June 14th, 2017

Cache replacement and branch prediction are two important microarchitectural prediction techniques for improving performance. We propose a data-driven approach to designing microarchitectural predictors. Through simulation, we collect traces giving detailed control-flow and memory behavior. Then use stochastic search techniques, such as genetic algorithms, to find points in a large design space of predictors that yield good accuracy on the traces. We then evaluate the predictors on held-out data. This talk will present two techniques resulting from this methodology. In Multiperspective Branch Prediction, many features and their parameters are tuned using a genetic algorithm to yield a very accurate perceptron-based branch predictor. Multiperspective Reuse Prediction uses the same idea for cache management. Many features of memory accesses to predict the reuse of a given memory access. The features and their parameters are chosen by a stochastic search yielding a very accurate predictor. This predictor is applied to a placement, replacement, and bypass optimization that out-performs the state of the art

AWESoME: Big Data for Automatic Web Service Management in SDN

Software Defined Network (SDN) has enabled consistent and programmable management in computer networks. However, the explosion of cloud services and Content Delivery Networks (CDN) – coupled with the momentum of encryption – challenges the simple per-flow management and calls for a more comprehensive approach for managing web traffic. We propose a new approach based on a “per service” management concept, which allows to identify and prioritize all traffic of important web services, while segregating others, even if they are running on the same cloud platform, or served by the same CDN. We design and evaluate AWESoME, Automatic WEb Service Manager, a novel SDN application to address the above problem. On the one hand, it leverages big data algorithms to automatically build models describing the traffic of thousands of web services. On the other hand, it uses the models to install rules in SDN switches to steer all flows related to the originating services. Using traffic traces from volunteers and operational networks, we provide extensive experimental results to show that AWESoME associates flows to the corresponding web service in real-time and with high accuracy. AWESoME introduces a negligible load on the SDN controller and installs a limited number of rules on switches, hence scaling well in realistic deployments. Finally, for easy reproducibility, we release ground truth traces and scripts implementing AWESoME core components

Cooperative vehicular traffic monitoring in realistic low penetration scenarios: The COLOMBO experience

The relevance of effective and efficient solutions for vehicle traffic surveillance is widely recognized in order to enable advanced strategies for traffic management, e.g., based on dynamically adaptive and decentralized traffic light management. However, most related solutions in the literature, based on the powerful enabler of cooperative vehicular communications, assume the complete penetration rate of connectivity/communication technologies (and willingness to participate in the collaborative surveillance service) over the targeted vehicle population, thus making them not applicable nowadays. The paper originally proposes an innovative solution for cooperative traffic surveillance based on vehicular communications capable of: (i) working with low penetration rates of the proposed technology and (ii) of collecting a large set of monitoring data about vehicle mobility in targeted areas of interest. The paper presents insights and lessons learnt from the design and implementation work of the proposed solution. Moreover, it reports extensive performance evaluation results collected on realistic simulation scenarios based on the usage of iTETRIS with real traces of vehicular traffic of the city of Bologna. The reported results show the capability of our proposal to consistently estimate the real vehicular traffic even with low penetration rates of our solution (only 10%)

A Big Data Analyzer for Large Trace Logs

Current generation of Internet-based services are typically hosted on large data centers that take the form of warehouse-size structures housing tens of thousands of servers. Continued availability of a modern data center is the result of a complex orchestration among many internal and external actors including computing hardware, multiple layers of intricate software, networking and storage devices, electrical power and cooling plants. During the course of their operation, many of these components produce large amounts of data in the form of event and error logs that are essential not only for identifying and resolving problems but also for improving data center efficiency and management. Most of these activities would benefit significantly from data analytics techniques to exploit hidden statistical patterns and correlations that may be present in the data. The sheer volume of data to be analyzed makes uncovering these correlations and patterns a challenging task. This paper presents BiDAl, a prototype Java tool for log-data analysis that incorporates several Big Data technologies in order to simplify the task of extracting information from data traces produced by large clusters and server farms. BiDAl provides the user with several analysis languages (SQL, R and Hadoop MapReduce) and storage backends (HDFS and SQLite) that can be freely mixed and matched so that a custom tool for a specific task can be easily constructed. BiDAl has a modular architecture so that it can be extended with other backends and analysis languages in the future. In this paper we present the design of BiDAl and describe our experience using it to analyze publicly-available traces from Google data clusters, with the goal of building a realistic model of a complex data center.Comment: 26 pages, 10 figure

