Petr Novotny

On-Demand Discovery of Software Service Dependencies in MANETs

The dependencies among the components of service-oriented software applications hosted in a mobile ad hoc network (MANET) are difficult to determine due to the inherent loose coupling of the services and the transient communication topologies of the network. Yet understanding these dependencies is critical to making good management decisions, since dependence data underlie important analyses such as fault localization and impact analysis. Current methods for discovering dependencies, developed primarily for fixed networks, assume that dependencies change only slowly and require relatively long monitoring periods as well as substantial memory and communication resources, all of which are impractical in the MANET environment. We describe a new dynamic dependence discovery method designed specifically for this environment, yielding dynamic snapshots of dependence relationships discovered through observations of service interactions. We evaluate the performance of our method in terms of the accuracy of the discovered dependencies, and draw insights on the selection of critical parameters under various operational conditions. Although operated under more stringent conditions, our method is shown to provide results comparable to or better than existing methods.

Fault Localization in MANET-Hosted Service-Based Systems

Fault localization in general refers to a technique for identifying the likely root causes of failures observed in systems formed from components. Fault localization in systems deployed on mobile ad hoc networks (MANETs) is a particularly challenging task because those systems are subject to a wider variety and higher incidence of faults than those deployed in fixed networks, the resources available to track fault symptoms are severely limited, and many of the sources of faults in MANETs are by their nature transient. We present a method for localizing the faults occurring in service-based systems hosted on MANETs. The method is based on the use of dependence data that are discovered dynamically through decentralized observations of service interactions. We employ both Bayesian and timing-based reasoning techniques to analyze the data in the context of a specific fault propagation model, deriving a ranked list of candidate fault locations. We present the results of an extensive set of experiments exploring a wide range of operational conditions to evaluate the accuracy of our method.

Dynamic placement of composite software services in hybrid wireless networks

The dynamic environment of hybrid mobile and fixed wireless networks used in military operations poses significant challenges in the efficient provisioning of software functionality to application clients. With their transient topology, the software services hosted on mobile nodes may become temporarily unavailable or the cost of transferring data across the network may become too high. To address this problem we have designed a placement technique that allows the dynamic repositioning of services within the network as it evolves. The technique repositions services in reaction to changes in network topology as well as in various system properties, such as service dependencies or the workload generated by application clients. In our approach we use a multi-layer model to represent a service-based software system embedded in a network topology. We apply constraint programming and its linear programming relaxation to solve the model to find where best to place or reposition the services. We evaluate the technique in terms of its effectiveness and cost under various simulated operational conditions.

Diagnosing degradation of services in hybrid wireless tactical networks

In this paper, we consider a problem related to service management and deployment in tactical military networks. Tactical networks are typically hybrid wireless networks in which there are both static and mobile nodes with several wireless interfaces, such as 802.11, 3G, satellite, etc. In tactical networks, performance degradation in services could prove fatal, so it must be diagnosed quickly. This degradation could be due to mobility or bottlenecks in capacity at network layer. We provide a cross-layer framework to detect and diagnose these causes of performance degradation as part of service management; it includes a monitoring model of services and a network model for hybrid wireless networks. In addition, we give a working example in tactical military networks to illustrate our framework. We provide an experimental setup to simulate our hybrid wireless tactical network scenario along with preliminary results.

Inferring Network Topologies in MANETs Applied to Service Redeployment

The heterogeneous and dynamic nature of tactical coalition networks poses several challenges to common network management tasks, due to the lack of complete and accurate network information. In this paper, we consider the problem of redeploying services in mobile tactical networks. We propose M-iTop, an algorithm for inferring the network topology when only partial information is available. M-iTop initially constructs a virtual topology that overestimates the number of network components, and then repeatedly merges links in this topology to resolve it towards the structure of the true network. We perform extensive simulations and show that M-iTop enables an efficient redeployment of services over the network despite the limitation of partial information.

LedgerGuard: Improving Blockchain Ledger Dependability

The rise of crypto-currencies has spawned great interest in their underlying technology, namely, Blockchain. The central component in a Blockchain is a shared distributed ledger. A ledger comprises series of blocks, which in turns contains a series of transactions. An identical copy of the ledger is stored on all nodes in a blockchain network. Maintaining ledger integrity and security is one of the crucial design aspects of any blockchain platform. Thus, there are typically built-in validation mechanisms leveraging cryptography to ensure the validity of incoming blocks before committing them into the ledger. However, a blockchain node may run over an extended period of time, during which the blocks on the disk can may become corrupted due to software or hardware failures, or due to malicious activity. This paper proposes LedgerGuard, a tool to maintain ledger integrity by detecting corrupted blocks and recovering these blocks by synchronizing with rest of the network. The experimental implementation of LedgerGuard is based on Hyperledger Fabric, which is a popular open source permissioned blockchain platform.

Locating faults in MANET-hosted software systems

We present a method to locate faults in service-based software systems hosted on mobile ad hoc networks (MANETs). In such systems, computations are structured as interdependent services distributed across the network, collaborating to satisfy client requests. Faults, which may occur at either or both the service and network layers, propagate by cascading through some subset of the services, from their root causes back to the clients that initiate requests. Fault localization in this environment is especially challenging because the systems are typically subject to a wider variety and higher incidence of faults than those deployed in fixed networks, the resources available to collect and store analysis data are severely limited, and many of the sources of faults are by their nature transient. Our method makes use of service-dependence and fault data that are harvested in the network through decentralized, run-time observations of service interactions and fault symptoms. We have designed timing- and Bayesian-based reasoning techniques to analyze the data in the context of a specific fault propagation model. The analysis provides a ranked list of candidate fault locations. Through extensive simulations, we evaluate the performance of our method in terms of its accuracy in correctly ranking root causes under a wide range of operational conditions.

Delay Tolerant Harvesting of Monitoring Data for MANET-Hosted Service-Based Systems

We are concerned with reliably harvesting data used to monitor a service-based system hosted in a mobile ad hoc network (MANET) environment. These data are time-bounded, time-sensitive time-series data recorded by individual hosts in the network. Harvesting is used to gather the data for global time-series analyses, such as fault localization. The MANET environment challenges data harvesting, due to the inherently unstable and unpredictable connectivity and the resource limitations of wireless devices. We present an epidemic, delay tolerant method to improve the availability of time-series monitoring data in the presence of network instabilities, asymmetries, and partitions. The method establishes a network-wide synchronization overlay to incrementally and efficiently move data to intermediate nodes. We have implemented the algorithm in Java EE and evaluated it in the CORE and EMANE MANET emulation environments.