Search

The Smart Grid is an advanced digital two-way power flow power system capable of self-healing, adaptive, resilient and sustainable with foresight for prediction under different uncertainties. In this paper, a survey on various Smart Grid enabling technologies, Smart Grid metering and communication, cloud computing in Smart Grid and Smart Grid applications are explored in detail. Opportunities and future of Smart Grid is also described in this paper. For Smart grid enabling technologies Smart meters, smart sensors, vehicle to grid, plug in hybrid electric vehicle technology, sensor and actuator networks are explored. Advanced metering infrastructure, intelligent electronic devices, phasor measurement units, wide area measurement systems, local area network, home access network, neighborhood area network, wide area networks and cloud computing are explored for Smart Grid metering and communication. Home and building automation, smart substation, feeder automation is explored for smart grid applications. Associations of initial studies for the next step in smart grid applications will provide an economic benefit for the authorities in the long term, and will help to establish standards to be compatible with every application so that all smart grid applications can be coordinated under the control of the same authorities. Therefore, this study is expected to be an important guiding source for researchers and engineers studying the smart grid. It also helps transmission and distribution system operators to follow the right path as they are transforming their classical grids to smart grids.

Concerns over environment and increased demand for energy have led the world to think about alternate energy sources such as the wind, hydro, solar and fuel cells. Out of these photovoltaic (PV) generation systems (PGS) become increasingly important all over the world due to its availability, cleanness, low maintenance cost, and inexhaustible nature. The probability of partial shading conditions (PSC) is also high for large PGS. Under PSC, the P–V curve of PGS exhibits multiple peaks, which reduces the effectiveness of conventional maximum power point tracking (MPPT) methods. In this paper, an improved particle swarm optimization (PSO) based MPPT algorithm for PGS operating under PSC is proposed. Conventional PSO is modified to meet practical consideration of PGS operating under PSC. Problem formulation, design details, and experimental results are discussed in detail. The proposed technique is independent of system, it is easy to implement, tracking efficiency is high and performance under PSC is good. The effectiveness of the proposed method is validated by analyzing the experimental results obtained from 110 W solar power generation systems.

Tree-based learning techniques are considered to be one of the best and most used supervised learning methods. Tree-based methods empower predictive models with high accuracy, stability, and ease of interpretation. Unlike linear models, they map non-linear relationships pretty well. These methods are adaptable at solving any kind of problem at hand (classification or regression). Methods like decision trees, random forest, gradient boosting are being widely used in all kinds of machine learning and data science problems. Hence, for every data analyst, it is important to learn these algorithms and use them for modeling. This chapter guide the learner to learn tree-based modeling techniques from scratch.

This paper demonstrates the implementation of a QPSK/ time division multiple access (TDMA) narrowband (NB) satellite receiver using short preamble-based synchronization in the presence of timing, frequency and phase offsets, and with additive white Gaussian noise (AWGN). The narrowband satellite communication (NB-SATCOM) system, which is mostly preferred for low-rate data transfer, is primarily affected by large carrier frequency offset (CFO). The implemented receiver uses a 32-symbol short preamble for synchronization of time, large frequency and phase, and it gives better bit error rate (BER) performance at low energy per bit to noise density ratio (E b /N 0 ). As the proposed design uses short preamble, it is able to achieve a high level of spectral efficiency with less computational complexity. The functional verification of the synchronization algorithm is done using Matlab simulations and the algorithm implementation uses fixed-point C. The receiver design has been implemented for 24 TDMA channels in Texas Instruments (TI) multi-core C66x DSPs.

The main aim of this paper is to provide the security for accessing the collaborative computing environment. Main thing here is using authentication method, users can access their collaborative environments. So normal authentication is not sufficient for collaborative environment, that is why here I am proposing two-factor authentication for collaborative environment.

This paper demonstrates a multi-core DSP-based implementation of variable data rate OQPSK/time division multiple access (TDMA) satellite receiver in the presence of timing, frequency and phase offsets, and with additive white Gaussian noise (AWGN). The implemented receiver uses a 64-bit short preamble for synchronization. It operates at a variable symbol rate of 220Ksps to 660Ksps and gives better bit error rate (BER) performance at low energy per bit to noise density ratio (E b /N 0 ). The proposed receiver operates at a carrier frequency offset upto 15% value normalized to symbol rate. Matlab simulations are used for functional verification of the synchronization algorithm and fixed-point C is used for algorithm implementation. The receiver design is prototyped for 12 TDMA channels in Texas Instruments (TI) multi-core C66x DSPs. The design and implementation of this receiver have been done for C-DOT indigenous satellite project.

