IEEE Final Year Projects 2011-2012 :: Grid Computing:: Elysium Technologies Pvt Ltd

Elysium Technologies Private Limited ISO 9001:2008 A leading Research and Development Division Madurai | Chennai | Trichy | Coimbatore | Kollam| Singapore Website: elysiumtechnologies.com, elysiumtechnologies.info Email: [email protected]

IEEE Final Year Project List 2011-2012

Madurai Elysium Technologies Private Limited

230, Church Road, Annanagar,

Madurai , Tamilnadu – 625 020.

Contact : 91452 4390702, 4392702, 4394702.

eMail: [email protected]

Trichy Elysium Technologies Private Limited

3rd

Floor,SI Towers,

15 ,Melapudur , Trichy,

Tamilnadu – 620 001.

Contact : 91431 - 4002234.


Kollam Elysium Technologies Private Limited

Surya Complex,Vendor junction,

kollam,Kerala – 691 010.

Contact : 91474 2723622.


A b s t r a c t GRID COMPUTING 2011 - 2012

01 A Dual Framework and Algorithms for Targeted Online Data Delivery

A variety of emerging online data delivery applications challenge existing techniques for data delivery to human users,

applications, or middleware that are accessing data from multiple autonomous servers. In this paper, we develop a

framework for formalizing and comparing pull-based solutions and present dual optimization approaches. The first

approach, most commonly used nowadays, maximizes user utility under the strict setting of meeting a priori constraints on

the usage of system resources. We present an alternative and more flexible approach that maximizes user utility by

satisfying all users. It does this while minimizing the usage of system resources. We discuss the benefits of this latter

approach and develop an adaptive monitoring solution Satisfy User Profiles (SUPs). Through formal analysis, we identify

sufficient optimality conditions for SUP. Using real (RSS feeds) and synthetic traces, we empirically analyze the behavior of

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SUP under varying conditions. Our experiments show that we can achieve a high degree of satisfaction of user utility when

the estimations of SUP closely estimate the real event stream, and has the potential to save a significant amount of system

resources. We further show that SUP can exploit feedback to improve user utility with only a moderate increase in resource

utilization.

02 A Multidimensional Critical State Analysis for Detecting Intrusions in SCADA Systems

A relatively new trend in Critical Infrastructures (e.g., power plants, nuclear plants, energy grids, etc.) is the massive

migration from the classic model of isolated systems, to a system-of-systems model, where these infrastructures are

intensifying their interconnections through Information and Communications Technology (ICT) means. The ICT core of

these industrial installations is known as Supervisory Control And Data Acquisition Systems (SCADA). Traditional ICT

security countermeasures (e.g., classic firewalls, anti-viruses and IDSs) fail in providing a complete protection to these

systems since their needs are different from those of traditional ICT. This paper presents an innovative approach to

Intrusion Detection in SCADA systems based on the concept of Critical State Analysis and State Proximity. The theoretical

framework is supported by tests conducted with an Intrusion Detection System prototype implementing the proposed

detection approach.

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03 An Event-Driven Demand Response Scheme for Power System Security Enhancement

Demand response has become a key feature of the future smart grid. In addition to having advanced communication and

computing infrastructures, a successful demand response program must respond to the needs of a power system. In other

words, the efficiency and security of a power system dictate the locations, amounts and speeds of the load reductions of a

demand response program. In this paper, we propose an event-driven emergency demand response scheme to prevent a

power system from experiencing voltage collapse. A technique to design such a scheme is presented. This technique is

able to provide key setting parameters such as the amount of demand reductions at various locations to arm the demand

response infrastructure. The validity of the proposed technique has been verified by using several test power systems.

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04 Data Replication in Data Intensive Scientific Applications with Performance Guarantee

Data replication has been well adopted in data intensive scientific applications to reduce data file transfer time and

bandwidth consumption. However, the problem of data replication in Data Grids, an enabling technology for data intensive

applications, has proven to be NP-hard and even non approximable, making this problem difficult to solve. Meanwhile, most

of the previous research in this field is either theoretical investigation without practical consideration, or heuristics-based

with little or no theoretical performance guarantee. In this paper, we propose a data replication algorithm that not only has a

provable theoretical performance guarantee, but also can be implemented in a distributed and practical manner.

