Obtaining response time moments in processor sharing (PS) queues is difficult due to serving of multiple jobs. Egalitarian PS (EPS) queues are limited to one class of arriving jobs. Discriminatory PS (DPS) assigns weights to different job classes and offers more diverse modeling capabilities than EPS. It is known that response time is the representative metric for delay as specified in service level agreements (SLAs), which consider higher moments important. Hence, we build an automated numerical algorithm for calculating higher moments of response time in M/M/1-DPS queues for multiple job classes and test two different case studies.
The purpose of this paper is to articulate the need for an open, extensible robot platform to support swarm robotic research using vision and to propose one such platform. The platform proposed here is intended for research which trades smaller population size with more sophisticated individual robot capabilities. The validation of proposed swarm robotic algorithms using real-world hardware is essential, but is fraught with difficulty due to the expense and complexity of developing and maintaining multiple operational units. A number of open hardware platforms have been proposed, although most prioritize small size and low cost over advanced capabilities such as vision. We are interested in a number of different research directions which utilize vision as a core capability and find the existing open hardware platforms to be insufficient (and existing commercial platforms too expensive). In this paper we describe a set of desirable characteristics for an open, extensible visually-guided robot platform. We then present our solution, the BuPiGo (pronounced buppy-go), describing the hardware itself and a model developed for simulation purposes. We also present some initial results on using the BuPiGo for visual homing an individual navigation task that we hope to exploit for swarm tasks in the future.
Feature-oriented programming (FOP) and aspect-oriented programming (AOP) focus are to modularize additional classes behavior and crosscutting concerns, respectively, for soft- ware evolution. So, these software development approaches represent advanced paradigms for modular software product lines development. Thereby, a FOP and AOP symbiosis would permit reaching pros and cons of both approaches. FOP allows developers to modularly refine classes collaboration for Software Product Lines (SPLs), an adequate approach to represent heterogeneous crosscutting concerns. Similarly, traditional AOP structurally modularizes in a re- fined manner homogeneous crosscutting concerns. Since traditional AOP presents implicit dependencies and strong coupling between classes and aspects, these AOP issues are solved by the Join Point Interface JPI approach. This article presents JPI Feature Modules for FOP + JPI SPL components modularization, i.e., classes, aspects, and join point interfaces along with their evolution, for a SPL transparent implementation in a FOP + JPI context. In addition, this article shows JPI Feature Modules of a case study to highlight mutual benefits of FOP and JPI approaches for a modular SPL software conception.
Many modern programming languages rely on memory management environments that are responsible for allocation and deallocation of objects. Garbage collection phases are used in order to detect inaccessible objects on the heap so they can be deallocated. The performance of garbage collection techniques depends heavily on the environment, implementation specific parameters and the benchmark used. The contribution of this publication is an extendable memory management simulator, which aims to assist developers in memory management evaluation and research. The simulator is capable of reading operations from a trace file extracted from a virtual machine and simulating the memory management needed by the simulated mutator. The framework aims to provide an isolated experimentation and comparison platform in the field of automatic memory management. New algorithms can be added to the framework in order to compare them to established algorithms.
Model checking of Markov chains using logics like CSL or asCSL proves whether a logical formula holds for a state of the Markov chain. It has been developed in the last decade to a widely used approach to express performance and dependability quantities for models from a wide range of application areas. In this paper, model checking is extended to prove formulas for distributions rather than single states. This is a very natural way to express certain performance or dependability measures that depend on the state of the system rather than on a specific state in the state space of the Markov chain. It is shown that the mentioned logics can be easily extended from states to distributions and model checking algorithms can also be easily adopted. Furthermore, new equivalences will be introduced that are weaker than bisimulation but still characterize the extended logics.