Traceability of Requirements and Software Architecture for Change Management

At the present day, software systems get more and more complex. The requirements of software systems change continuously and new requirements emerge frequently. New and/or modified requirements are integrated with the existing ones, and adaptations to the architecture and source code of the system are made. The process of integration of the new/modified requirements and adaptations to the software system is called change management. The size and complexity of software systems make change management costly and time consuming. To reduce the cost of changes, it is important to apply change management as early as possible in the software development cycle. Requirements traceability is considered crucial in change management for establishing and maintaining consistency between software development artifacts. It is the ability to link requirements back to stakeholders’ rationales and forward to corresponding design artifacts, code, and test cases. When changes for the requirements of the software system are proposed, the impact of these changes on other requirements, design elements and source code should be traced in order to determine parts of the software system to be changed. Determining the impact of changes on the parts of development artifacts is called change impact analysis. Change impact analysis is applicable to many development artifacts like requirements documents, detailed design, source code and test cases. Our focus is change impact analysis in requirements and software architecture. The need for change impact analysis is observed in both requirements and software architecture. When a change is introduced to a requirement, the requirements engineer needs to find out if any other requirement related to the changed requirement is impacted. After determining the impacted requirements, the software architect needs to identify the impacted architectural elements by tracing the changed requirements to software architecture. It is hard, expensive and error prone to manually trace impacted requirements and architectural elements from the changed requirements. There are tools and approaches that automate change impact analysis like IBM Rational RequisitePro and DOORS. In most of these tools, traces are just simple relations and their semantics is not considered. Due to the lack of semantics of traces in these tools, all requirements and architectural elements directly or indirectly traced from the changed requirement are candidate impacted. The requirements engineer has to inspect all these candidate impacted requirements and architectural elements to identify changes if there are any. In this thesis we address the following problems which arise in performing change impact analysis for requirements and software architecture. Explosion of impacts in requirements after a change in requirements. In practice, requirements documents are often textual artifacts with implicit structure. Most of the relations among requirements are not given explicitly. There is a lack of precise definition of relations among requirements in most tools and approaches. Due to the lack of semantics of requirements relations, change impact analysis may produce high number of false positive and false negative impacted requirements. A requirements engineer may have to analyze all requirements in the requirements document for a single change. This may result in neglecting the actual impact of a change. Manual, expensive and error prone trace establishment. Considerable research has been devoted to relating requirements and design artifacts with source code. Less attention has been paid to relating Requirements (R) with Architecture (A) by using well-defined semantics of traces. Designing architecture based on requirements is a problem solving process that relies on human experience and creativity, and is mainly manual. The software architect may need to manually assign traces between R&A. Manual trace assignment is time-consuming, expensive and error prone. The assigned traces might be incomplete and invalid. Explosion of impacts in software architecture after a change in requirements. Due to the lack of semantics of traces between R&A, change impact analysis may produce high number of false positive and false negative impacted architectural elements. A software architect may have to analyze all architectural elements in the architecture for a single requirements change. In this thesis we propose an approach that reduces the explosion of impacts in R&A. The approach employs semantic information of traces and is supported by tools. We consider that every relation between software development artifacts or between elements in these artifacts can play the role of a trace for a certain traceability purpose like change impact analysis. We choose Model Driven Engineering (MDE) as a solution platform for our approach. MDE provides a uniform treatment of software artifacts (e.g. requirements documents, software design and test documents) as models. It also enables using different formalisms to reason about development artifacts described as models. To give an explicit structure to requirements documents and treat requirements, architecture and traces in a uniform way, we use metamodels and models with formally defined semantics. The thesis provides the following contributions: A modeling language for definition of requirements models with formal semantics. The language is defined according to the MDE principles by defining a metamodel. It is based on a survey about the most commonly found requirements types and relation types. With this language, the requirements engineer can explicitly specify the requirements and the relations among them. The semantics of these entities is given in First Order Logic (FOL) and allows two activities. First, new relations among requirements can be inferred from the initial set of relations. Second, requirements models can be automatically checked for consistency of the relations. Tool for Requirements Inferencing and Consistency Checking (TRIC) is developed to support both activities. The defined semantics is used in a technique for change impact analysis in requirements models. A change impact