Hierarchical Collective Agent Network (HCAN) for efficient 3 fusion and management of multiple networked sensors

Agent-based software systems and applications are constructed by integrating diverse sets of components that are intelligent, heterogeneous, distributed, and concurrent. This paper describes a multi-agent system to assure the operation efficiency and reliability in data fusion and management of a set of networked distributive sensors (NDS). We discuss the general concept and architecture of a Hierarchical Collective Agent Network (HCAN) and its functional components for learning and adaptive control of the NDS. Sophistication of a HCAN control environment and an anatomy of the agent modules for enabling intelligent data fusion and management are presented. An exemplar HCAN is configured to support dynamic data fusion and automated sensor management in a simulated distributive and collaborative military sensor network for Global Missile Defense (GMD) application

Wireless Sensor Network Infrastructure: Construction and Evaluation

International audienceLarge area wireless sensor deployments rely on multi-hop communications. Efficient packet transmissions and virtual topologies, which structure sensor networks, are two main features for efficient energy management in wireless sensor networks. This paper aims to present a distributed and low-cost topology construction algorithm for wireless sensor networks, addressing the following issues: large-scale, random network deployment, energy efficiency and small overhead. We propose structuring nodes in zones, meant to reduce the global view of the network to a local one. This zone-based architecture is the infrastructure used by our hierarchical routing protocol. The experimental results show that the proposed algorithm has low overhead and is scalable

CyberCraft: Protecting Electronic Systems with Lightweight Agents

The United States military is seeking new and innovative methods for securing and maintaining its computing and network resources locally and world-wide. This document presents a work-in-progress research thrust toward building a system capable of meeting many of the US military’s network security and sustainment requirements. The system is based on a Distributed Multi-Agent System (DMAS), that is secure, small, and scalable to the large networks found in the military. It relies on a staged agent architecture capable of dynamic configuration to support changing mission environments. These agents are combined into Hierarchical Peer-to-Peer (HP2P) networks to provide scalable solutions. They employ Public Key Infrastructure (PKI) communications (with digital signatures), and support trust chain management concepts. This document, a work-in-progress, presents the motivation and current challenges in choosing a network communications architecture capable of supporting one million or more agents in a DMAS

Distributed mobility management with mobile Host Identity Protocol proxy

The architectural evolution from hierarchical to flatter networks creates new challenges such as single points of failure and bottlenecks, non-optimal routing paths, scalability problems, and long handover delays. The cellular networks have been hierarchical so that they are largely built on centralized functions based on which their handover mechanisms have been built. They need to be redesigned and/or carefully optimized. The mobility extension to Host Identity Protocol (HIP) proxy, mobile HIP Proxy (MHP), provides a seamless and secure handover for the Mobile Host in the hierarchical network. However, the MHP cannot ensure the same handover performance in flatter network because the MHP has also utilized the features offered by the hierarchical architecture. This paper extends the MHP to distributed mobile HIP proxy (DMHP). The performance evaluation of the DMHP in comparison to MHP and other similar mobility solutions demonstrates that DMHP does indeed perform well in the flatter networks. Moreover, the DMHP supports both efficient multi-homing and handover management for many mobile hosts at the same time to the same new point of attachment

Network anomaly detection using management information base (MIB) network traffic variables

In this dissertation, a hierarchical, multi-tier, multiple-observation-window, network anomaly detection system (NADS) is introduced, namely, the MIB Anomaly Detection (MAD) system, which is capable of detecting and diagnosing network anomalies (including network faults and Denial of Service computer network attacks) proactively and adaptively. The MAD system utilizes statistical models and neural network classifier to detect network anomalies through monitoring the subtle changes of network traffic patterns. The process of measuring network traffic pattern is achieved by monitoring the Management Information Base (Mifi) II variables, supplied by the Simple Network Management Protocol (SNMP) LI. The MAD system then converted each monitored Mifi variable values, collected during each observation window, into a Probability Density Function (PDF), processed them statistically, combined intelligently the result for each individual variable and derived the final decision. The MAD system has a distributed, hierarchical, multi-tier architecture, based on which it could provide the health status of each network individual element. The inter-tier communication requires low network bandwidth, thus, making it possibly utilization on capacity challenged wireless as well as wired networks. Efficiently and accurately modeling network traffic behavior is essential for building NADS. In this work, a novel approach to statistically model network traffic measurements with high variability is introduced, that is, dividing the network traffic measurements into three different frequency segments and modeling the data in each frequency segment separately. Also in this dissertation, a new network traffic statistical model, i.e., the one-dimension hyperbolic distribution, is introduced

Description of the SSF PMAD DC testbed control system data acquisition function

The NASA LeRC in Cleveland, Ohio has completed the development and integration of a Power Management and Distribution (PMAD) DC Testbed. This testbed is a reduced scale representation of the end to end, sources to loads, Space Station Freedom Electrical Power System (SSF EPS). This unique facility is being used to demonstrate DC power generation and distribution, power management and control, and system operation techniques considered to be prime candidates for the Space Station Freedom. A key capability of the testbed is its ability to be configured to address system level issues in support of critical SSF program design milestones. Electrical power system control and operation issues like source control, source regulation, system fault protection, end-to-end system stability, health monitoring, resource allocation, and resource management are being evaluated in the testbed. The SSF EPS control functional allocation between on-board computers and ground based systems is evolving. Initially, ground based systems will perform the bulk of power system control and operation. The EPS control system is required to continuously monitor and determine the current state of the power system. The DC Testbed Control System consists of standard controllers arranged in a hierarchical and distributed architecture. These controllers provide all the monitoring and control functions for the DC Testbed Electrical Power System. Higher level controllers include the Power Management Controller, Load Management Controller, Operator Interface System, and a network of computer systems that perform some of the SSF Ground based Control Center Operation. The lower level controllers include Main Bus Switch Controllers and Photovoltaic Controllers. Power system status information is periodically provided to the higher level controllers to perform system control and operation. The data acquisition function of the control system is distributed among the various levels of the hierarchy. Data requirements are dictated by the control system algorithms being implemented at each level. A functional description of the various levels of the testbed control system architecture, the data acquisition function, and the status of its implementationis presented

Management of DiffServ-over-MPLS Transit Networks with BFD/OAM in ForCES Architecture †

Abstract. This paper proposes a management of DiffServ-over-MPLS transit network with BFD(Bidirectional Forwarding Detection)/OAM (operation, administration and maintenance) in ForCES (Forwarding and Control Element Separation) architecture for QoS-guaranteed DiffServ-over-MPLS traffic engineering. The proposed BFD and ForCES functions are implemented on Intel 2400 network processor, where BFD/OAM packets for MPLS TE-LSP are exchanged every 5 ~ 10 ms interval for performance measurements and link failure detection. The operations of BFD/OAM-based fault detection and performance measurement are controlled via distributed control plane with ForCES (forwarding and control element separation) architecture for large scale IP/MPLS router using multiple network processors in each network interface card. We explain the implementation details of ForCES-based distributed control plane functions, hierarchical traffic grooming with label stacking, and BFD/OAM mechanisms. The link failure detection performance of BFD/OAM functions for MPLS TE-LSP is evaluated