An Object-Oriented Model for Network Management

Most networks today lack management tools that support automated identification of faults and bottlenecks and support effective recovery procedures. The NetMATE project, discussed in this paper, addresses the issue related to distributed network management of large, heterogeneous networks. NetMATE employs a modular, object-oriented approach to develop extensible management tools and a model for network information. The first prototype of the system confirms the elegance of the design

Towards a Framework for Comparing Object-Oriented Systems

Choosing a suitable object-oriented system for a particular application domain is very hard, at least in part because the object-oriented research community has not yet converged on what is meant by "object-oriented system". In order to solve this selection problem, a comparison framework is proposed to evaluate a range of object-oriented systems. We then use this framework to consider three different systems, MELD, MARVEL, and VBASE, which represent several quite different design choices for object-oriented systems. We also show the advantages as well as disadvantages about such a framework, and discuss future extensions

A conceptual design of a Software Base Management System for the Computer Aided Prototyping System

This thesis builds upon work previously done in the development of the Computer Aided Prototyping System (CAPS) and the Prototype System Description Language (PSDL), and presents a conceptual design for the Software Base Management System (SBMS) component of CAPS. The SBMS is the most critical component of CAPS as it will coordinate the retrieval and integration of Ada software modules. A robust SBMS that enables a software system designer to successfully retrieve reusable Ada components will expedite the prototype development process and enhance designer productivity. Implementation of the conceptual design will be the basis for further work in this area. (Ada is a registered trademark of the United States Government, Ada Joint Program Office.)http://archive.org/details/conceptualdesign00galiLieutenant Commander, United States NavyApproved for public release; distribution is unlimited

Automating Fine Concurrency Control in Object-Oriented Databases

Several propositions were done to provide adapted concurrency control to object-oriented databases. However, most of these proposals miss the fact that considering solely read and write access modes on instances may lead to less parallelism than in relational databases! This paper cope with that issue, and advantages are numerous: (1) commutativity of methods is determined a priori and automatically by the compiler, without measurable overhead, (2) run-time checking of commutativity is as efficient as for compatibility, (3) inverse operations need not be specified for recovery, (4) this scheme does not preclude more sophisticated approaches, and, last but not least, (5) relational and object-oriented concurrency control schemes with read and write access modes are subsumed under this proposition

Automated Extraction of Behaviour Model of Applications

Highly replicated cloud applications are deployed only when they are deemed to be func- tional. That is, they generally perform their task and their failure rate is relatively low. However, even though failure is rare, it does occur and is very difficult to diagnose. We devise a tool for failure diagnosis which learns the normal behaviour of an application in terms of the statistical properties of variables used throughout its execution, and then monitors it for deviation from these statistical properties. Our study reveals that many variables have unique statistical characteristics that amount to an invariant of the pro- gram. Therefore, any significant deviation from these characteristics reflects an abnormal behaviour of the application which may be caused by a program error. It is difficult to get the invariant from the application’s static code analysis alone. For example, the name of a person usually does not include a semicolon; however, an intruder may try to do a SQL injection (which will include a semicolon) through the ‘name’ field while entering his information and be successful if there is no checking for this case. This scenario can only be captured at runtime and may not be tested by the application de- veloper. The character range of the ‘name’ variable is one of its statistical properties; by learning this range from the execution of the application it is possible to detect the above described abnormal input. Hence, monitoring the statistics of values taken by the different variables of an application is an effective way to detect anomalies that can help to diagnose the failure of the application. We build a tool that collects frequent snapshots of the application’s heap and build a statistical model solely from the extensional knowledge of the application. The extensional knowledge is only obtainable from runtime data of the application without having any description or explanation of the application’s execution flow. The model characterizes the application’s normal behaviour. Collecting snapshots in form of memory dumps and determine the application’s behaviour model from them without code instrumentation make our tool applicable in cases where instrumentation is computationally expensive. Our approach allows a behaviour model to be automatically and efficiently built using the monitoring data alone. We evaluate the utility of our approach by applying it on an e-commerce application and online bidding system, and then derive different statisti- cal properties of variables from their runtime-exhibited values. Our experimental result demonstrates 96% accuracy in the generated statistical model with a maximum 1% per- formance overhead. This accuracy is measured at the basis of generating less false positive alerts when the application is running without any anomaly. The high accuracy and low performance overhead indicates that our tool can successfully determine the application’s normal behaviour without affecting the performance of the application and can be used to monitor it in production time. Moreover, our tool also correctly detected two anomalous condition while monitoring the application with a small amount of injected fault. In ad- dition to anomaly detection, our tool logs all the variables of the application that violates the learned model. The log file can help to diagnose any failure caused by the variables and gives our tool a source-code granularity in fault localization