This paper demonstrates the implementation of bit synchronization and delayed decision feedback equalization for Enhanced Data rates for GSM Evolution (EDGE) system on TMS320C6424 DSP. EDGE makes use of training sequence for channel estimation and inter symbol interference (ISI) cancellation by use of delayed decision feedback equalization. Modulated baseband in-phase (I) and quadrature (Q) signals are generated using Agilent E4438C Vector signal generator and faded using Agilent fading simulator, is used as input to the DSP. Bit Error Rate (BER) performance of uncoded bits for Packet Data Traffic Channel (PDTCH) meets the EDGE standards. Software implementation uses fixed-point C and Integrated Development Environment (IDE) used for development is code composer studio (CCS). Prototyped our design in Texas Instrument TMS320C6424 DSP and verified for all propagation models as per the EDGE standards. The design and hardware implementation of this Demodulator is done for C-DOT indigenous Shared GSM Radio Access Network (SGRAN) Base Transceiver Station (BTS) project.

Real time system is a system in which the computation not only depends on producing a correct output, but the output should be delivered within predetermine timing constraint called deadline. As humans, we handle scheduling issues every day. For example, a student must accomplish homework by the appropriate due date, a professor must complete the rough draft of a paper by the submission date, etc., where we have only one task to accomplish, meeting that deadline probably would be very simple. Our lives, however, contain many tasks that have deadlines tax forms, car inspections, meetings, classes, etc. Thus, we must use some sort of scheduling technique to “juggle” our various tasks, so that they all are completed by their appropriate deadlines. As a result, many scholars develop different static and dynamic scheduling algorithms, which are best suited for both uniprocessor and multiprocessors. This paper work will focus on proposing a new dynamic scheduling algorithm. Because, it is found that the well-known uniprocessor dynamic scheduling (EDF (earlier deadline first) and LLF (least slack time first)) algorithms have many context switching and many probability of overhead occurrence (deadline-tie and laxity-tie respectively) which will degrade the performance of the whole system. The paper proposes a dynamic scheduling algorithm that has low context switching and totally reduce the probability of overhead occurrence by combining the deadline and slack to give priority for each task in the ready queue.

As Internet and its technologies are improving with rapid pace, there are security threats growing with same pace. The malicious software such as worm is causing such threats to IT systems linked to information super highway. The worms are capable of replicating themselves and infect systems over network. Their traffic propagation can be detected by employing anti worm or virus software. However, there is a new type of worm that can camouflage itself so as to prevent anti worm software from identifying it. The difference between normal worm's traffic and C-worm's traffic can't be found when time domain is considered. However, in terms of frequency definitely it can be differentiated. Based on this hypothesis, this paper presents novel schemes such as PSD and SFM that are capable of differentiating the traffic of C-worm from background traffic. The empirical results revealed that our schemes are effecting in detecting camouflaging worms effectively besides identifying normal worms. Keywords - Traffic propagation, worm, camouflaging worm, time domain, and frequency domain. I. Introduction Worm is a word with broad meaning. It refers to any program which is malicious in nature. Such program could be a VIRUS, worm etc. They have common features which are also there with biological virus. The common features include that they replicate themselves and also propagate from one machine to another machine. The means of propagation is only through infected storage media and also networks of all kinds including those without wire. Active worms continuously strive to propagate themselves to other systems and make them insecure. This is a problem which has been around ever since the world came across malicious programs for the first time. Some worms include Slammer (2), Sasser (3) and Code-Red (1). Some worms will work together by forming bonnets and cause more damage to IT systems. The attacks made by such worms include DDoS; attack to obtain sensitive information; destroying data (5) and also put forth unwanted materials such as advertisements. Many such worms are commonly known as malware (malicious software). This includes virus as well. The virus could be boot sector virus, file virus, love virus, time bomb virus, Trojan virus and so on. There is enough evidence in the history that some people have made it their business to create malware and also solutions to prevent them. This is major problem in the world of computers. This man made evil will continue posing threats to IT systems and also cause the businesses to loose confidential information and thus loosing confidence and profits in the business (4), (6). Researchers also predicting the possibility of malicious programs such as bonnets to collaborate and cause more security threats to IT world. Such collaborated bonnets is known as super bots (7). As there were reports of worms causing major damage to IT systems, the past few years saw significant research in the area of worms. Worm detection and prevention is an essential task required by all systems involved in IT. Thus the presence of anti-worm software is felt and the same is done through research. The process of identifying the worms by observing their scan traffic much anti-worm software succeed in detecting and also preventing any damage to IT systems. The emergence of Internet and also other networking facilities and communication systems paved way for the increase of threats caused by worms. Studying different kinds of worms and their impact on the IT systems and also prevention techniques are to be given paramount importance. When a worm infects a system, it will propagate its traffic in the system to cause damage to its data. It also strives to propagate the traffic to other systems though infected storage media and networks to other systems in the real world. They keep on identifying IP addresses of systems in the world and infect them though the ways known to them. The common way they follow is generating scan traffic in the time domain and frequency domain. Thus they make all the systems attacked by worms vulnerable to security threats. There is a possibility of loosing companies' sensitive information that leads to collapse of business or losing in revenues in large scale. The patterns of the worms (2), (8), (9) are increasing day by day. The more patterns of worm propagation is known, the more possibility to detect and prevent them. The assumption of all software in the world that is sued to combat worms is that the worms generate scan traffic and try to replicate themselves and infect systems in the same network and remote networks. The patterns are generally having same characteristics so as to enable anti-worm to detect them. However, a new class of worm has come into existence. This new worm is capable of hiding its presence.

