A survey on offline scheduling with rejection

In classical deterministic scheduling problems, it is assumed that all jobs have to be processed. However, in many practical cases, mostly in highly loaded make-to-order production systems, accepting all jobs may cause a delay in the completion of orders which in turn may lead to high inventory and tardiness costs. Thus, in such systems, the firm may wish to reject the processing of some jobs by either outsourcing them or rejecting them altogether. The field of scheduling with rejection provides schemes for coordinated sales and production decisions by grouping them into a single model. Since scheduling problems with rejection are very interesting both from a practical and a theoretical point of view, they have received a great deal of attention from researchers over the last decade. The purpose of this survey is to offer a unified framework for offline scheduling with rejection by presenting an up-to-date survey of the results in this field. Moreover, we highlight the close connection between scheduling with rejection and other fields of research such as scheduling with controllable processing times and scheduling with due date assignment, and include some new results which we obtained for open problems.     

Evolutionary forwarding games in delay tolerant networks: Equilibria,mechanism design and stochastic approximation

In this paper, we apply evolutionary games to non-cooperative forwarding control in Delay Tolerant Networks (DTNs). The main focus is on mechanisms to rule the participation of the relays to the delivery of messages in DTNs. Thus, we express the success probability as a function of the competition that takes place within a large population of mobiles, and we characterize the effect of reward-based mechanisms on the performance of such systems. Devices acting as active relays, in fact, sacrifice part of their batteries in order to support message replication and thus increase the probability to reach the destination. In our scheme, a relay can choose the strategy by which they participate to the message relaying. A mobile that participates receives a unit of reward based on the reward mechanism selected by the network. A utility function is introduced as the difference between the expected reward and the energy cost, i.e., the cost spent by the relay to sustain forwarding operations. We show how the evolution dynamics and the equilibrium behavior (called Evolutionary Stable Strategy – ESS) are influenced by the characteristics of inter contact time, energy expenditure and pricing characteristics.We extend our analysis to mechanisms that the system can introduce in order to have the message delivered to the destination with high probability within a given deadline and under energy constraints which bound the number of released copies per message. Finally, we apply our findings in order to devise decentralized forwarding algorithms that are rooted in the theory of stochastic approximations. Thus, we demonstrate that the ESS can be attained without complete knowledge of the system state and letting the source monitor number of released copies per message only. We provide extensive numerical results to validate the proposed scheme.     

Synthesis from component libraries

Synthesis is the automated construction of a system from its specification. In the classical temporal synthesis algorithms, it is always assumed the system is “constructed from scratch” rather than “composed” from reusable components. This, of course, rarely happens in real life. In real life, almost every non-trivial commercial system, either in hardware or in software system, relies heavily on using libraries of reusable components. Furthermore, other contexts, such as web-service orchestration, can be modeled as synthesis of a system from a library of components. In this work, we define and study the problem of LTL synthesis from libraries of reusable components. We define two notions of composition: data-flow composition, for which we prove the problem is undecidable, and control-flow composition, for which we prove the problem is 2EXPTIME-complete. As a side benefit, we derive an explicit characterization of the information needed by the synthesizer on the underlying components. This characterization can be used as a specification formalism between component providers and integrators.     

An Efficient Schema Transformation Technique for Data Migration from Relational to Column-Oriented Databases

Data transformation is the core process in migrating database from relational database to NoSQL database such as column-oriented database. However, there is no standard guideline for data transformation from relational database to NoSQL database. A number of schema transformation techniques have been proposed to improve data transformation process and resulted better query processing time when compared to the relational database query processing time. However, these approaches produced redundant tables in the resulted schema that in turn consume large unnecessary storage size and produce high query processing time due to the generated schema with redundant column families in the transformed column-oriented database. In this paper, an efficient data transformation technique from relational database to column-oriented database is proposed. The proposed schema transformation technique is based on the combination of denormalization approach, data access pattern and multiple-nested schema. In order to validate the proposed work, the proposed technique is implemented by transforming data from MySQL database to HBase database. A benchmark transformation technique is also performed in which the query processing time and the storage size are compared. Based on the experimental results, the proposed transformation technique showed significant improvement in terms query processing time and storage space usage due to the reduced number of column families in the column-oriented database.     

