Electronic Notes in Theoretical Computer Science最新文献

Answer Set Programming (ASP) is a successful rule-based formalism for modeling and solving knowledge-intense combinatorial (optimization) problems. Despite its success in both academic and industry, open challenges like automatic source code optimization, and software engineering remains. This is because a problem encoded into an ASP might not have the desired solving performance compared to an equivalent representation. Motivated by these two challenges, this paper has three main contributions. First, we propose a developing process towards a methodology to implement ASP programs, being faithful to existing methods. Second, we present ASP encodings that serve as the basis from the developing process. Third, we demonstrate the use of ASP to reverse the standard solving process. That is, knowing answer sets in advance, and desired strong equivalent properties, “we” exhaustively reconstruct ASP programs if they exist. This paper was originally motivated by the search of propositional formulas (if they exist) that represent the semantics of a new aggregate operator. Particularly, a parity aggregate. This aggregate comes as an improvement from the already existing parity (xor) constraints from xorro, where lacks expressiveness, even though these constraints fit perfectly for reasoning modes like sampling or model counting. To this end, this extended version covers the fundaments from parity constraints as well as the xorro system. Hence, we delve a little more in the examples and the proposed methodology over parity constraints. Finally, we discuss our results by showing the only representation available, that satisfies different properties from the classical logic xor operator, which is also consistent with the semantics of parity constraints from xorro.

We analyze the vertex-coloring problem restricted to planar graphs and propose to consider classic wheels and polyhedral wheels as basic patterns for the planar graphs. We analyze the colorability of the composition among wheels and introduce a novel algorithm based on three rules for the vertex-coloring problem. These rules are: 1) Selecting vertices in the frontier. 2) Processing subsumed wheels. 3) Processing centers of the remaining wheels. Our method forms a maximal independent set S₁ ⊂ V (G) consisting of wheel's centers, and a maximum number of vertices in the frontier of the planar graph. Thus, we show that if the resulting graph G′ = (G − S₁) is 3-colorable, then this implies the existence of a valid 4-coloring for G.

In this paper we present a modeling approach suitable for practical evaluation of the delays that may affect security monitoring systems in (multitenant) cloud based architecture, and in general to support professionals in planning and evaluating relevant parameters in dealing with new designs or migration projects. The approach is based on modularity and multiformalism techniques to manage complexity and guide designers in an incremental process, to help transferring technical knowledge into modeling practice and to help easing the use of simulation. We present a case study based on a real experience, triggered by a new legal requirement that Italian Public Administration should comply about their datacenters.

Different paradigms have been used to model the behaviour of pedestrians in a crowd. While some approaches analyze the modelization of crowd motion from a physical perspective, other techniques prefer to focus on similar abstractions following classic paradigms, such as mobile agents or cellular automata, or even from the point of view of social forces interaction. Particular interest has emerged around the topic of crowd behaviour under condition of stress caused by a dramatic event, such as an earthquake, a terrorist attack or a fire. This paper presents a novel approach including a GSPN to describe the behaviour of an individual, which is subsequently translated into a set of Markovian Agents. The model under study reproduces a scenario where a fire, developed in a closed environment, triggers erratic crowd behaviour. It is possible to perceive that a panic situation can be mitigated by enforcing certain measures involving human leaders or small embedded systems (such as Internet-of-things enabled devices), reducing the level of risk related to safety.

We evaluate energy consumption under unknown service demands using three policies: task assignment based on guessing size (TAGS), the shortest queue strategy and random allocation in a homogeneous environment. We modelled these policies using performance evaluation processing algebra (PEPA) to derive numerical solutions. Our results show that servers running under TAGS consumes more energy than other policies in terms of total energy consumption. In contrast, TAGS consumes less energy than random allocation in terms of energy per job when the arrival rate is high and the job size is variable.