Specifically, we design a polynomial time centralized replication algorithm that reduces the total data file access delay by at

least half of that reduced by the optimal replication solution. Based on this centralized algorithm, we also design a

distributed caching algorithm, which can be easily adopted in a distributed environment such as Data Grids. Extensive

simulations are performed to validate the efficiency of our proposed algorithms. Using our own simulator, we show that our

centralized replication algorithm performs comparably to the optimal algorithm and other intuitive heuristics under different

network parameters. Using GridSim, a popular distributed Grid simulator, we demonstrate that the distributed caching

technique significantly outperforms an existing popular file caching technique in Data Grids, and it is more scalable and

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adaptive to the dynamic change of file access patterns in Data Grids.

05 Dynamic Monitoring and Decision Systems for Enabling Sustainable Energy Services

This paper concerns the role of smart grids comprising man-made electric power networks and their supporting information

communications technology (ICT) as enablers of sustainable energy services. A proposed socio-ecological energy system

(SEES) framework used to characterize the corelevel subsystems (resources, users, and governance) in terms of second-

level and deeper level variables is motivated by the more general multilevel nested socio-ecological system (SES)

framework. Second-level and deeper level variables are introduced as a means of characterizing how sustainable a SEES is

likely to be by assessing their characteristics. Given vast spatial and temporal complexities in a typical SEES, it becomes

necessary to enhance the physical power network with just-in-time (JIT), just-in-place (JIP), and just-in-context (JIC)

functionalities. These, in turn, support sustainable energy services by aligning temporal, spatial, and contextual

characteristics of resources and users. We refer to the ICT implementation in support of these functionalities as dynamic

monitoring and decision systems (DYMONDS). The tradeoffs between the ability of the SEES to ensure sustainable services

and the complexity of the supporting smart grid are discussed for several representative energy system architectures.

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06 Fault-Tolerant and Scalable Key Management for Smart Grid

In this paper, we study the problem of secure keymanagement for smart grid. Since existing key management schemes are

not suitable for deployment in smart grid, in this paper, we propose a novel key management scheme which combines

symmetric key technique and elliptic curve public key technique. The symmetric key scheme is based on the Needham-

Schroeder authentication protocol. We show that the known threats including the man-in-the-middle attack and the replay

attack can be effectively eliminated under the proposed scheme. The advantages of the new key management scheme

include strong security, scalability, fault-tolerance, accessibility, and efficiency.

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07 Feasibility Analysis of the Positioning of Superconducting Fault Current Limiters for the Smart Grid Application Using Simulink

and SimPowerSystem

One of the most important topics regarding the application of superconducting fault current limiters (SFCL) for upcoming

smart grid is related to its possible effect on the reduction of abnormal fault current and the suitable location in the micro

grids. Due to the grid connection of the micro grids with the current power grids, excessive fault current is a serious

problem to be solved for successful implementation of micro grids. However, a shortage of research concerning the location

of SFCL in micro grid is felt. In this work, a resistive type SFCL model was implemented by integrating Simulink and

SimPowerSystem blocks in Matlab. The designed SFCL model could be easily utilized for determining an impedance level of

SFCL according to the fault-current-limitation requirements of various kinds of the smart grid system. In addition, typical

smart grid model including generation, transmission and distribution network with dispersed energy resource was modeled

to determine the location and the performance of the SFCL. As for a dispersed energy resource, 10 MVA wind farm was

considered for the simulation. Three phase faults have been simulated at different locations in smart grid and the effect of

the SFCL and its location on the wind farm fault current was evaluated. Consequently, the optimum arrangement of the SFCL

location in Smart Grid with renewable resources has been proposed and its remarkable performance has been suggested.

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08 Grid Service Reliability Modeling and Optimal Task Scheduling Considering Fault Recovery

There has been quite some research on the development of tools and techniques for grid systems, yet some important

issues, e.g., grid service reliability and task scheduling in the grid, have not been sufficiently studied. For some grid services

which have large subtasks requiring time-consuming computation, the reliability of grid service could be rather low. To

resolve this problem, this paper introduces Local Node Fault Recovery (LNFR) mechanism into grid systems, and presents

an in-depth study on grid service reliability modeling and analysis with this kind of fault recovery. To make LNFR mechanism

practical, some constraints, i.e. the life times of subtasks, and the numbers of recoveries performed in grid nodes, are

introduced; and grid service reliability models under these practical constraints are developed. Based on the proposed grid

service reliability model, a multi-objective task scheduling optimization model is presented, and an ant colony optimization

(ACO) algorithm is developed to solve it effectively. A numerical example is given to illustrate the influence of fault recovery

on grid service reliability, and show a high efficiency of ACO in solving the grid task scheduling problem.

