7 research outputs found
Detailed Concept of Network Security
Computer world security management is essential resource for all the latest news, analysis, case studies and reviews on authentication, business continuity and disaster recovery, data control, security infrastructure, intellectual property, privacy standards, law, threats cyber crime and hacking and identity fraud and theft. This section covers secrecy, reliable storage and encryption. security, protecting data from unauthorized access, protecting data from damage and ROM either an external or an internal source, and a disgruntled employee could easily do much harm
Agent Organization and Request Propagation in the Knowledge Plane
In designing and building a network like the Internet, we continue to face the problems of scale and distribution. In particular, network management has become an increasingly difficult task, and network applications often need to maintain efficient connectivity graphs for various purposes. The knowledge plane was proposed as a new construct to improve network management and applications. In this proposal, I propose an application-independent mechanism to support the construction of application-specific connectivity graphs. Specifically, I propose to build a network knowledge plane and multiple sub-planes for different areas of network services. The network knowledge plane provides valuable knowledge about the Internet to the sub-planes, and each sub-plane constructs its own connectivity graph using network knowledge and knowledge in its own specific area. I focus on two key design issues: (1) a region-based architecture for agent organization; (2) knowledge dissemination and request propagation. Network management and applications benefit from the underlying network knowledge plane and sub-planes. To demonstrate the effectiveness of this mechanism, I conduct case studies in network management and security
Multi-domain Diagnosis of End-to-End Service Failures in Hierarchically Routed Networks
Abstract. This paper investigates an approach to improving the scalability and feasibility of probabilistic fault localization in communication systems by exploiting the domain semantics of computer networks. The proposed technique divides the computational effort and system knowledge among multiple, hierarchically organized managers. Each manager performs fault localization in the domain it manages and requires only the knowledge of its own domain. Since failures propagate among domains, domain managers cooperate with each other to find a consensus explanation of the observed disorder. We show through simulation that the proposed approach increases the effectiveness of probabilistic diagnosis and makes it feasible in networks of considerable size 1.
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An Emergent Architecture for Scaling Decentralized Communication Systems (DCS)
With recent technological advancements now accelerating the mobile and wireless Internet solution space, a ubiquitous computing Internet is well within the research and industrial community's design reach - a decentralized system design, which is not solely driven by static physical models and sound engineering principals, but more dynamically, perhaps sub-optimally at initial deployment and socially-influenced in its evolution. To complement today's Internet system, this thesis proposes a Decentralized Communication System (DCS) architecture with the following characteristics: flat physical topologies with numerous compute oriented and communication intensive nodes in the network with many of these nodes operating in multiple functional roles; self-organizing virtual structures formed through alternative mobility scenarios and capable of serving ad hoc networking formations; emergent operations and control with limited dependency on centralized control and management administration. Today, decentralized systems are not commercially scalable or viable for broad adoption in the same way we have to come to rely on the Internet or telephony systems. The premise in this thesis is that DCS can reach high levels of resilience, usefulness, scale that the industry has come to experience with traditional centralized systems by exploiting the following properties: (i.) network density and topological diversity; (ii.) self-organization and emergent attributes; (iii.) cooperative and dynamic infrastructure; and (iv.) node role diversity. This thesis delivers key contributions towards advancing the current state of the art in decentralized systems. First, we present the vision and a conceptual framework for DCS. Second, the thesis demonstrates that such a framework and concept architecture is feasible by prototyping a DCS platform that exhibits the above properties or minimally, demonstrates that these properties are feasible through prototyped network services. Third, this work expands on an alternative approach to network clustering using hierarchical virtual clusters (HVC) to facilitate self-organizing network structures. With increasing network complexity, decentralized systems can generally lead to unreliable and irregular service quality, especially given unpredictable node mobility and traffic dynamics. The HVC framework is an architectural strategy to address organizational disorder associated with traditional decentralized systems. The proposed HVC architecture along with the associated promotional methodology