A risk-level assessment system based on the STRIDE/DREAD model for digital data marketplaces

Security is a top concern in digital infrastructure and there is a basic need to assess the level of security ensured for any given application. To accommodate this requirement, we propose a new risk assessment system. Our system identifies threats of an application workflow, computes the severity weights with the modified Microsoft STRIDE/DREAD model and estimates the final risk exposure after applying security countermeasures in the available digital infrastructures. This allows potential customers to rank these infrastructures in terms of security for their own specific use cases. We additionally present a method to validate the stability and resolution of our ranking system with respect to subjective choices of the DREAD model threat rating parameters. Our results show that our system is stable against unavoidable subjective choices of the DREAD model parameters for a specific use case, with a rank correlation higher than 0.93 and normalised mean square error lower than 0.05

Advances in integrating autonomy with acoustic communications for intelligent networks of marine robots

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2013Autonomous marine vehicles are increasingly used in clusters for an array of oceanographic tasks. The effectiveness of this collaboration is often limited by communications: throughput, latency, and ease of reconfiguration. This thesis argues that improved communication on intelligent marine robotic agents can be gained from acting on knowledge gained by improved awareness of the physical acoustic link and higher network layers by the AUV’s decision making software. This thesis presents a modular acoustic networking framework, realized through a C++ library called goby-acomms, to provide collaborating underwater vehicles with an efficient short-range single-hop network. goby-acomms is comprised of four components that provide: 1) losslessly compressed encoding of short messages; 2) a set of message queues that dynamically prioritize messages based both on overall importance and time sensitivity; 3) Time Division Multiple Access (TDMA) Medium Access Control (MAC) with automatic discovery; and 4) an abstract acoustic modem driver. Building on this networking framework, two approaches that use the vehicle’s “intelligence” to improve communications are presented. The first is a “non-disruptive” approach which is a novel technique for using state observers in conjunction with an entropy source encoder to enable highly compressed telemetry of autonomous underwater vehicle (AUV) position vectors. This system was analyzed on experimental data and implemented on a fielded vehicle. Using an adaptive probability distribution in combination with either of two state observer models, greater than 90% compression, relative to a 32-bit integer baseline, was achieved. The second approach is “disruptive,” as it changes the vehicle’s course to effect an improvement in the communications channel. A hybrid data- and model-based autonomous environmental adaptation framework is presented which allows autonomous underwater vehicles (AUVs) with acoustic sensors to follow a path which optimizes their ability to maintain connectivity with an acoustic contact for optimal sensing or communication.I wish to acknowledge the sponsors of this research for their generous support of my tuition, stipend, and research: the WHOI/MIT Joint Program, the MIT Presidential Fellowship, the Office of Naval Research (ONR) # N00014-08-1-0011, # N00014-08-1-0013, and the ONR PlusNet Program Graduate Fellowship, the Defense Advanced Research Projects Agency (DARPA) (Deep Sea Operations: Applied Physical Sciences (APS) Award # APS 11-15 3352-006, APS 11-15-3352-215 ST 2.6 and 2.7

A Decision Support Method for the Selection of Object Management Systems

With the increasing demand for highly complex, integrated and application domain specific systems engineering environments (SEEs) more or less specialized components of the SEEs are developed. An important component is the database management system (DBMS). It is generally accepted that conventional DBMSs are not useful to fulfill the requirements on highly complex, persistent data structures. Rather specialized DBMSs, namely object management systems (OMS), have been developed for fulfilling the enhanced requirements. An advantage of OMSs is that they further enhance the integration not only of data but also of processes. Currently several specialized OMSs with significantly different properties such as the data model, architecture and performance are available. Thus it is very difficult for an SEE developer to select the most appropriate OMS for his SEE. In this paper we have proposed a decision support method which enables an SEE developer to identify his requirements and to compare the evaluation results of different OMSs. Additionally we present a practical experiment where we have applied the decision support method for comparing different OMSs. Experiences of the investigation are presented briefly