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09 GRISSOM Platform: Enabling Distributed Processing and Management of Biological Data Through Fusion of Grid and Web Technologies

Transcriptomic technologies have a critical impact in the revolutionary changes that reshape biological research. Through

the recruitment of novel high-throughput instrumentation and advanced computational methodologies, an unprecedented

wealth of quantitative data is produced. Microarray experiments are considered high-throughput, both in terms of data

volumes (data intensive) and processing complexity (computationally intensive). In this paper, we present grids for in silico

systems biology and medicine (GRISSOM), a web-based application that exploits GRID infrastructures for distributed data

processing and management, of DNA microarrays (cDNA, Affymetrix, Illumina) through a generic, consistent, computational

analysis framework. GRISSOM performs versatile annotation and integrative analysis tasks, through the use of third-party

application programming interfaces, delivered as web services. In parallel, by conforming to service-oriented architectures,

it can be encapsulated in other biomedical processing workflows, with the help of workflow enacting software, like Taverna

Workbench, thus rendering access to its algorithms, transparent and generic. GRISSOM aims to set a generic paradigm of

efficient metamining that promotes translational research in biomedicine, through the fusion of grid and semantic web

computing technologies.

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Contact : 91474 2723622.


10 Local Restoration With Multiple Spanning Trees in Metro Ethernet Networks

Ethernet is becoming a preferred technology to be extended to metropolitan area networks (MANs) due to its low cost,

simplicity, and ubiquity. However, current Ethernet lacks a fast failure recovery mechanism as it reconstructs the spanning

tree after the failure is detected, which commonly requires tens of seconds. Some fast failure-handling methods based on

multiple spanning trees have been proposed in the literature, but these approaches are either centralized or require periodic

message broadcasting over the entire network. In this paper, we propose a local restoration mechanism for metro Ethernet

using multiple spanning trees, which is distributed and fast and does not need failure notification. Upon failure of a single

link, the upstream switch locally restores traffic to preconfigured backup spanning trees. We propose two restoration

approaches, connection-based and destination-based, to select backup trees. We formulate the tree preconfiguration

problem that includes working spanning tree assignment and backup spanning tree configuration. We prove that the

preconfiguration problem is NP-complete and develop an integer linear programming model. We also develop heuristic

algorithms for each restoration approach to reduce the computation complexity. To evaluate the effectiveness of our

heuristic algorithms, we carry out the simulation on grid and random networks. The simulation results show that our

heuristic algorithms have comparable performance close to the optimal solutions, and both restoration approaches can

efficiently utilize the network bandwidth to handle single link failures.

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11 Modeling Load Redistribution Attacks in Power Systems

State estimation is a key element in today’s power systems for reliable system operation and control. State estimation

collects information from a large number of meter measurements and analyzes it in a centralized manner at the control

center. Existing state estimation approaches were traditionally assumed to be able to tolerate and detect random bad

measurements. They were, however, recently shown to be vulnerable to intentional false data injection attacks. This paper

fully develops the concept of load redistribution (LR) attacks, a special type of false data injection attacks, and analyzes their

damage to power system operation in different time steps with different attacking resource limitations. Based on damaging

effect analysis, we differentiate two attacking goals from the adversary’s perspective, i.e., immediate attacking goal and

delayed attacking goal. For the immediate attacking goal, this paper identifies the most damaging LR attack through a max-

min attacker-defender model. Then, the criterion of determining effective protection strategies is explained. The

effectiveness of the proposed model is tested on a 14-bus system. To the author’s best knowledge, this is the first work of

its kind, which quantitatively analyzes the damage of the false data injection attacks to power system operation and security.

Our analysis hence provides an in-depth insight on effective attack prevention with limited protection resource budget.

