DRAMA 1 is a distributed policy-based management system designed to manage Mobile Ad hoc NETworks (MANETs). Its design philosophy is to create intelligent, self-adaptive policy agents to manage dynamic networks without human intervention. Network management functions are performed in a distributed fashion by these policy agents, rather than being controlled by a centralized management station. Policies are used to control the frequency and content of network management messages exchanged among policy agents in a way that reduces bandwidth usage and increases the utility of management messages. This greatly enhances management efficiency and reduces the bandwidth overhead required for network management. As with any new technology, there is a question about the scalability of this approach. The purpose of the work described in this paper is to study whether the DRAMA policy-based network management system can scale to networks of 500+ nodes. The study uses a novel simulation-based approach to evaluate DRAMA performance when DRAMA is used to manage MANETs of up to 500 nodes. The results confirm that the DRAMA distributed policy-based management paradigm provides superior performance over a centralized management paradigm for MANETs.
The need for scalability analysis of mobile ad hoc networks (MANETs) is both obvious and critical. However, the complexity of MANETs coupled with the unpredictable environment they are designed to operate (e.g., highly dynamic link conditions and random mobility patterns) renders use of closed form solutions infeasible unless over-simplifying assumptions are made. The use of modeling and simulation (M&S) techniques that allow us to retain the complexity of the system therefore become invaluable while analyzing such systems. While current discrete event simulation (DES) tools render the analysis of complex MANETs feasible, they are often times limited to analyzing small (O(100)) node networks. Scalability analysis (e.g., O(500)+ nodes) with current DES tools however tend to require very long simulation times. In this paper we describe approaches to speeding up the M&S phase while analyzing MANETs. More specifically, we propose techniques to analyze the scalability performance of a dynamic policy-based network management system for MANETs that are instrumental in maintaining the "health" of the underlying MANET.
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