DoKnowMe: Towards a Domain Knowledgedriven Methodology for Performance Evaluation

Software engineering considers performance evaluation to be one of the key portions of software quality assurance. Unfortunately, there seems to be a lack of standard methodologies for performance evaluation even in the scope of experimental computer science. Inspired by the concept of “instantiation” in object-oriented programming, we distinguish the generic performance evaluation logic from the distributed and ad-hoc relevant studies, and develop an abstract evaluation methodology (by analogy of “class”) we name Domain Knowledge-driven Methodology (DoKnowMe). By replacing five predefined domain-specific knowledge artefacts, DoKnowMe can be instantiated into specific methodologies (by analogy of “object”) to guide evaluators in performance evaluation of different software and even computing systems. We also propose a generic validation framework with four indicators (i.e. usefulness, feasibility, effectiveness and repeatability), and use it to validate DoKnowMe in the Cloud services evaluation domain. Given the positive and promising validation result, we plan to integrate more common evaluation strategies to improve DoKnowMe and further focus on the performance evaluation of Cloud autoscaler systems

Streaming media over the Internet: Flow based analysis in live access networks

Multimedia service delivery over the Internet is a success. The number of services available and the number of people accessing them is huge. In this paper, we investigate multimedia streaming services over the Internet. Our analysis is based on traffic measurement in live access fiber-to-the-home networks. We study parameters like traffic volume and flow characteristics for selected services. Especially the Swedish P2P video service Voddler and the Swedish P2P music service Spotify are studied. We show that indeed these services are widely used (20% of local hosts using Voddler, 65 % of local hosts using Spotify). We also show that they are different concerning the flow characteristics, with many short flows for Voddler and longer flows for Spotify. One thing that they have in common in our measurements is that the outbound, or uplink, traffic volume is larger than the inbound

Overload Protection for CORBA Systems with Time Constraints

Scalable and reliable distributed object-oriented computing (DOC) middleware systems is an important technology in, for example, telecommunications service logic and distributed web servers. The Common Object Request Broker Architecture (CORBA), developed by the Object Management Group (OMG) is a speci cation of a common platform for DOC systems. CORBA acts as middleware, by inserting itself between the Operating System (OS) layer and the Application layer on a host. CORBA provides support for transparent interaction of objects situated on different nodes. The original CORBA specications had no support for timing constraints in applications and very little support in the terms of performance optimizations. Present extension to CORBA include support for real-time applications and a number of performance enhancements such as load balancing. However, no work so far address the issue of overload in a CORBA system. This paper presents a discussion of overload issues in distributed CORBA systems with time-constrained tasks. First a performance model of a CORBA system is introduced. Second, overload in distributed CORBA systems is discussed. Third, a number of classic overload protection mechanisms are applied to the performance model and investigated using simulation. The simulations show that even by using very simple protection mechanism, a good throughput can be achieved

Analysis of admission control mechanisms using non-linear control theory

All service control nodes can be modelled as a server system with one or more servers processing incoming requests. In this paper we show how non-linear control theory may be used when analyzing admission control mechanisms for server systems. Two models are developed, one linear and one non-linear. We show that, due to the non-linearities appearing in a real server system, linear control theory is sufficient when designing controllers for these systems. With non-linear analysis, however, the dynamics of a server system may be analysed and taken care of by choosing the controller parameters appropriately

NARX-based multi-step ahead response time prediction for database servers

Advanced telecommunication applications are often based on a multi-tier architecture, with application servers and database servers. With a rapidly increasing development of cloud computing and data centers, characterizations of the dynamics for database servers during changing workloads will be a key factor for analysis and performance improvements in these applications. We propose a multi-step ahead response time predictor for database queries based on a nonlinear autoregressive neural network model with exogenous inputs. The estimator shows many promising characteristics which make it a viable candidate for being implemented in admission control products for database servers. Performance of the proposed predictor is evaluated through experiments on a lab setup with a MySQL-server

Intrusion Detection in Digital Twins for Industrial Control Systems

Nowadays, the growth of advanced technologies is paving the way for Industrial Control Systems (ICS) and making them more efficient and smarter. However, this makes ICS more connected to communication networks that provide a potential platform for attackers to intrude into the systems and cause damage and catastrophic consequences. In this paper, we propose implementing digital twins that have been equipped with an intrusion detection algorithm. Our novel algorithm is able to detect attacks in a timely manner and also diagnose the type of attack by classification of different types of attacks. With digital twins, which are a new concept in ICS, we have virtual replicas of physical systems so that they precisely mirror the internal behavior of the physical systems. So by placing the intrusion detection algorithm in digital twins, security tests can be done remotely without risking negative impacts on live systems

Synchronization in Digital Twins for Industrial Control Systems

Digital twins, which are a new concept in industrial control systems (ICS), play a key role in realizing the vision of a smart factory, and they can have different effective use cases. With digital twins, we have virtual replicas of physical systems so that they precisely mirror the internal behavior of the physical systems. Hence, synchronization is necessary to keep the states of digital twins in sync with those of their physical counterparts. Otherwise, their behavior may be different from each other, and it can lead to wrong decisions about the system that can have catastrophic consequences. In this paper, we propose three different architectures for digital twins, and then by investigating their ability to follow the physical system's behavior, we will determine the best architecture, whose output has the lowest error compared with the physical system's output.Comment: 4 pages, 6 figure