Sharif Digital Repository

Climate change affects temperature, magnitude, and also the duration of the Urban Heat Island (UHI), which has severe impacts on the environment, communities, and the people's lives. This study evaluates UHI formation in the city of Tehran (Iran) using a reliability framework, which is able to include related uncertainties into the modeling procedure. First, 2 km air temperature field from Weather and Research Forecasting (WRF) model is downscaled to a 50 m grid spacing using a probabilistic downscaling method, which combines inverse distance weighting (IDW) interpolation and a Bayesian regression model. This downscaling method not only can produce a long record of the fine resolution of the... 

Key predistribution in sensor networks refers to the problem of distributing secret keys among sensor nodes prior to deployment. Recently, many key predistribution schemes have been proposed for wireless sensor networks. To further improve these techniques, researchers have also proposed to use sensors' expected location information to help predistribution of keying materials. In this paper we propose a lightweight and scalable key establishment scheme for GPS-enabled wireless sensor networks. This scheme has little communication overhead and memory usage. Since communications and computations of key establishment schemes are done only once and when the network is begin initiated, actually... 

DSP algorithms are one of the most important components of modern embedded computer systems. These applications generally include fixed point and floating-point arithmetic operations and trigonometric functions which have long latencies and high power consumption. Nonetheless, DSP applications enjoy from some interesting characteristics such as tolerating slight loss of accuracy and high degree of value locality which can be exploited to improve their power consumption and performance. In this paper, we present an application-specific result-cache that aims to reduce the power consumption and latency of DSP algorithms by reusing the results of the arithmetic operations executed on the same... 

DSP algorithms are one of the most important components of modern embedded computer systems. These applications generally include fixed point and floating-point arithmetic operations and trigonometric functions which have long latencies and high power consumption. Nonetheless, DSP applications enjoy from some interesting characteristics such as tolerating slight loss of accuracy and high degree of value locality which can be exploited to improve their power consumption and performance. In this paper, we present an application-specific result-cache that aims to reduce the power consumption and latency of DSP algorithms by reusing the results of the arithmetic operations executed on the same... 

An important approach to reduce power dissipation is reducing the number of instructions executed by the processor. To achieve this goal, this paper introduces a novel instruction scheduling algorithm that executes an instruction only when its result is required by another instruction. In this manner, it not only does not execute useless instructions, but also reduces the number of instructions executed after a mispredicted branch. The cost of the extra hardware is 161 bytes for 128 instruction window size. Measurements done using SPEC CPU 2000 benchmarks show that the average number of executed instructions is reduced by 13.5% while the average IPC is not affected. Copyright 2008 ACM  

The critical issue in designing correlated data networks like Wireless Sensor Networks is to minimize the total cost of data transmission in the network, and decrease the amount of data flow. The problem of finding optimal aggregation tree for correlated data gathering in single sink network is considered as an NP-Complete problem and hence heuristic methods are usually applied to solve it[1]. In this paper, we apply genetic algorithm (GA) to solve the problem. In our method, we improve the performance of genetic search by selecting proper initial population. This initial population is determined in two ways, by using Prime's algorithm, and shortest path tree. The main issue is to regard... 

The purpose of the present study is to investigate the thermal performance of a photovoltaic/thermal system, integrated with phase change materials in porous medium. For this purpose, a metal foam was employed as porous medium and the performance of five different PCMs, as organic and inorganic, were examined as well. Moreover, the effects of different key parameters such as the mass flow rate, solar irradiance, inlet water temperature and inclination were studied. Finally, the simulation results were compared with a water-cooled photovoltaic/thermal without incorporating PCMs and porous medium, and thermal performance of the three PV/T cases were reported. The highest thermal efficiency of... 

Authentication is an essential security requirement in safety-related vehicle-to-vehicle applications in VANETs. TESLA is one of the most popular broadcast source authentication protocols proposed and standardized for this purpose. Having strict time constraints and being prone to GPS synchronization errors make the analysis of this protocol challenging. In this paper, we utilize a timed model checking approach based on timed colored Petri nets to model and verify TESLA considering its time-sensitive behaviors. In this way, we show how neglecting timing aspects in protocol design and in protocol modelling can lead to successfully launched attacks and erroneous analyses respectively, and how... 

The growing number of Internet users and the prevalence of web applications make it necessary to deal with very complex software and applications in the network. This results in an increasing number of new vulnerabilities in the systems, and leading to an increase in cyber threats and, in particular, zero-day attacks. The cost of generating appropriate signatures for these attacks is a potential motive for using machine learning-based methodologies. Although there are many studies on using learning-based methods for attack detection, they generally use extracted features and overlook raw contents. This approach can lessen the performance of detection systems against content-based attacks... 

The growing number of Internet users and the prevalence of web applications make it necessary to deal with very complex software and applications in the network. This results in an increasing number of new vulnerabilities in the systems, and leading to an increase in cyber threats and, in particular, zero-day attacks. The cost of generating appropriate signatures for these attacks is a potential motive for using machine learning-based methodologies. Although there are many studies on using learning-based methods for attack detection, they generally use extracted features and overlook raw contents. This approach can lessen the performance of detection systems against content-based attacks... 

In this paper we evaluate the performance of Energy Management and Building Automation Systems in smart environment using wireless sensor network. We describe some aspects of smart grid and then explain the related communication models of smart meters and building management or energy management systems in a smart home. We propose three models, then we compare these models and we select a model for our test bed. We implement the selected model in real environment using wireless sensor network. We analyse network delay to find out whether wireless sensor network is useful or not. With proposed model, we can save up to 57% in energy cost. Also, we develop In- home display to inform customers... 

The main challenge of an intrusion detection system (IDS) is detecting novelties (i.e., zero-day attacks) in addition to generating a report about the known attacks (i.e., classifying known attacks). Another challenge of an IDS is the adaptation to the detected novelties. For this purpose, it needs sufficient labeled samples of the new attacks. On the other hand, the labeling procedure is a time-consuming task for the security expert teams. This paper proposes a DL-based IDS framework adaptable to new attacks, consisting of different phases. The first phase uses deep learning-based open set recognition methods to identify unknown samples (i.e., new attacks), and make a report from different... 

Although several analytical models have been proposed for wireless sensor networks (WSNs) with different capabilities, very few of them consider the effect of general service distribution as well as design constraints on network performance. This paper presents a new analytical model to compute message latency in a WSN with loop-free Bellman Ford routing strategy. The model considers limited buffer size for each node using M/G/1/k queuing system. Also, contention probability and resource utilization are suitably modeled. The results obtained from simulation experiments confirm that the model exhibits a high degree of accuracy for various network configurations. © 2009 IEEE