Sharif Digital Repository

In cloud computing, services play key roles. Services are well defined and autonomous components. Nowadays, the demand of using Fuzzy inference as a service is increasing in the domain of complex and critical systems. In such systems, along with the development of the software, the cost of detecting and fixing software defects increases. Therefore, using formal methods, which provide clear, concise, and mathematical interpretation of the system, is crucial for the design of these Fuzzy systems. To obtain this goal, we introduce the Fuzzy Inference Cloud Service (FICS) and propose a novel discipline for formal modeling of the FICS. The FICS provides the service of Fuzzy inference to the... 

A potential peculiarity of software systems is that a large number of soft-errors are inherently derated (masked) at the software level. The rate of error-deration may depend on the type of algorithms and data structures used in the software. This paper investigates the effects of the underlying algorithms of programs on the rate of error-deration. Eight different benchmark programs were used in the study; each of them was implemented by four different algorithms, i.e. divide-and-conquer, dynamic, backtracking and branch-and-bound. About 10,000 errors were injected into each program in order to quantify and analyze the error-derating capabilities of different algorithm-designing- techniques.... 

The increasing demand on execution of large-scale Cloud workflow applications which need a robust and elastic computing infrastructure usually lead to the use of high-performance Grid computing clusters. As the owners of Cloud applications expect to fulfill the requested Quality of Services (QoS) by the Grid environment, an adaptive scheduling mechanism is needed which enables to distribute a large number of related tasks with different computational and communication demands on multi-cluster Grid computing environments. Addressing the problem of scheduling large-scale Cloud workflow applications onto multi-cluster Grid environment regarding the QoS constraints declared by application's... 

Wireless sensor networks (WSNs) comprise a large number of small sensor nodes scattered across limited geographical areas. The nodes in such networks carry sources of limited and mainly unchangeable energy. Therefore, it is necessary that these networks operate under energy efficient protocols and structures. Energy efficient clustering algorithms have been developed to reduce the networks energy consumption and extend its lifetime. This paper presents an innovative cluster-based communication protocol for WSNs. In order to reduce communication overhead, the authors propose an Energy Aware Clustering Hierarchy Protocol that creates a multi-level hierarchical structure to adequately route and... 

The semantic sensor web adds semantic web technologies such as ontology to sensor network. Semantic technologies can help the better management of query and data aggregation of the sensor network. So far, several ontologies have been presented for the semantic presentation of sensor networks concepts. However, applications and end-users require physical entities information rather than technical details and information regarding sensors and sensor network. This paper semantically models physical entities whose information is collected by sensor networks at a level higher than sensors and their observations. Hence, first, an ontology is presented for semantically modelling physical entities... 

In a wireless sensor network, with numerous sensor nodes, a huge volume of data is produced. For the massive data generated by sensor networks to be understood by the machine, semantic web technologies such as ontology need to be applied. On the other hand, since the end users intend to access the high-level physical entities information monitored by the sensor network, the applicability of sensor networks can be enhanced through proposing a strategy to extract the data based on entities instead of extracting the raw sensor data. Hence, in this paper firstly, ontology will be presented for physical entities semantic modelling (PESM). Secondly, an appropriate strategy will be offered to... 

The semantic sensor web adds semantic web technologies such as ontology to sensor network. Semantic technologies can help the better management of query and data aggregation of the sensor network. So far, several ontologies have been presented for the semantic presentation of sensor networks concepts. However, applications and end-users require physical entities information rather than technical details and information regarding sensors and sensor network. This paper semantically models physical entities whose information is collected by sensor networks at a level higher than sensors and their observations. Hence, first, an ontology is presented for semantically modelling physical entities... 

Today, cloud computing has developed as one of the important emergent technologies in communication and Internet. It offers on demand, pay per use access to infrastructure, platforms, and applications. Due to the increase in its popularity, the huge number of requests need to be handled in an efficient manner. Task scheduling as one of the challenges in the cloud computing supports the requests for assigning a particular resource so as to perform effectively. In the resource management, task scheduling is performed where there is the dependency between tasks. Many approaches and case studies have been developed for the scheduling of these tasks. Up to now, a systematic literature review... 

Routing is a very important matter for ad hoc networks which means choosing the suitable and correct path for transferring data from a source node to a destination node. Today, the methods using several paths for routing are attended very much. In this paper, a new plan in multiple paths On-Demand Distance Vector (AODV) routing is presented which its routing is based on the distance of nodes from the center of the network. In this new routing algorithm, the number of dropped packets will be decreased and indeed this will be happened with more balancing in the network. This claim will be proved by some simulations using ns2 (network simulator)  

In the last decade, the scale of heterogeneous computing (HC) systems such as heterogeneous cloud computing environments was growing like never before. So network failures are unavoidable in such systems, which affect system reliability. Since the task scheduling algorithm in HC is challenging, we investigate a new reliability-aware task scheduling algorithm (RATSA) in this paper. RATSA is designed to schedule tasks on directed acyclic graphs (DAGs) by using the shuffled frog-leaping algorithm (SFLA) and genetic algorithm (GA) as evolutionary algorithms. The population-based SFLA-GA is applied to optimize makespan in the RATSA as an NP-complete problem. Moreover, the proposed algorithm... 