organizes distributed control and management services by leveraging alternative organizational models (e.g., peer-to-peer (P2P), centralized or tiered) in hierarchical and virtual fashion. Through simulation and analytical modeling, we demonstrate HVC efficiencies in DCS structural scalability and resilience by comparing static and dynamic HVC node configurations against traditional physical configurations based on P2P, centralized or tiered structures. Next, an emergent management architecture for DCS exploiting HVC for self-organization, introduces emergence as an operational approach to scaling DCS services for state management and policy control. In this thesis, emergence scales in hierarchical fashion using virtual clustering to create multiple tiers of local and global separation for aggregation, distribution and network control. Emergence is an architectural objective, which HVC introduces into the proposed self-management design for scaling and stability purposes. Since HVC expands the clustering model hierarchically and virtually, a clusterhead (CH) node, positioned as a proxy for a specific cluster or grouped DCS nodes, can also operate in a micro-capacity as a peer member of an organized cluster in a higher tier. As the HVC promotional process continues through the hierarchy, each tier of the hierarchy exhibits emergent behavior. With HVC as the self-organizing structural framework, a multi-tiered, emergent architecture enables the decentralized management strategy to improve scaling objectives that traditionally challenge decentralized systems. The HVC organizational concept and the emergence properties align with and the view of the human brain's neocortex layering structure of sensory storage, prediction and intelligence. It is the position in this thesis, that for DCS to scale and maintain broad stability, network control and management must strive towards an emergent or natural approach. While today's models for network control and management have proven to lack scalability and responsiveness based on pure centralized models, it is unlikely that singular organizational models can withstand the operational complexities associated with DCS. In this work, we integrate emergence and learning-based methods in a cooperative computing manner towards realizing DCS self-management. However, unlike many existing work in these areas which break down with increased network complexity and dynamics, the proposed HVC framework is utilized to offset these issues through effective separation, aggregation and asynchronous processing of both distributed state and policy. Using modeling techniques, we demonstrate that such architecture is feasible and can improve the operational robustness of DCS. The modeling emphasis focuses on demonstrating the operational advantages of an HVC-based organizational strategy for emergent management services (i.e., reachability, availability or performance). By integrating the two approaches, the DCS architecture forms a scalable system to address the challenges associated with traditional decentralized systems. The hypothesis is that the emergent management system architecture will improve the operational scaling properties of DCS-based applications and services. Additionally, we demonstrate structural flexibility of HVC as an underlying service infrastructure to build and deploy DCS applications and layered services. The modeling results demonstrate that an HVC-based emergent management and control system operationally outperforms traditional structural organizational models. In summary, this thesis brings together the above contributions towards delivering a scalable, decentralized system for Internet mobile computing and communications
Agent organization in the KP
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 181-191).In designing and building a network like the Internet, we continue to face the problems of scale and distribution. With the dramatic expansion in scale and heterogeneity of the Internet, network management has become an increasingly difficult task. Furthermore, network applications often need to maintain efficient organization among the participants by collecting information from the underlying networks. Such individual information collection activities lead to duplicate efforts and contention for network resources. The Knowledge Plane (KP) is a new common construct that provides knowledge and expertise to meet the functional, policy and scaling requirements of network management, as well as to create synergy and exploit commonality among many network applications. To achieve these goals, we face many challenging problems, including widely distributed data collection, efficient processing of that data, wide availability of the expertise, etc. In this thesis, to provide better support for network management and large-scale network applications, I propose a knowledge plane architecture that consists of a network knowledge plane (NetKP) at the network layer, and on top of it, multiple specialized KPs (spec-KPs). The NetKP organizes agents to provide valuable knowledge and facilities about the Internet to the spec-KPs. Each spec-KP is specialized in its own area of interest. In both the NetKP and the spec-KPs, agents are organized into regions based on different sets of constraints. I focus on two key design issues in the NetKP: (1) a region-based architecture for agent organization, in which I design an efficient and non-intrusive organization among regions that combines network topology and a distributed hash table; (2) request and knowledge dissemination, in which I design a robust and efficient broadcast and aggregation mechanism using a tree structure among regions.(cont.) In the spec-KPs, I build two examples: experiment management on the PlanetLab testbed and distributed intrusion detection on the DETER testbed. The experiment results suggest a common approach driven by the design principles of the Internet and more specialized constraints can derive productive organization for network management and applications.by Ji Li.Ph.D
