Hierarchical Approach to Control Dynamic Data Transmission and Mobility Management in MANETs
Krishnaiah Boyana1, Venkateswara Rao Gurrala2, G.V. Swamy3

1Krishnaiah Boyana, Research Scholar, Department of Computer Science & Engineering, GIT, Gitam University Visakapatnam (A.P), India.
2Dr. Venkateswara Rao Gurrala, Associate Professor, Department of Information Technology, GIT, Gitam University Visakhapatnam (A.P), India.
3Dr. G.V. Swamy, Professors and Head, Department of Electronics and Physics, GIT, Gandhi Institute of Technology and Management, Visakhapatnam (A.P), India.

Manuscript received on 24 September 2018 | Revised Manuscript received on 30 September 2018 | Manuscript published on 30 November 2018 | PP: 276-282 | Volume-7 Issue-4, November 2018 | Retrieval Number: E1844017519©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Autonomous addressing protocols require a distributed and self-managed mechanism to avoid address collisions in dynamic mobile ad hoc networks with fading channels, frequent partitions, and joining/leaving nodes. Random policy based adaption is the informative analysis in mobile ad hoc networks dynamism and node simulation in recent application framework with respect to the mobile ad hoc networks performance. Traditionally propose and analyze a lightweight protocol that configures mobile ad hoc nodes based on a distributed address database stored in filters that reduces the control load and makes the proposal robust to packet losses and mobile ad hoc networks partitions. The proposed framework addresses the mobility management issue from a new perspective through posing it as a problem of learning from current system behavior, while creating new policies at runtime in response to changing requirements. A hierarchical policy model i.e. Dynamic Position & Quorum based Opportunistic Energy Routing Protocol (DPQOERP) is used to capture users and administrators’ higher level goals into mobile ad hoc networks level objectives. Given sets of mobile ad hoc networks objectives and constraints, policies are assembled at runtime. The new approach gives more flexibility to users and applications to dynamically change their quality-of-service (QoS) requirements while maintaining a smooth delivery of QoS through mobile ad hoc networks monitors feedback. Our proposed approach compares with existing mobility models with respect to end-to end delay, packet delivery ration and other specifications present in ad hoc networks. Simulation results demonstrate the performance with traditional mobility model
Keywords: Mobile ad hoc networks, Lightweight protocol, Energy Protocol, Quality of service, Mobility management and Dynamic & Position routing.

Scope of the Article: Mobile Computing and Applications