vertex in V1 is connected
to every vertex of V2; and Star Graph: A complete
bipartite graph of the form K1, n-1 is a star graph with n-
vertices. A star graph is a complete bipartite graph if a
single vertex belongs to one set and all the remaining
vertices belong to the other set. Graph of any of the
categories mentioned can be used to solve Shortest Path
Problems; Network Flow Problems; Matching Problems;
2-SAT Problem; Graph Coloring Problem; Traveling
Salesman Problem (TSP)[4,5].
2.3. Shortest Path Problem
Shortest path is a fundamental problem in graph theory. It
is can also be one of the principal problem in network
analysis. The shortest path problem is a problem of finding
the shortest path or route from a starting point to a final
destination. Generally, in order to represent the shortest
path problem, we use graphs. A graph is a mathematical
abstract object, which contains sets of vertices and edges.
Edges connect pairs of vertices. Along the edges of a
graph it is possible to walk by moving from one vertex to
other vertices. Depending on whether or not one can walk
along the edges by both sides or by only one side
determines if the graph is a directed graph or an undirected
graph. In addition, lengths of edges are often called
weights, and the weights are normally used for calculating
the shortest path from one point to another point. In the
real world it is possible to apply the graph theory to
different types of scenarios.
For example, in order to represent a map, we can use a
graph, where vertices represent cities and edges represent
routes that connect the cities. If routes are one-way then
the graph will be directed; otherwise, it will be undirected.
Another definition of Liu, "The path(s) through the
network from a known starting point to an optional ending
point that minimizes distance, or some other measure
based on distance, such as travel time". Furthermore, there
are three main types of shortest path problems. Which are:
Single source shortest path (SSSP) algorithms; Single
destination shortest path (SDSP) algorithms; All-pairs
shortest path (APSP) algorithms [6,7].There exist different
types of algorithms that solve the shortest path problem
that uses geneticalgorithm which include: Dijkstra’s
Algorithm; Floyd-Warshall Algorithm; Bellman-Ford
Algorithm; and Alternative path algorithm [8,9,10].
3. RESEARCH METHOD AND DESIGN
3.1. Research Data
In the process of design of proposed application, we
source for data about various popular locations within
YabaTech. The locations are:
 First gate
 Second gate
 Medical center
 Library
 New building
 art complex
 college hall
 food village
 science complex
Since the research is focus on design of a software, we
develop a program algorithm that will serve as guide for
coding with the use of appropriate programming tool.
Figure 1: propose application flowchart

3302
The following procedure explains how the system
flowchart works
i. User launches the application’s icon
ii. The welcome screen displays and then takes the
user to the main screen
iii. User is asked to select his / her current location
iv. User is asked to select his / her destination.
v. Click Next
vi. It tests if the current location is not equal to
destination. If current location is equal to
destination, then it will go back to select current
location. Else
vii. It will display result and stop.
3.2. Programming Tools
The programming tools proposed to be use for design of
the proposed system is:
 Android studio: This is software used in coding
and designing native android applications. It
contains XML files and Java files. The reason for
the choice of programming language is because
the Android Operating System is one of the major
Operating Systems dominating the world of
mobile devices nowadays and since mobile
devices are also trending, beating down the usual
use of laptops and desktops, the decision of
designing a mobile application was birthed.
 Android SDK: This is software that is used for
developing android application.
3.3. System Design and Specification
This application will be design to show different locations
in the college. It shows the distances between a pair of
location selected and also displays them on a map and
advices user on the shortest routes from the origin to the
destination of the journey within the college.
The input specification describes the kind of information
that will be feed into the application to be designed while
the output specification lay emphasis on how the
appearance and the kind of result the application will
produce after it has been successfully executed, aftermath
of debugging.
The following are the Input Specification
requirement:
 The user is required to select his/her current
location.
 The user is required to select his/her Destination.
The following are the output specification
requirement:
 The application displays the distance to cover and
also shows the route to the destination in meters.
 The application also shows you the time required
to get to your destination from your source.
Table 1: Data Structure for Source and Destination
database design
Field Name Data
type
Length
Source Char 1 - 255
Destination Char 1 - 255
4. IMPLEMENTATION AND TESTING
The algorithm in figure I was coded using the proposed
programming language, and data structure in table I. The
system was implemented, debug and tested, and it was
observed that the research objective was achieved and the
program has since been deployed for usage free of charge
within and outside the college. The figure 2 shows the
splash screen after launching of the program.
Figure 2: Splash Screen
After the splash screen the users then click on Icon with
inscription go, and the user interface figure 3, will invoke
through which the user can select activity like location to
start it journey from or view the various building with the
college.

