Improved Energy Efficiency using Distributed Swarm Intelligence (DSI) in Wireless Mobile Networks

Abstract

Distributed Swarm Intelligence (DSI) is a relatively new paradigm being applied in a host of research settings to improve the management and control of large numbers of interacting entities such as communication, computer, mobile networks, satellite constellations and more. Distributed path computation is a core functionality of modern communication networks and is expected to remain so, even though some recent proposals contemplate the use of more centralized solutions and patterns. Depending on the mode of information dissemination and subsequent computation using the disseminated information, there are two broad classes of algorithms: (i) link-state algorithms and (ii) distance-vector algorithms. In both methods, nodes choose successor (next-hop) nodes for each destination based only on local information, along with this objective we are providing an additional algorithm i.e. Mobile Ants-Based Routing (MABR) with DSI to chosen better paths to the destination by effective in an appropriate manner. Using Ant Colony optimization with DSI for the distribution computation is the novel approach carried on which clearly shows the performance improvement of their QoS metrics based on the parameters viz. Delay, Data rate, Packets Received and Packets Lost were analyzed. We are able to achieve consistency across nodes, thus energy Efficiency using Distributed Swarm Intelligence (DSI) in Wireless Mobile Networks.