In the field of robotics, the two wheel mobile manipulator has the potential to perform wide range of applications. Balancing of the system becomes a bothering task due to the highly unstable nature of the system. Dynamics of wheeled mobile manipulator are derived by the basics of energy balance equation by approximating double inverted pendulum dynamics. Control method for balancing the two wheeled mobile manipulator using H-infinity controller (H∞) is discussed in the work. H-infinity control methods are developed to design systems which have the desired dynamic behavior and are robust with respect to perturbations. Settling time required to achieve stability of the system and maximum deviation from desired value using linear quadratic regulator (LQR) controller and H-infinity controller are compared. Designing and simulations are carried out to check the validity of the proposed method and the results prove the effectiveness of the proposed method.

Nowadays, Computer Networks tend to be large and diverse systems that communicate using wide selection of protocols. This complexity made the desire for more sophisticated tools to watch and troubleshoot network traffic. Network traffic monitoring is can be quite a network diagnostic tool that monitors local area networks and provides a graphical display of network statistics. While collecting information through the network's data stream, network monitor displays the source address of the computer that sent a frame onto the network, the destination address of the computer that received the frame and also the protocols employed to send the frame. The procedure through which network monitor collects this information is known as Capturing. Automatically, the network monitor gathers statistics on all of the frames it detects on the network into a capture buffer that is a reserved storage area in memory. To capture statistics on merely a specific subset of frames, we could discriminate these frames by designing a capture filter. To work with network monitor, the computer will need to have a network card that supports promiscuous mode. This paper targets on the usage of packet capturing library Jpcap for monitoring, analyzing and reporting Distributed Denial of Service (DDoS) Attacks.

Distributed Denial of Service (DDoS) attacks in the internet disrupts the availability of a service or resource. Massive Distributed DoS attacks have the potential to severely decrease backbone availability and can virtually detach a network from the Internet. Because of the seriousness of the problem many defense mechanisms have been proposed to combat these attacks. This paper presents a Multi-layered probabilistic model for DDoS attacks and evaluated the performance of the system. Furthermore, important features of each attack and defense system category are described and advantages and disadvantages of each proposed scheme are outlined. The goal of the paper is to place some order into the existing attack and defense mechanisms, so that a better understanding of DDoS attacks can be achieved and subsequently more efficient and effective algorithms, techniques and procedures to combat these attacks may be developed.

Web is a collection of inter-related files on one or more Web servers. Web mining is one of the mining technologies, which applies data mining techniques in large amount of web data to improve the web services. Wide Web provides every internet citizen with access to an abundance of information, but it becomes increasingly difficult to identify the relevant pieces of information. Research in web mining tries to address this problem by applying techniques from data mining and machine learning to Web data and documents. The Web Mining is an application of Data Mining. Without the internet, life would have been almost impossible. The data available on the web is so voluminous and heterogeneous that it becomes an essential factor to mine this available data to make it presentable, useful, and pertinent to a particular problem. Web mining deals with extracting these interesting patterns and developing useful abstracts from diversified sources. The present paper deals with a preliminary discussion of WEB mining, few key computer science contributions in the field of web mining and outlines some promising areas of future research.