3303
Figure 3: Main Activity Users Interface
After selection of the locations, a user interface as shown
in figure 4 appear and user can then pair two different
location and view the path to his or her destination. In
figure 4 the pair locations are first gate and science
complex and the result displayed is as shown figure 5. The
shortest path is shown in the map display.
Figure 4: Pair Locations for first gate and science
complex
Figure 5: Result for pair location first gate and science
complex.
The System was also tested to find the shortest path
between: first gate and college hall, and second gate to
college hall. The alternative route was shown for the two
pair and the result was displayed and compared to have
significant time difference. figure 6,7,8, and 9 shows the
displayed result.
Figure 6: Shortest path first gate to college hall

3304
Figure 7: Alternative route first gate to college hall
Figure 8: Shortest path second gate to college hall
Figure 9: alternative route second gate to college hall
If two same locations are selected no map will be
displayed instead the following user interface with
inscription you cannot pair two same locations will be
display and the system will advise the user to pair two
different location. see figure 10. User can then click back
button to select two different locations.
Figure 10: users interface for two same locations
5. CONCLUSION
This study discussed the graph theory combined with
its types and application areas. The shortest path problem
was identified as a problem in graph theory which finds
the shortest and quickest route. We design mobile map to
find the shortest path from a source to a destination. We
used the dijkstra algorithm to determine the shortest route

3305
within the locations. The distance and time of different
nodes that leads to a particular destination were identified
and compared in order to choose the shortest and fastest
route in the network. A mobile map application was
designed and implements using the Android studio, and
Android SDK. The system was tested and it meets the
standard and solution required to resolve the problem
identified.
REFERENCES
[1.] Mojo H., (2016). Graph theory. Available at
www.en.m.wikipedia.org/wiki/Graph_Theoy.
Retrieved 9th
August 2016.
[2.] Map of India (n.d) what is map? available at
http://www.mapsofindia.com/what-is-map.html.
Retrieved on December 25th
, 2016.
[3.] Merriam W., (2016). Definition of Graph. Available
at www.merriam-webster.com/Dictionary/graph.
retrieved 13th
July, 2016.
[4.] Jaehyun, P. (2015), Basic Graph Algorithms. CS
97SI. Stanford University.
[5.] Amanda B., (2016). Types of maps. Available at
www.thoughtco.com/types of maps. retrieved 19th
august 2016.
[6.] Al-Tameemi, H.L.H., (2014). Using Dijkstra
Algorithm in Calculating AlternativeShortest
Paths for Public Transportation with
Transfersand Walking. Ankara.
[7.] Kairanbay, M., &Hajar, M.J., (2013). A Review
and Evaluations of Shortest Path Algorithms.
International Journal of Scientific and
Technology Research, Vol 2, 99-101.
[8.] Holger, B., Stefan, F., Peter, S., Dominik, S.,
&Domagoj, M., (2010). Transit Ultrafast
Shortest-Path Queries with Linear-time
Preprocessing. Germany.
[9.] Avdhesh, K.S., & Sourabh, K., (2013). Finding of
Shortest Path from Source to Destination by
traversing every Node in wired Network
International Journal of Engineering and
Technology, Vol 5, 2655-2656.
[10.] Hyun J.L., & Soo D.K., (2010). A service-based
approach to developing Android Mobile Internet
Device (MID) applications. Service-Oriented
Computing and Applications.

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