In this paper we present two performance models of a web-based sales system, one without the presence of an attack and the other with the presence of a denial of service attack. Models are formulated using the PEPA formalism. The PEPA eclipse plug-in is used to support the creation of the PEPA models for the web-based sales system and the automatic calculation of the performance measures identified to evaluate the models. The evaluation of the models illustrates how the performance of the warehouse's sale is negatively affected by denial of service attack through preventing some or all customers' orders from being fulfilled. The resultant delay on selling perishable products would result on products being discarded.

Cyber-Physical Systems (CPS) are present in many settings addressing a myriad of purposes. Examples are Internet-of-Things (IoT) or sensing software embedded in appliances or even specialised meters that measure and respond to electricity demands in smart grids. Due to their pervasive nature, they are usually chosen as recipients for larger scope cyber-security attacks. Those promote system-wide disruptions and are directed towards one key aspect such as confidentiality, integrity, availability or a combination of those characteristics. Our paper focuses on a particular and distressing attack where coordinated malware infected IoT units are maliciously employed to synchronously turn on or off high-wattage appliances, affecting the grid's primary control management. Our model could be extended to larger (smart) grids, Active Buildings as well as similar infrastructures. Our approach models Coordinated Load-Changing Attacks (CLCA) also referred as GridLock or BlackIoT, against a theoretical power grid, containing various types of power plants. It employs Continuous-Time Markov Chains where elements such as Power Plants and Botnets are modelled under normal or attack situations to evaluate the effect of CLCA in power reliant infrastructures. We showcase our modelling approach in the scenario of a power supplier (e.g. power plant) being targeted by a botnet. We demonstrate how our modelling approach can quantify the impact of a botnet attack and be abstracted for any CPS system involving power load management in a smart grid. Our results show that by prioritising the type of power-plants, the impact of the attack may change: in particular, we find the most impacting attack times and show how different strategies impact their success. We also find the best power generator to use depending on the current demand and strength of attack.

In the area of Markovian quantitative modelling, compositional model specification techniques such as Stochastic Process Algebra are widely used. However, exploiting a model's compositional structure for efficient analysis is still a difficult problem and mostly limited to special cases. This paper addresses some important issues in the area of compositional model checking of Markovian models for models with Boucherie-type product form. It closes a long-standing gap concerning the question whether compositional model checking of so-called global time-unbounded Until formulas is possible. The answer to this turns out to be negative. The paper then turns to the area of model repair, i.e. the question of how to fix a model in case it violates a given requirement. Here another general result and a useful proposition for compositional model repair are provided.

We show how to obtain stochastic bounds for the strong stochastic ordering and the concave ordering of the maximal flow in a network where the capacities are non negative discrete random variables. While the deterministic problem is polynomial, the stochastic version with discrete random variables is NP-hard. The monotonicity of the Min-Cut problem for these stochastic orderings allows us to simplify the input distributions and obtain bounds on the results. Thus we obtain a tradeoff between the complexity of the computations and the precision of the bounds. We illustrate the approach with some examples.

The Eilenberg-Kelly theorem states that a category $C$ with an object I and two functors $\otimes :C\times C\to C$ and $⊸:C^{\mathrm{op}}\times C\to C$ related by an adjunction $-\otimes B⊣B⊸-$ natural in B is monoidal iff it is closed and moreover the adjunction holds internally. We dissect the proof of this theorem and observe that the necessity for a side condition on closedness arises because the standard definition of closed category is left-skew in regards to associativity. We analyze Street's observation that left-skew monoidality is equivalent to left-skew closedness and establish that monoidality is equivalent to closedness unconditionally under an adjusted definition of closedness that requires normal associativity. We also work out a definition of right-skew closedness equivalent to right-skew monoidality. We give examples of each type of structure; in particular, we look at the Kleisli category of a left-strong monad on a left-skew closed category and the Kleisli category of a lax closed monad on a right-skew closed category. We also view skew and normal monoidal and closed categories as special cases of skew and normal promonoidal categories and take a brief look at left-skew prounital-closed categories.