analysis technique for requirements using semantics of requirements relations and requirements change types. The technique aims at solving the problem of explosion of impacts in requirements when semantics of requirements relations is missing. The technique uses formal semantics of requirements relations and requirements change types. A classification of requirements changes based on the structure of a textual requirement is given and formalized. The semantics of requirements change types is based on FOL. We support three activities for impact analysis. First, the requirements engineer proposes changes according to the change classification before implementing the actual changes. Second, the requirements engineer indentifies the propagation of the changes to related requirements. The change alternatives in the propagation are determined based on the semantics of change types and requirements relations. Third, possible contradicting changes are identified. We extend TRIC with a support for these activities. The tool automatically determines the change propagation paths, checks the consistency of the changes, and suggests alternatives for implementing the change. A technique that provides trace establishment between R&A by using architecture verification and semantics of traces. It is hard, expensive and error prone to manually establish traces between R&A. We present an approach that provides trace establishment by using architecture verification together with semantics of requirements relations and traces. We use a trace metamodel with commonly used trace types. The semantics of traces is formalized in FOL. Software architectures are expressed in the Architecture Analysis and Design Language (AADL). AADL is provided with a formal semantics expressed in Maude. The Maude tool set allows simulation and verification of architectures. The first way to establish traces is to use architecture verification techniques. A given requirement is reformulated as a property in terms of the architecture. The architecture is executed and a state space is produced. This execution simulates the behavior of the system on the architectural level. The property derived from the requirement is checked by the Maude model checker. Traces are generated between the requirement and the architectural components used in the verification of the property. The second way to establish traces is to use the requirements relations together with the semantics of traces. Requirements relations are reflected in the connections among the traced architectural elements based on the semantics of traces. Therefore, new traces are inferred from existing traces by using requirements relations. We use semantics of requirements relations and traces to both generate/validate traces and generate/validate requirements relations. There is a tool support for our approach. The tool provides the following: (1) generation/validation of traces by using requirements relations and/or verification of architecture, (2) generation/validation of requirements relations by using traces. A change impact analysis technique for software architecture using architecture verification and semantics of traces between R&A. The software architect needs to identify the impacted architectural elements after requirements change. We present a change impact analysis technique for software architecture using architecture verification and semantics of traces. The technique is semi-automatic and requires participation of the software architect. Our technique has two parts. The first part is to identify the architectural elements that implement the system properties to which proposed requirements changes are introduced. By having the formal semantics of requirements relations and traces, we identify which parts of software architecture are impacted by a proposed change in requirements. We have extended TRIC for determining candidate impacted architectural elements. The second part of our technique is to propose possible changes for software architecture when the software architecture does not satisfy the new and/or changed requirements. The technique is based on architecture verification. The output of verification is a counter example if the requirements are not satisfied. The counter example is used with a classification of architectural changes in order to propose changes in the software architecture. These changes produce a new version of the architecture that possibly satisfies the new or the changed requirements

Change Support in Process-Aware Information Systems - A Pattern-Based Analysis

In today's dynamic business world the economic success of an enterprise increasingly depends on its ability to react to changes in its environment in a quick and flexible way. Process-aware information systems (PAIS) offer promising perspectives in this respect and are increasingly employed for operationally supporting business processes. To provide effective business process support, flexible PAIS are needed which do not freeze existing business processes, but allow for loosely specified processes, which can be detailed during run-time. In addition, PAIS should enable authorized users to flexibly deviate from the predefined processes if required (e.g., by allowing them to dynamically add, delete, or move process activities) and to evolve business processes over time. At the same time PAIS must ensure consistency and robustness. The emergence of different process support paradigms and the lack of methods for comparing existing change approaches have made it difficult for PAIS engineers to choose the adequate technology. In this paper we suggest a set of changes patterns and change support features to foster the systematic comparison of existing process management technology with respect to process change support. Based on these change patterns and features, we provide a detailed analysis and evaluation of selected systems from both academia and industry. The identified change patterns and change support features facilitate the comparison of change support frameworks, and consequently will support PAIS engineers in selecting the right technology for realizing flexible PAIS. In addition, this work can be used as a reference for implementing more flexible PAIS