Active Sites Engineering toward Superior Carbon‐Based Oxygen Reduction Catalysts via Confinement Pyrolysis

Developing efficient and low‐cost defective carbon‐based catalysts for the oxygen reduction reaction (ORR) is essential to metal–air batteries and fuel cells. Active sites engineering toward these catalysts is highly desirable but challenging to realize boosted catalytic performance. Herein, a sandwich‐like confinement route to achieve the controllable regulation of active sites for carbon‐based catalysts is reported. In particular, three distinct catalysts including metal‐free N‐doped carbon (NC), single Co atoms dispersed NC (Co–N–C), and Co nanoparticles‐contained Co–N–C (Co/Co–N–C) are controllably realized and clearly identified by synchrotron radiation‐based X‐ray spectroscopy. Electrochemical measurements suggest that the Co/Co–N–C catalyst delivers optimized ORR performance due to the rich Co–N_x active sites and their synergistic effect with metallic Co nanoparticles. This work provides deep insight for rationally designing efficient ORR catalyst based on active sites engineering.     

From object-process analysis to object-process design

The object-process methodology incorporates the system static-structural and dynamic-procedural aspects into a single, unified model. This unification bridges the gap that separates the static, object model from the dynamic, behavior, state, or function-oriented models found in many current object oriented methodologies. In this work we concentrate on the transition from object-process analysis to design within the development of information systems. We use a detailed case study as a running example throughout the paper to demonstrate how the structure-behavior unification, which characterizes object-process analysis, is carried on to object-process design. The case study first applies object-process analysis to perform the analysis stage. The sequence of steps that constitutes the design is then discussed and demonstrated through the case study. The design is divided into two phases: the analysis refinement phase and the implementation-dependent phase. Analysis refinement is concerned with adding details to the analysis results which are beyond the interest of the analysis itself, yet they are not related with a particular implementation. The implementation-dependent phase is concerned with code-level design, which takes place after specific implementation details, such as programming language, data organization, and user interface, have been made during the strategic design.     

Expert-driven genetic algorithms for simulating evaluation functions

In this paper we demonstrate how genetic algorithms can be used to reverse engineer an evaluation function’s parameters for computer chess. Our results show that using an appropriate expert (or mentor), we can evolve a program that is on par with top tournament-playing chess programs, outperforming a two-time World Computer Chess Champion. This performance gain is achieved by evolving a program that mimics the behavior of a superior expert. The resulting evaluation function of the evolved program consists of a much smaller number of parameters than the expert’s. The extended experimental results provided in this paper include a report on our successful participation in the 2008 World Computer Chess Championship. In principle, our expert-driven approach could be used in a wide range of problems for which appropriate experts are available.     

2009 CAV award announcement

The 2009 CAV (Computer-Aided Verification) award was presented to seven individuals who made major advances in creating high-performance Boolean satisfiability solvers. This annual award recognizes a specific fundamental contribution or series of outstanding contributions to the CAV field.     

Wald's mighty maximin: a tutorial

Ever since its appearance on the scene in the 1940s, in the then nascent field of statistical decision theory, Wald's maximin paradigm has played a vital role in many disciplines in the treatment of nonprobabilistic uncertainty, both as a tool of thought and as a practical instrument. In fact, in some fields, such as modern robust optimization, Wald's paradigm dominates the scene. It is important to note that this paradigm's preeminence in many fields continues unabated, despite its obvious limitations and the criticism that had been and continues to be leveled at it. So, in this tutorial we examine the methodological aspects of this stalwart of decision theory from the viewpoint of robust decision‐making, paying special attention to its obvious and not so obvious limitations and to its relation to other maximin paradigms.