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12 Multicloud Deployment of Computing Clusters for Loosely Coupled MTC Applications

Cloud computing is gaining acceptance in many IT organizations, as an elastic, flexible, and variable-cost way to deploy

their service platforms using outsourced resources. Unlike traditional utilities where a single provider scheme is a common

practice, the ubiquitous access to cloud resources easily enables the simultaneous use of different clouds. In this paper, we

explore this scenario to deploy a computing cluster on the top of a multicloud infrastructure, for solving loosely coupled

Many-Task Computing (MTC) applications. In this way, the cluster nodes can be provisioned with resources from different

clouds to improve the cost effectiveness of the deployment, or to implement high-availability strategies. We prove the

viability of this kind of solutions by evaluating the scalability, performance, and cost of different configurations of a Sun Grid

Engine cluster, deployed on a multicloud infrastructure spanning a local data center and three different cloud sites: Amazon

EC2 Europe, Amazon EC2 US, and ElasticHosts. Although the testbed deployed in this work is limited to a reduced number

of computing resources (due to hardware and budget limitations), we have complemented our analysis with a simulated

infrastructure model, which includes a larger number of resources, and runs larger problem sizes. Data obtained by

simulation show that performance and cost results can be extrapolated to large-scale problems and cluster infrastructures.

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13 Parameter Exploration in Science and Engineering Using Many-Task Computing

scientific methods require the exploration of the parameter space of a system (some of which can be run in parallel on

distributed resources), and may involve complete state space exploration, experimental design, or numerical optimization

techniques. Many-Task Computing (MTC) provides a framework for performing robust design, because it supports the

execution of a large number of otherwise independent processes. Further, scientific workflow engines facilitate the

specification and execution of complex software pipelines, such as those found in real science and engineering design

problems. However, most existing workflow engines do not support a wide range of experimentation techniques, nor do they

support a large number of independent tasks. In this paper, we discuss Nimrod/K—a set of add in components and a new

run time machine for a general workflow engine, Kepler. Nimrod/K provides an execution architecture based on the tagged

dataflow concepts, developed in 1980s for highly parallel machines. This is embodied in a new Kepler “Director” that

supports many-task computing by orchestrating execution of tasks on on clusters, Grids, and Clouds. Further, Nimrod/K

provides a set of “Actors” that facilitate the various modes of parameter exploration discussed above. We demonstrate the

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power of Nimrod/K to solve real problems in cardiac science.

14 Performance Analysis of Cloud Computing Services for Many-Tasks Scientific Computing

Cloud computing is an emerging commercial infrastructure paradigm that promises to eliminate the need for maintaining

expensive computing facilities by companies and institutes alike. Through the use of virtualization and resource time

sharing, clouds serve with a single set of physical resources a large user base with different needs. Thus, clouds have the

potential to provide to their owners the benefits of an economy of scale and, at the same time, become an alternative for

scientists to clusters, grids, and parallel production environments. However, the current commercial clouds have been built

to support web and small database workloads, which are very different from typical scientific computing workloads.

Moreover, the use of virtualization and resource time sharing may introduce significant performance penalties for the

demanding scientific computing workloads. In this work, we analyze the performance of cloud computing services for

scientific computing workloads. We quantify the presence in real scientific computing workloads of Many-Task Computing

(MTC) users, that is, of users who employ loosely coupled applications comprising many tasks to achieve their scientific

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goals. Then, we perform an empirical evaluation of the performance of four commercial cloud computing services including

Amazon EC2, which is currently the largest commercial cloud. Last, we compare through trace-based simulation the

performance characteristics and cost models of clouds and other scientific computing platforms, for general and MTC-based

scientific computing workloads. Our results indicate that the current clouds need an order of magnitude in performance

improvement to be useful to the scientific community, and show which improvements should be considered first to address

this discrepancy between offer and demand.

15 Privilege Management Infrastructure for Virtual Organizations in Healthcare Grids

This paper is focused on the management of virtual organizations (VO) inside healthcare environments where grid

technology is used as middleware for a healthcare services-oriented architecture (HSOA). Some of the main tasks

considered for the provision of an efficient VOmanagement aremanagement of users, assignation of roles to users,

assignation of privileges to roles, and definition of resources access policies. These tasks are extremely close to privilege

management infrastructures (PMI), so we face VOmanagement services as part of the PMI supporting access control to

healthcare resources inside the HSOA. In order to achieve a completely open and interoperable PMI, we review and apply

standards of security and architectural design. Moreover, semantic technologies are introduced in decision points for

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access control allowing the management of a high degree of descriptors by means of ontologies and infer the decision

making through rules and reasoners.