Rapid and exponential development of textual data in recent years has yielded to the need for automatic text summarization models which aim to automatically condense a piece of text into a shorter version. Although various unsupervised and machine learning-based approaches have been introduced for text summarization during the last decades, the emergence of deep learning has made remarkable progress in this field. However, deep learning-based text summarization models are still in their early steps of development and their potential has yet to be fully explored. Accordingly, a novel abstractive summarization model is proposed in this paper which utilized the combination of convolutional... 

In the last decade, the scale of heterogeneous computing (HC) systems such as heterogeneous cloud computing environments was growing like never before. So network failures are unavoidable in such systems, which affect system reliability. Since the task scheduling algorithm in HC is challenging, we investigate a new reliability-aware task scheduling algorithm (RATSA) in this paper. RATSA is designed to schedule tasks on directed acyclic graphs (DAGs) by using the shuffled frog-leaping algorithm (SFLA) and genetic algorithm (GA) as evolutionary algorithms. The population-based SFLA-GA is applied to optimize makespan in the RATSA as an NP-complete problem. Moreover, the proposed algorithm... 

Shear wall panels, including cold-formed steel frames and its attached sheathing, are common lateral load resisting systems of cold-formed steel structures. In this paper, the finite element method is used to study the lateral performance of shear wall panels. The finite element model is validated against experimental results of other researchers. Using the validated model, a parametric study is described to determine strength, drift and seismic behavior of the shear wall panels. Based on the results, it is concluded that the initial stiffness and ultimate lateral strength are dramatically affected by the thickness of the frame members, type of sheathing material, edge screw spacing, height... 

Providing an efficient resource allocation mechanism is a challenge to computational grid due to large-scale resource sharing and the fact that Grid Resource Owners (GROs) and Grid Resource Consumers (GRCs) may have different goals, policies, and preferences. In a real world market, various economic models exist for setting the price of grid resources, based on supply-and-demand and their value to the consumers. In this paper, we discuss the use of multiagent-based negotiation model for interaction between GROs and GRCs. For realizing this approach, we designed the Market- and Behavior-driven Negotiation Agents (MBDNAs). Negotiation strategies that adopt MBDNAs take into account the... 

This paper presents a new negotiation model for designing Market- and Behavior-driven Negotiation Agents (MBDNAs) that address computational grid resource allocation problem. To determine the amount of concession for each trading cycle, the MBDNAs are guided by six factors: (1) number of negotiator's trading partners, (2) number of negotiator's competitors, (3) negotiator's time preference, (4) flexibility in negotiator's trading partner's proposal, (5) negotiator's proposal deviation from the average of its trading partners proposals, and (6) previous concession behavior of negotiator's trading partner. In our experiments, we compare grid resource consumer (GRC) of type MBDNAs (respectively... 

Soft-errors are increasingly considered as a major cause for computer system failures. Software techniques are used as cost-effective and flexible techniques to tolerate soft-errors but the introduced overhead is not acceptable in some safety-critical real-time systems. The identification of the program blocks and protecting only vulnerable blocks against soft-errors reduces the performance overhead. In this paper, we present a genetic algorithm to identify the vulnerable program blocks as well as the derating program blocks against soft-errors. Then, only vulnerable blocks are protected by some software-based soft-error tolerance techniques to achieve a lower performance and space overhead.... 

Emerging STT-MRAM memories are promising alternatives for SRAM memories to tackle their low density and high static power consumption, but impose high energy consumption for reliable read/write operations. However, absolute data integrity is not required for many approximate computing applications, allowing energy savings with minimal quality loss. This paper proposes QuARK, a hardware/software approach for trading reliability of STT-MRAM caches for energy savings in the on-chip memory hierarchy of multi- A nd many-core systems running approximate applications. In contrast to SRAM-based cache-way-level actuators, QuARK utilizes fine-grained cache-line-level actuation knobs with different... 

In this paper, dynamic programming alignment is replaced by a particle swarm optimization (PSO) procedure in time warping problem. The basic PSO is a very slow process to be applied to speech recognition application. In order to achieve a higher performance, by inspiring of PSO optimization methodology, we introduced a PSO Inspired Time warping Algorithm (PTW) that significantly increase the computational performance of time warping in alignments of long length massive data sets. As a main enhancement, a pruning strategy with an add-in controlling threshold is defined in PTW that causes a considerable reduction in recognition time, while maintaining the system accuracy comparing to DTW. ©... 

A novel high-level fault model to accelerate test process of on-chip communication structures for SoCs is proposed. To this end, bus components are modeled using a simple, yet efficient, graph-based technique and all possible faults on the graph nodes are probed. The proposed method is optimized in terms of test time. The method applies the same test process to all interconnects and components. Compared to the conventional stuck-at fault testing methods, our extensive simulations on the AMBA-AHB bus architecture reveal that our test method can help in achieving a significant test speed improvement  

In this study, we have investigated the use of electrodeposited Au-Pt nanoparticles (AuPtNPs) on indium tin oxide (ITO) for the detection of Hg2+ heavy ions in water samples. The mechanism of AuPtNP electrocrystallization on ITO glass in an aqueous solution containing 0.5 mM HAuCl4 + 0.5 mM H2PtCl6 is described for the first time. The nucleation mechanism of monometallic AuNPs on ITO was found to be progressive; however, a transition from progressive to instantaneous was observed for bimetallic AuPtNPs at elevated overpotentials. The modified ITOs were then assessed for the electrodetection of Hg2+ in aqueous media. It was shown by differential pulse voltammetry (DPV) that the sensitivity of...