Agent Organization in the Knowledge Plane
In designing and building a network like the Internet, we continue to face the problems of scale and distribution. With the dramatic expansion in scale and heterogeneity of the Internet, network management has become an increasingly difficult task. Furthermore, network applications often need to maintain efficient organization among the participants by collecting information from the underlying networks. Such individual information collection activities lead to duplicate efforts and contention for network resources.The Knowledge Plane (KP) is a new common construct that provides knowledge and expertise to meet the functional, policy and scaling requirements of network management, as well as to create synergy and exploit commonality among many network applications. To achieve these goals, we face many challenging problems, including widely distributed data collection, efficient processing of that data, wide availability of the expertise, etc.In this thesis, to provide better support for network management and large-scale network applications, I propose a knowledge plane architecture that consists of a network knowledge plane (NetKP) at the network layer, and on top of it, multiple specialized KPs (spec-KPs). The NetKP organizes agents to provide valuable knowledge and facilities about the Internet to the spec-KPs. Each spec-KP is specialized in its own area of interest. In both the NetKP and the spec-KPs, agents are organized into regions based on different sets of constraints. I focus on two key design issues in the NetKP: (1) a regionbased architecture for agent organization, in which I design an efficient and non-intrusive organization among regions that combines network topology and a distributed hash table; (2) request and knowledge dissemination, in which I design a robust and efficient broadcast and aggregation mechanism using a tree structure among regions. In the spec-KPs, I build two examples: experiment management on the PlanetLab testbed and distributed intrusion detection on the DETER testbed. The experiment results suggest a common approach driven by the design principles of the Internet and more specialized constraints can derive productive organization for network management and applications
CAPRI: A Common Architecture for Distributed Probabilistic Internet Fault Diagnosis
PhD thesisThis thesis presents a new approach to root cause localization and fault diagnosis in the Internet based on a Common Architecture for Probabilistic Reasoning in the Internet (CAPRI) in which distributed, heterogeneous diagnostic agents efficiently conduct diagnostic tests and communicate observations, beliefs, and knowledge to probabilistically infer the cause of network failures. Unlike previous systems that can only diagnose a limited set of network component failures using a limited set of diagnostic tests, CAPRI provides a common, extensible architecture for distributed diagnosis that allows experts to improve the system by adding new diagnostic tests and new dependency knowledge.To support distributed diagnosis using new tests and knowledge, CAPRI must overcome several challenges including the extensible representation and communication of diagnostic information, the description of diagnostic agent capabilities, and efficient distributed inference. Furthermore, the architecture must scale to support diagnosis of a large number of failures using many diagnostic agents. To address these challenges, this thesis presents a probabilistic approach to diagnosis based on an extensible, distributed component ontology to support the definition of new classes of components and diagnostic tests; a service description language for describing new diagnostic capabilities in terms of their inputs and outputs; and a message processing procedure for dynamically incorporating new information from other agents, selecting diagnostic actions, and inferring a diagnosis using Bayesian inference and belief propagation.To demonstrate the ability of CAPRI to support distributed diagnosis of real-world failures, I implemented and deployed a prototype network of agents on Planetlab for diagnosing HTTP connection failures. Approximately 10,000 user agents and 40 distributed regional and specialist agents on Planetlab collect information from over 10,000 users and diagnose over 140,000 failures using a wide range of active and passive tests, including DNS lookup tests, connectivity probes, Rockettrace measurements, and user connection histories. I show how to improve accuracy and cost by learning new dependency knowledge and introducing new diagnostic agents. I also show that agents can manage the cost of diagnosing many similar failures by aggregating related requests and caching observations and beliefs