16 Reputation-Based Trust for a Cooperative Agent-Based Backup Protection Scheme

This paper explores integrating a reputation-based trust mechanism with an agent-based backup protection system to help

protect against malicious or byzantine failures. A distributed cooperative trust system has the potential to add an additional

layer of protection designed to operate with greater autonomy. This trust component enables the agents in the system to

make assessments using an estimate of the trustworthiness of cooperating protection agents based on their responsiveness

and the consistency of their responses when compared with their peers. Results illustrate the improved decision-making

capability of agents who incorporate this cooperative trust method in the presence of failures in neighboring relays.

17 Reputation-Based Trust for a Cooperative Agent-Based Backup Protection Scheme

This paper explores integrating a reputation-based trust mechanism with an agent-based backup protection system to help

16






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protect against malicious or byzantine failures. A distributed cooperative trust system has the potential to add an additional

layer of protection designed to operate with greater autonomy. This trust component enables the agents in the system to

make assessments using an estimate of the trustworthiness of cooperating protection agents based on their responsiveness

and the consistency of their responses when compared with their peers. Results illustrate the improved decision-making

capability of agents who incorporate this cooperative trust method in the presence of failures in neighboring relays.

.18 Scheduling Grid Tasks in Face of Uncertain Communication Demands

Grid scheduling is essential to Quality of Service provisioning as well as to efficient management of grid resources. Grid

scheduling usually considers the state of the grid resources as well application demands. However, such demands are

generally unknown for highly demanding applications, since these often generate data which will be transferred during their

execution. Without appropriate assessment of these demands, scheduling decisions can lead to poor performance. Thus, it

is of paramount importance to consider uncertainties in the formulation of a grid scheduling problem. This paper introduces

the IPDT-FUZZY scheduler, a scheduler which considers the demands of grid applications with such uncertainties. The

scheduler uses fuzzy optimization, and both computational and communication demands are expressed as fuzzy numbers.

Its performance was evaluated, and it was shown to be attractive when communication requirements are uncertain. Its

efficacy is compared, via simulation, to that of a deterministic counterpart scheduler and the results reinforce its adequacy

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for dealing with the lack of accuracy in the estimation of communication demands.

19 Smart Grid Technologies for Autonomous Operation and Control

This paper presents a new smart grid infrastructure for active distribution systems that will allow continuous and accurate

monitoring of distribution system operations and customer utilization of electric power. The infrastructure allows a complete

array of applications. The paper discusses four specific applications: a) protection against downed conductors; b) load

levelization; c) loss minimization; and d) reliability enhancement.

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20 Strategic Protection Against Data Injection Attacks on Power Grids

Data injection attacks to manipulate system state estimators on power grids are considered. A unified formulation for the

problem of constructing attacking vectors is developed for linearized measurement models. Based on this formulation, a

new low-complexity attacking strategy is shown to significantly outperform naive relaxation. It is demonstrated that it is

possible to defend against malicious data injection if a small subset of measurements can be made immune to the attacks.

However, selecting such subsets is a high-complexity combinatorial problem given the typically large size of electrical grids.

To address the complexity issue, a fast greedy algorithmto select a subset ofmeasurements to be protected is proposed.

Another greedy algorithm that facilitates the placement of secure phasor measurement units (PMUs) to defend against data

injection attacks is also developed. Simulations on the IEEE test systems demonstrate the benefits of the proposed

algorithms.

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21 Virtualized Optical Network Services across Multiple Domains for Grid Applications

In the field of grid computing over optical networks, joint scheduling of computing and network resources is an important

issue. However previous research efforts were static approaches, which are difficult to implement in multidomain optical

networks, especially in public carriers’ networks with lots of dynamic background traffic. In this article we put forward that

optical network virtualization can be a possible solution to the above mentioned problems. We analyze the benefits and

challenges of joint scheduling over a virtualized optical network (VON) across multiple domains and discuss the impacts of

dedicated and shared VON provisioning on scheduling problems. Then we propose a VON service composition framework

for grid applications, which is different from traditional interdomain routing protocol. Finally, we show the feasibility of our

proposal through simulation and an experimental demonstration over a field trial optical network testbed.

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IEEE Final Year Projects 2011-2012 :: Grid Computing:: Elysium Technologies Pvt Ltd