Evaluating an Application Aware Distributed Dijkstra Shortest Path Algorithm in Hybrid CloudEdge Environments
Abstract : To increase the flexibility and the dynamism of communication networks, Software Defined Networking (SDN) has emerged as the challenging approach to decouple control and data planes, using a logically centralized controller able to manage the underlying network resources. However, traditional network solutions can not be always used in SDN. In this paper, we deal with routing issued in the setup of dynamic SDNs spanning Fog/Edge and IoT systems for the support of new generation applications. In particular, we propose a modified version of the Dijkstra's routing algorithm that can optimize complex routing metrics and uses MapReduce to speed up the configuration of routers in the network. The system can optimize the packet routing in according to different parameters including, e.g., hops, latency, and energy efficiency policies. In order to validate our work, we performed evaluations on the revised MapReduce version of the Dijkstra routing algorithm considering a high scalable network topology with thousands of virtual nodes.
? Extending this idea we observe the existence of a shortest path tree in which distance from source to vertex is length of shortest path from source to vertex in original tree.
? In their most simple form, such systems will model a road network using an edge-weighted graph with vertices (nodes) of this graph representing road junctions.
? The user then takes two pegs and pulls them apart, and the shortest path between these pegs is shown by the tight pieces of string.
? As an alternative, we propose two variants of Dijkstra’s algorithm that operate on the original, unexpanded graph.
? In transportation problems for example, they could indicate predicted travel times or fuel costs; in currency conversion they could represent exchange rates.
? The manipulation of shortest paths between various locations appears to be a major problem in the road networks.
? The shortest path problem is to find a path between two vertices (nodes) on a given graph, such that the sum of the weights on its constituent edges is minimized.
? This problem has been intensively investigated over years, due to its extensive applications in graph theory, artificial intelligence, computer network and the design of transportation systems.
? The classic Dijkstra’s algorithm was designed to solve the single source shortest path problem for a static graph.
? Dijkstra‘s Algorithm is a graph search algorithm that solves the single-source shortest path problem for a graph with nonnegative edge path costs, producing a shortest path tree.
• This paper has proposed two new shortest path algorithms that are able to handle vertex transfer penalties without first having to perform a graph expansion.
• We then propose two extensions to Dijkstra’s algorithm that allow us to calculate shortest paths in these graphs without any need for expansion.
• We now propose two variants of Dijkstra’s algorithm. These are designed to find shortest paths in our edge-coloured graphs (that is, graphs featuring transfer penalties at their vertices), but without the need for first performing a graph expansion.
• Although the Kirby–Potts expansion is the most useful for our purposes, we should also note the presence of two other expansion methods used in the literature.
? Efficient usage of routing algorithms can significantly reduce travelling distance and transportation costs as well.
? This algorithm is often used in routing and other network related protocols.
? The algorithms are part of an overall Indoor Navigation Model that is used to provide assistance and guidance in unfamiliar indoor environments.
? In particular, we wish to assess the relative performances of our extended Dijkstra methods in comparison to using Dijkstra’s original algorithm on Kirby–Potts expanded graphs.
? We now consider the relative performance of our implementations on real-world public transport networks.
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