Stephanie Demers

Performance Analysis of Drama: A Distributed Policy-Based System for Manet Management

DRAMA 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

MANETs: Perfrormance Analysis and Management

In this work, we model and analyze the performance of optimized link state routing (OLSR), a proactive routing protocol, in wireless mobile ad-hoc networks. More specifically, we identify key OLSR parameters that have significant impact on the amount of overhead produced and the network route convergence time. Observe that while reduction in protocol-related overheads is crucial in bandwidth sensitive wireless MANETs, it is also critical that route convergence times are minimized in order to ensure rapidity of information dissemination. However, bandwidth reduction and convergence times place opposing constraints on the key OLSR parameters. In this paper, we use detailed modeling, simulations and analyses (MSA), to analyze the effect of varying the key OLSR parameters and the trades they produce in terms of overheads and convergence times. In particular, our contribution is two-fold. Via MSA, we provide detailed insights on how the topology control and hello interval timers can be used to reduce overheads without adversely affecting MANET route convergence times. Next, we describe an approach that combines the rapidly emerging policy-based network management paradigm with MSA to result in an adaptive network management system (ANMS). Such an ANMS has the capability of providing powerful information to MANET designers in terms of provisioning the network as well as understanding how quickly the network can be deployed in order to support mission critical services

A Generic Solution to Software-in-the-Loop

The low fidelity and speed of traditional simulations have become unacceptable for the complex large-scale networks of today. In this paper we propose alternative techniques and focus on a software-in-the-loop implementation. Software-in-the-loop provides us with the following two-fold advantages: (a) it helps solve traditional simulation problems of model validity and (b) it can be used in the design phase as well as in the testing phase of a project. However, software-in-the-loop brings its own set of challenges, as we discuss in this paper. We will present a generic end-to-end solution that mitigates the challenges of a software-in-the-loop configuration to bring it it to its full potential. The success of our solution will be exemplified by its use in two government funded projects where it was successfully used to analyze scalability performance in one case and to perform unit and integration testing in a second case. The focus of this paper will be on the use of software-in-the-loop versus traditional simulations, discussing the challenges, issues and decision processes involved with the use of software-in-the-loop.

Scalable Registration and Discovery of Devices in Low-Bandwidth Tactical Networks

Management of RF Network and Tasking Infrastructure (MARTI) is a distributed system that discovers, tracks, coordinates, and manages the reception and transmission capabilities of an overlay network of RF devices. To enable scalable discovery and tracking, we employ a dynamic hierarchical domain management technique with features targeted for low-bandwidth networks. The dynamic hierarchy achieves the efficiency benefit of hierarchical systems, while avoiding single points of failure by dynamic reelection of domain manager (DM) nodes in response to node failures and disconnections. The Domain Announcement Protocol (DAP) employed for this purpose autonomously creates and organizes domains in a dynamic structure, supports splits and merges of domains, and employs a rich set of metrics for DM election, which enables DAP to adapt to loss of links or node failures. Furthermore the criteria used for the dynamic election of DMs are tuned so that DMs can also serve as distributed and survivable Directory Agents (DAs). Thus the DAP DMs which support the formation of domains are also used to realize the MARTI directory agent functions, which is an unusual example of efficient cross-layer functional re-use.

Demand-Driven Prioritization for ACERT

Cognitive Adaptive Radio Teams (CART) is a new platform developed by our group in support of collaborative data collection and dissemination in a radio- challenged setting. The target scenario is characterized by a harsh ad-hoc radio environment with many-to-many multicast applications. In this paper we proposed a special data structure called demand-driven prioritized data structure (DDPDS) that allows optimization of such data dissemination using cognitive wireless techniques.